nltk_exploration.ipynb

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      "name": "nltk_exploration.ipynb",
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        "id": "view-in-github",
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        "<a href=\"https://colab.research.google.com/github/hrushikute/DataAnalytics/blob/master/nltk_exploration.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Exploring the NLP space."
      ],
      "metadata": {
        "id": "67EPdzFwokV0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import nltk\n",
        "nltk.download\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j1Ll1gCTooEn",
        "outputId": "9feb0f49-08db-46da-ad50-4d54087cf7f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method Downloader.download of <nltk.downloader.Downloader object at 0x7f88cd75ad50>>"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nltk.download('stopwords')\n",
        "from nltk.corpus import stopwords\n",
        "stopwords.words('english')[0:30]"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/"
        },
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['i',\n",
              " 'me',\n",
              " 'my',\n",
              " 'myself',\n",
              " 'we',\n",
              " 'our',\n",
              " 'ours',\n",
              " 'ourselves',\n",
              " 'you',\n",
              " \"you're\",\n",
              " \"you've\",\n",
              " \"you'll\",\n",
              " \"you'd\",\n",
              " 'your',\n",
              " 'yours',\n",
              " 'yourself',\n",
              " 'yourselves',\n",
              " 'he',\n",
              " 'him',\n",
              " 'his',\n",
              " 'himself',\n",
              " 'she',\n",
              " \"she's\",\n",
              " 'her',\n",
              " 'hers',\n",
              " 'herself',\n",
              " 'it',\n",
              " \"it's\",\n",
              " 'its',\n",
              " 'itself']"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "headers = ['label', 'message']\n",
        "data =pd.read_csv('SMSSpamCollection.csv', sep='|', names=headers)\n",
        "data.head()\n",
        "data2 =pd.read_csv('SMSSpamCollection', sep='\\t', names=headers , header=None)\n",
        "data2.head()"
      ],
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      "outputs": [
        {
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              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
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              "                                                     [key], {});\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
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            "text/plain": [
              "  label                                            message\n",
              "0   ham  Go until jurong point, crazy.. Available only ...\n",
              "1   ham                      Ok lar... Joking wif u oni...\n",
              "2  spam  Free entry in 2 a wkly comp to win FA Cup fina...\n",
              "3   ham  U dun say so early hor... U c already then say...\n",
              "4   ham  Nah I don't think he goes to usf, he lives aro..."
            ]
          },
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          "execution_count": 6
        }
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      "source": [
        "data2.describe()"
      ],
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      "outputs": [
        {
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          "data": {
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              "\n",
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>5572</td>\n",
              "      <td>5572</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>unique</th>\n",
              "      <td>2</td>\n",
              "      <td>5169</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>top</th>\n",
              "      <td>ham</td>\n",
              "      <td>Sorry, I'll call later</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>freq</th>\n",
              "      <td>4825</td>\n",
              "      <td>30</td>\n",
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              "\n",
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              "          const element = document.querySelector('#df-71601461-ef3b-440a-bf2f-da97f6a0bd31');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "  "
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            "text/plain": [
              "       label                 message\n",
              "count   5572                    5572\n",
              "unique     2                    5169\n",
              "top      ham  Sorry, I'll call later\n",
              "freq    4825                      30"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Explore the data set"
      ],
      "metadata": {
        "id": "eT8l03oFyKfJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Find the number of rows and columns of data set"
      ],
      "metadata": {
        "id": "l4LLtPT8y4Ni"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "num_of_rows = len(data2)\n",
        "num_of_rows"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "URITdJSP0iMv",
        "outputId": "529a8921-9df5-492b-dd77-13604cd4a362"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5572"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "num_of_cols = len(data2.columns)\n",
        "num_of_cols"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HkcFs0IN0mwf",
        "outputId": "6ffbe1da-5364-4d86-eac7-013a13dda7a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(f'There are {num_of_rows} of rows and {num_of_cols} of columns in data')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GYUrH5N00v1P",
        "outputId": "c1b66f67-617f-4c5a-cbc0-64d7c782d30f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "There are 5572 of rows and 2 of columns in data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Find the number of ham and spam of total rows"
      ],
      "metadata": {
        "id": "k9YMnfQk08XJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "num_of_spam = (data2['label'] == 'spam').sum()\n",
        "num_of_spam"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
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        "outputId": "f0ff2053-4dd8-4969-db53-48df03355d8d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "747"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "num_of_ham = (data2['label'] == 'ham').sum()\n",
        "num_of_ham"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nrkVlXLB1Wyl",
        "outputId": "0da906d6-a20e-4233-dbd1-3a89a2af726b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4825"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(f'There are in all {num_of_spam} spam and {num_of_ham} ham out of {num_of_rows}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1SMtD1rx4LZB",
        "outputId": "27759a71-511a-4c1d-ad79-1fff34ebe6f7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "There are in all 747 spam and 4825 ham out of 5572\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## NLP : Basics To clean the text\n",
        "\n",
        "1. Remove Punctuation\n",
        "2. Tokenization\n",
        "3. Removing Stopwords\n",
        "4. Lematization/Stemming "
      ],
      "metadata": {
        "id": "1U7ZbuMS4bS6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Remove punction\n",
        "\n",
        "import string\n",
        "string.punctuation"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "HTdVT7-K7fIB",
        "outputId": "7e863626-ba37-43b7-fe2f-e937709d1854"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'!\"#$%&\\'()*+,-./:;<=>?@[\\\\]^_`{|}~'"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def remove_punctuation(data):\n",
        "  # Used list comprehension\n",
        "  text_noPunct = [char for char in data if char not in string.punctuation]\n",
        "  return text_noPunct"
      ],
      "metadata": {
        "id": "Fad0O3PR8Jpa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data2['clean_message'] = data2['message'].apply(lambda x: remove_punctuation(x))\n",
        "data2.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "45EHN2qJ-Pdq",
        "outputId": "106c2510-412d-4522-ad67-a14b8bd0578c"
      },
      "execution_count": null,
      "outputs": [
        {
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              "\n",
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              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>clean_message</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
              "      <td>[G, o,  , u, n, t, i, l,  , j, u, r, o, n, g, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[O, k,  , l, a, r,  , J, o, k, i, n, g,  , w, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
              "      <td>[F, r, e, e,  , e, n, t, r, y,  , i, n,  , 2, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[U,  , d, u, n,  , s, a, y,  , s, o,  , e, a, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
              "      <td>[N, a, h,  , I,  , d, o, n, t,  , t, h, i, n, ...</td>\n",
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              "  </tbody>\n",
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              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
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              "      background-color: #E8F0FE;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ab1088eb-458d-4a3e-b9a9-546df2985028');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ...                                      clean_message\n",
              "0   ham  ...  [G, o,  , u, n, t, i, l,  , j, u, r, o, n, g, ...\n",
              "1   ham  ...  [O, k,  , l, a, r,  , J, o, k, i, n, g,  , w, ...\n",
              "2  spam  ...  [F, r, e, e,  , e, n, t, r, y,  , i, n,  , 2, ...\n",
              "3   ham  ...  [U,  , d, u, n,  , s, a, y,  , s, o,  , e, a, ...\n",
              "4   ham  ...  [N, a, h,  , I,  , d, o, n, t,  , t, h, i, n, ...\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Here the clean message have each character as list however we want sentences\n",
        "# Hence we need to add join by modifying the remove_punctuation function\n",
        "\n",
        "def remove_punctuation(data):\n",
        "  # Used list comprehension\n",
        "  text_noPunct = \"\".join([char for char in data if char not in string.punctuation])\n",
        "  return text_noPunct\n",
        "\n",
        "data2['clean_message_after'] = data2['message'].apply(lambda x: remove_punctuation(x))\n",
        "data2.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 250
        },
        "id": "dPbxxTZQ-p8a",
        "outputId": "308898ba-98f0-42ba-e86c-2a811e292ea0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-a30d1561-637b-4858-8ac8-216d7ac68cb4\">\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "    .dataframe thead th {\n",
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              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>clean_message</th>\n",
              "      <th>clean_message_after</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
              "      <td>[G, o,  , u, n, t, i, l,  , j, u, r, o, n, g, ...</td>\n",
              "      <td>Go until jurong point crazy Available only in ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[O, k,  , l, a, r,  , J, o, k, i, n, g,  , w, ...</td>\n",
              "      <td>Ok lar Joking wif u oni</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
              "      <td>[F, r, e, e,  , e, n, t, r, y,  , i, n,  , 2, ...</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[U,  , d, u, n,  , s, a, y,  , s, o,  , e, a, ...</td>\n",
              "      <td>U dun say so early hor U c already then say</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
              "      <td>[N, a, h,  , I,  , d, o, n, t,  , t, h, i, n, ...</td>\n",
              "      <td>Nah I dont think he goes to usf he lives aroun...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a30d1561-637b-4858-8ac8-216d7ac68cb4 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a30d1561-637b-4858-8ac8-216d7ac68cb4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ...                                clean_message_after\n",
              "0   ham  ...  Go until jurong point crazy Available only in ...\n",
              "1   ham  ...                            Ok lar Joking wif u oni\n",
              "2  spam  ...  Free entry in 2 a wkly comp to win FA Cup fina...\n",
              "3   ham  ...        U dun say so early hor U c already then say\n",
              "4   ham  ...  Nah I dont think he goes to usf he lives aroun...\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## Tokenize the text\n",
        "import re\n",
        "\n",
        "def tokenize_text(data):\n",
        "  tokens =re.split('\\W+',data)\n",
        "  return tokens\n",
        "\n",
        "data2['message_tokens'] = data2['clean_message_after'].apply(lambda x: tokenize_text(x.lower()))\n",
        "data2.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "XuSDJNyF_eVw",
        "outputId": "805c0247-7d52-432f-970c-49ea024f9b8f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-a367d07e-3188-4034-8f04-c97a7bc8d505\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>clean_message</th>\n",
              "      <th>clean_message_after</th>\n",
              "      <th>message_tokens</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
              "      <td>[G, o,  , u, n, t, i, l,  , j, u, r, o, n, g, ...</td>\n",
              "      <td>Go until jurong point crazy Available only in ...</td>\n",
              "      <td>[go, until, jurong, point, crazy, available, o...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[O, k,  , l, a, r,  , J, o, k, i, n, g,  , w, ...</td>\n",
              "      <td>Ok lar Joking wif u oni</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
              "      <td>[F, r, e, e,  , e, n, t, r, y,  , i, n,  , 2, ...</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
              "      <td>[free, entry, in, 2, a, wkly, comp, to, win, f...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[U,  , d, u, n,  , s, a, y,  , s, o,  , e, a, ...</td>\n",
              "      <td>U dun say so early hor U c already then say</td>\n",
              "      <td>[u, dun, say, so, early, hor, u, c, already, t...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
              "      <td>[N, a, h,  , I,  , d, o, n, t,  , t, h, i, n, ...</td>\n",
              "      <td>Nah I dont think he goes to usf he lives aroun...</td>\n",
              "      <td>[nah, i, dont, think, he, goes, to, usf, he, l...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a367d07e-3188-4034-8f04-c97a7bc8d505')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a367d07e-3188-4034-8f04-c97a7bc8d505 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a367d07e-3188-4034-8f04-c97a7bc8d505');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ...                                     message_tokens\n",
              "0   ham  ...  [go, until, jurong, point, crazy, available, o...\n",
              "1   ham  ...                     [ok, lar, joking, wif, u, oni]\n",
              "2  spam  ...  [free, entry, in, 2, a, wkly, comp, to, win, f...\n",
              "3   ham  ...  [u, dun, say, so, early, hor, u, c, already, t...\n",
              "4   ham  ...  [nah, i, dont, think, he, goes, to, usf, he, l...\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## Remove stopwords\n",
        "import nltk\n",
        "\n",
        "stop_words = nltk.corpus.stopwords.words('english')\n"
      ],
      "metadata": {
        "id": "cvxn-WcNAtwc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def remove_stopwords(data):\n",
        "  clean_data = [word for word in data if word not in stop_words]\n",
        "  return clean_data\n",
        "data2['message_after_stop'] = data2['message_tokens'].apply(lambda x: remove_stopwords(x))\n",
        "data2.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "XsJHi9csB1kg",
        "outputId": "8d76a99d-af08-490c-8edd-613de71a790b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-f3dbb78a-38e6-433b-bf49-8658818f605a\">\n",
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              "<style scoped>\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>clean_message</th>\n",
              "      <th>clean_message_after</th>\n",
              "      <th>message_tokens</th>\n",
              "      <th>message_after_stop</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
              "      <td>[G, o,  , u, n, t, i, l,  , j, u, r, o, n, g, ...</td>\n",
              "      <td>Go until jurong point crazy Available only in ...</td>\n",
              "      <td>[go, until, jurong, point, crazy, available, o...</td>\n",
              "      <td>[go, jurong, point, crazy, available, bugis, n...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[O, k,  , l, a, r,  , J, o, k, i, n, g,  , w, ...</td>\n",
              "      <td>Ok lar Joking wif u oni</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
              "      <td>[F, r, e, e,  , e, n, t, r, y,  , i, n,  , 2, ...</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
              "      <td>[free, entry, in, 2, a, wkly, comp, to, win, f...</td>\n",
              "      <td>[free, entry, 2, wkly, comp, win, fa, cup, fin...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[U,  , d, u, n,  , s, a, y,  , s, o,  , e, a, ...</td>\n",
              "      <td>U dun say so early hor U c already then say</td>\n",
              "      <td>[u, dun, say, so, early, hor, u, c, already, t...</td>\n",
              "      <td>[u, dun, say, early, hor, u, c, already, say]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
              "      <td>[N, a, h,  , I,  , d, o, n, t,  , t, h, i, n, ...</td>\n",
              "      <td>Nah I dont think he goes to usf he lives aroun...</td>\n",
              "      <td>[nah, i, dont, think, he, goes, to, usf, he, l...</td>\n",
              "      <td>[nah, dont, think, goes, usf, lives, around, t...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "              style=\"display:none;\">\n",
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              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f3dbb78a-38e6-433b-bf49-8658818f605a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f3dbb78a-38e6-433b-bf49-8658818f605a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ...                                 message_after_stop\n",
              "0   ham  ...  [go, jurong, point, crazy, available, bugis, n...\n",
              "1   ham  ...                     [ok, lar, joking, wif, u, oni]\n",
              "2  spam  ...  [free, entry, 2, wkly, comp, win, fa, cup, fin...\n",
              "3   ham  ...      [u, dun, say, early, hor, u, c, already, say]\n",
              "4   ham  ...  [nah, dont, think, goes, usf, lives, around, t...\n",
              "\n",
              "[5 rows x 6 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Suplemental Data Cleaning : Using stemming\n",
        "\n",
        "Test out porter stemer"
      ],
      "metadata": {
        "id": "-GLtHQM8CoPR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import nltk\n",
        "import re\n",
        "import pandas as pd\n",
        "nltk.download('wordnet')\n",
        "\n",
        "pd.set_option('display.max_colwidth',100)\n",
        "ps = nltk.PorterStemmer()\n",
        "stop_words = nltk.corpus.stopwords.words('english')\n",
        "\n",
        "data3=pd.read_csv('SMSSpamCollection', sep='\\t', names=headers , header=None)\n",
        "data3.head()\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "ZIca9rzW0Oc1",
        "outputId": "13fc1611-9952-4237-fb3a-b48e686fcedc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/wordnet.zip.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d4fb8a95-bdb5-4ab9-8a1f-d4efe579628d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d4fb8a95-bdb5-4ab9-8a1f-d4efe579628d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label                                                                                              message\n",
              "0   ham  Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...\n",
              "1   ham                                                                        Ok lar... Joking wif u oni...\n",
              "2  spam  Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...\n",
              "3   ham                                                    U dun say so early hor... U c already then say...\n",
              "4   ham                                        Nah I don't think he goes to usf, he lives around here though"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def Pre_process_data(text_data):\n",
        "  text_noPunct = \"\".join([char for char in text_data if char not in string.punctuation])\n",
        "  tokenize_text = re.split('\\W+',text_noPunct)\n",
        "  no_stop_text = [word for word in tokenize_text if word not in stop_words]\n",
        "  \n",
        "  return no_stop_text\n",
        "   "
      ],
      "metadata": {
        "id": "Lvrum_gkTMCo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data3['pre_procs_data'] = data3['message'].apply(lambda x : Pre_process_data(x.lower()))\n",
        "data3.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "1plo4RInVE-F",
        "outputId": "d2af0678-a8af-4862-c795-ff3b926059a4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-fd1b77f8-e39c-43f0-8f06-da709063371d\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>pre_procs_data</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "      <td>[go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "      <td>[free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[u, dun, say, early, hor, u, c, already, say]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "      <td>[nah, dont, think, goes, usf, lives, around, though]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fd1b77f8-e39c-43f0-8f06-da709063371d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fd1b77f8-e39c-43f0-8f06-da709063371d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fd1b77f8-e39c-43f0-8f06-da709063371d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ...                                                                                       pre_procs_data\n",
              "0   ham  ...  [go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]\n",
              "1   ham  ...                                                                       [ok, lar, joking, wif, u, oni]\n",
              "2  spam  ...  [free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...\n",
              "3   ham  ...                                                        [u, dun, say, early, hor, u, c, already, say]\n",
              "4   ham  ...                                                 [nah, dont, think, goes, usf, lives, around, though]\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def stemming_data(text_data):\n",
        "  stem_text = [ps.stem(word) for word in text_data]\n",
        "  return stem_text\n",
        "\n",
        "data3['stem_text'] = data3['pre_procs_data'].apply(lambda x : stemming_data(x))\n",
        "data3.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "id": "c8wWO9PmVeEg",
        "outputId": "7c48ebb2-6abb-4ccb-d2cc-d5a67502bc8a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-8d331273-e8c3-4074-83cb-fdbc13fa15a6\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>pre_procs_data</th>\n",
              "      <th>stem_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "      <td>[go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]</td>\n",
              "      <td>[go, jurong, point, crazi, avail, bugi, n, great, world, la, e, buffet, cine, got, amor, wat]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "      <td>[ok, lar, joke, wif, u, oni]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "      <td>[free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...</td>\n",
              "      <td>[free, entri, 2, wkli, comp, win, fa, cup, final, tkt, 21st, may, 2005, text, fa, 87121, receiv,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[u, dun, say, early, hor, u, c, already, say]</td>\n",
              "      <td>[u, dun, say, earli, hor, u, c, alreadi, say]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "      <td>[nah, dont, think, goes, usf, lives, around, though]</td>\n",
              "      <td>[nah, dont, think, goe, usf, live, around, though]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8d331273-e8c3-4074-83cb-fdbc13fa15a6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8d331273-e8c3-4074-83cb-fdbc13fa15a6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8d331273-e8c3-4074-83cb-fdbc13fa15a6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ...                                                                                            stem_text\n",
              "0   ham  ...        [go, jurong, point, crazi, avail, bugi, n, great, world, la, e, buffet, cine, got, amor, wat]\n",
              "1   ham  ...                                                                         [ok, lar, joke, wif, u, oni]\n",
              "2  spam  ...  [free, entri, 2, wkli, comp, win, fa, cup, final, tkt, 21st, may, 2005, text, fa, 87121, receiv,...\n",
              "3   ham  ...                                                        [u, dun, say, earli, hor, u, c, alreadi, say]\n",
              "4   ham  ...                                                   [nah, dont, think, goe, usf, live, around, though]\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Apply preprocesig using lemmatizer : Using WordnetLemmatizer"
      ],
      "metadata": {
        "id": "uZVS_GffbZBG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "wn = nltk.WordNetLemmatizer()\n",
        "\n",
        "def lemmatize_data(text_data):\n",
        "  lemma_text = [wn.lemmatize(word) for word in text_data]\n",
        "  return lemma_text\n",
        "\n",
        "data3['lemmatize_text'] = data3['pre_procs_data'].apply(lambda x : lemmatize_data(x))\n",
        "data3.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 389
        },
        "id": "dqGFLmliazmQ",
        "outputId": "1d23a1a2-abbb-4180-bfb4-fa0dcd560d6a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-82eed0d1-419a-456d-a64f-ac167e327e3a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>pre_procs_data</th>\n",
              "      <th>stem_text</th>\n",
              "      <th>lemmatize_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "      <td>[go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]</td>\n",
              "      <td>[go, jurong, point, crazi, avail, bugi, n, great, world, la, e, buffet, cine, got, amor, wat]</td>\n",
              "      <td>[go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "      <td>[ok, lar, joke, wif, u, oni]</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "      <td>[free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...</td>\n",
              "      <td>[free, entri, 2, wkli, comp, win, fa, cup, final, tkt, 21st, may, 2005, text, fa, 87121, receiv,...</td>\n",
              "      <td>[free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[u, dun, say, early, hor, u, c, already, say]</td>\n",
              "      <td>[u, dun, say, earli, hor, u, c, alreadi, say]</td>\n",
              "      <td>[u, dun, say, early, hor, u, c, already, say]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "      <td>[nah, dont, think, goes, usf, lives, around, though]</td>\n",
              "      <td>[nah, dont, think, goe, usf, live, around, though]</td>\n",
              "      <td>[nah, dont, think, go, usf, life, around, though]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-82eed0d1-419a-456d-a64f-ac167e327e3a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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              "          const element = document.querySelector('#df-82eed0d1-419a-456d-a64f-ac167e327e3a');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "  "
            ],
            "text/plain": [
              "  label  ...                                                                                       lemmatize_text\n",
              "0   ham  ...  [go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]\n",
              "1   ham  ...                                                                       [ok, lar, joking, wif, u, oni]\n",
              "2  spam  ...  [free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...\n",
              "3   ham  ...                                                        [u, dun, say, early, hor, u, c, already, say]\n",
              "4   ham  ...                                                    [nah, dont, think, go, usf, life, around, though]\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Vectorizing the Data : \n",
        "It is used to convert text data to numbers to feed it to Machine learning model\n",
        "\n",
        "1. CountVectorizer\n",
        "2. N-gram\n",
        "3. TF-IDF\n"
      ],
      "metadata": {
        "id": "9-AAuDHVb1JF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Let import the data \n",
        "import pandas as pd\n",
        "import re\n",
        "import string\n",
        "import nltk\n",
        "nltk.download('wordnet')\n",
        "\n",
        "pd.set_option('display.max_colwidth',100)\n",
        "ps = nltk.PorterStemmer()\n",
        "stop_words = nltk.corpus.stopwords.words('english')\n",
        "wn = nltk.WordNetLemmatizer()\n",
        "\n",
        "headers = ['label','message']\n",
        "df = pd.read_csv('SMSSpamCollection', sep='\\t',names=headers, header=None)\n",
        "df.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "iFZAfMNBteaS",
        "outputId": "94ad58da-e642-4f57-b295-35b78dc8e094"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "<style scoped>\n",
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              "\n",
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              "      <th></th>\n",
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              "      <th>message</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "  </style>\n",
              "\n",
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              "          document.querySelector('#df-b29d3508-15da-441d-a753-36f97ae0d7af button.colab-df-convert');\n",
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              "          const element = document.querySelector('#df-b29d3508-15da-441d-a753-36f97ae0d7af');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
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              "    </div>\n",
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              "  "
            ],
            "text/plain": [
              "  label                                                                                              message\n",
              "0   ham  Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...\n",
              "1   ham                                                                        Ok lar... Joking wif u oni...\n",
              "2  spam  Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...\n",
              "3   ham                                                    U dun say so early hor... U c already then say...\n",
              "4   ham                                        Nah I don't think he goes to usf, he lives around here though"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Preporcess Data\n",
        "1.  Remove punctuation\n",
        "2.  Tokenize\n",
        "3.  Remove stop words\n",
        "4.  Lematize the data"
      ],
      "metadata": {
        "id": "NnEQ-LOCuKL7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def PreProcessin_data(text_data):\n",
        "  puct_removal =\"\".join([char for char in text_data if  char not in string.punctuation])\n",
        "  tokenzie_text = re.split('\\W+', puct_removal)\n",
        "  stop_words_removal = [wn.lemmatize(word)   for word in tokenzie_text if word not in stop_words]\n",
        "  # lema_text= [wn.lemmatize(word) for word in stop_word_removal]\n",
        "  return stop_words_removal\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "Dt0PUu-cvJ9O"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['clean_data'] = df['message'].apply(lambda x: PreProcessin_data(x.lower()))\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "m9f3F4ghzlhY",
        "outputId": "686d41da-1992-4e3a-83fb-ad3462fefbd0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>clean_data</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "      <td>[go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "      <td>[free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[u, dun, say, early, hor, u, c, already, say]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "      <td>[nah, dont, think, go, usf, life, around, though]</td>\n",
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              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-03bf52fb-b6d7-49f7-a911-40211872c79a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-03bf52fb-b6d7-49f7-a911-40211872c79a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ...                                                                                           clean_data\n",
              "0   ham  ...  [go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]\n",
              "1   ham  ...                                                                       [ok, lar, joking, wif, u, oni]\n",
              "2  spam  ...  [free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...\n",
              "3   ham  ...                                                        [u, dun, say, early, hor, u, c, already, say]\n",
              "4   ham  ...                                                    [nah, dont, think, go, usf, life, around, though]\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## CountVectorizer"
      ],
      "metadata": {
        "id": "XD9pw2c0lESE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "\n",
        "count_vect = CountVectorizer(analyzer=PreProcessin_data)\n",
        "\n",
        "x_count=count_vect.fit_transform(df['message'])\n",
        "\n",
        "print(x_count.shape)\n",
        "print(count_vect.get_feature_names())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xDAyJPRpz7BY",
        "outputId": "2ff0fd44-4a2b-42b9-a3fa-7578c506889e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(5572, 11045)\n",
            "['', '0', '008704050406', '0089my', '0121', '01223585236', '01223585334', '0125698789', '02', '020603', '0207', '02070836089', '02072069400', '02073162414', '02085076972', '020903', '021', '050703', '0578', '06', '060505', '061104', '07008009200', '07046744435', '07090201529', '07090298926', '07099833605', '071104', '07123456789', '0721072', '07732584351', '07734396839', '07742676969', '07753741225', '0776xxxxxxx', '07786200117', '077xxx', '078', '07801543489', '07808', '07808247860', '07808726822', '07815296484', '07821230901', '0784987', '0789xxxxxxx', '0794674629107880867867', '0796XXXXXX', '07973788240', '07XXXXXXXXX', '07xxxxxxxxx', '0800', '08000407165', '08000776320', '08000839402', '08000930705', '08000938767', '08001950382', '08002888812', '08002986030', '08002986906', '08002988890', '08006344447', '0808', '08081263000', '08081560665', '0825', '0844', '08448350055', '08448714184', '0845', '08450542832', '08452810071', '08452810073', '08452810075over18s', '0870', '08700621170150p', '08701213186', '08701237397', '08701417012', '08701417012150p', '0870141701216', '087016248', '08701752560', '087018728737', '0870241182716', '08702490080', '08702840625', '08702840625COMUK', '08704439680', '08704439680TsCs', '08706091795', '0870737910216yrs', '08707500020', '08707509020', '0870753331018', '08707808226', '08708034412', '08708800282', '08709222922', '08709501522', '0870k', '087104711148', '08712101358', '08712103738', '0871212025016', '08712300220', '087123002209am7pm', '08712317606', '08712400200', '08712400603', '08712402050', '08712402578', '08712402779', '08712402902', '08712402972', '08712404000', '08712405020', '08712405022', '08712460324', '08712460324nat', '08712466669', '0871277810710pmin', '0871277810810', '0871277810910pmin', '087143423992stop', '087147123779am7pm', '08714712379', '08714712388', '08714712394', '08714712412', '08714714011', '08714719523', '08715203028', '08715203649', '08715203652', '08715203656', '08715203677', '08715203685', '08715203694', '08715205273', '08715500022', '08715705022', '08717111821', '08717168528', '08717205546', '08717507382', '08717507711', '08717509990', '08717890890', '08717895698', '08717898035', '08718711108', '08718720201', '08718723815', '08718725756', '08718726270', '08718726270150gbpmtmsg18', '08718726970', '08718726971', '08718726978', '087187272008', '08718727868', '08718727870', '08718729755', '08718729758', '08718730555', '08718730666', '08718738001', '08718738002', '08718738034', '08719180219', '08719180248', '08719181259', '08719181503', '08719181513', '08719839835', '08719899217', '08719899229', '08719899230', '09041940223', '09050000301', '09050000332', '09050000460', '09050000555', '09050000878', '09050000928', '09050001295', '09050001808', '09050002311', '09050003091', '09050005321', '09050090044', '09050280520', '09053750005', '09056242159', '09057039994', '09058091854', '09058091870', '09058094454', '09058094455', '09058094507', '09058094565', '09058094583', '09058094594', '09058094597', '09058094599', '09058095107', '09058095201', '09058097189', '09058097218', '09058098002', '09058099801', '09061104276', '09061104283', '09061209465', '09061213237', '09061221061', '09061221066', '09061701444', '09061701461', '09061701851', '09061701939', '09061702893', '09061743386', '09061743806', '09061743810', '09061743811', '09061744553', '09061749602', '09061790121', '09061790125', '09061790126', '09063440451', '09063442151', '09063458130', '0906346330', '09064011000', '09064012103', '09064012160', '09064015307', '09064017295', '09064017305', '09064018838', '09064019014', '09064019788', '09065069120', '09065069154', '09065171142stopsms08', '09065171142stopsms08718727870150ppm', '09065174042', '09065394514', '09065394973', '09065989180', '09065989182', '09066350750', '09066358152', '09066358361', '09066361921', '09066362206', '09066362220', '09066362231', '09066364311', '09066364349', '09066364589', '09066368327', '09066368470', '09066368753', '09066380611', '09066382422', '09066612661', '09066649731from', '09066660100', '09071512432', '09071512433', '09071517866', '09077818151', '09090204448', '09090900040', '09094100151', '09094646631', '09094646899', '09095350301', '09096102316', '09099725823', '09099726395', '09099726429', '09099726481', '09099726553', '09111030116', '09111032124', '09701213186', '0ANETWORKS', '1', '10', '100', '1000', '10000', '100000', '1000CALL', '100603', '100pSMS', '1010', '1013', '101mega', '1030', '10803', '10K', '10am', '10am7pm', '10am9pm', '10k', '10p', '10pmin', '10ppm', '10th', '11', '1120', '113', '1131', '11414', '1146', '1148', '116', '1172', '118pmsg', '11mths', '12', '120', '12000pes', '1205', '121', '1225', '123', '1230', '125', '1250', '125gift', '128', '12Mths', '12hours', '12hrs', '12mths', '12price', '13', '130', '131004', '1327', '13404', '139', '140', '1405', '140ppm', '145', '1450', '146tf150p', '14thMarch', '150', '1500', '150Mtmsgrcvd18', '150P', '150PPM', '150ea', '150moreFrmMob', '150msg', '150p', '150pMSGRCVD', '150pMTmsg', '150pMsg', '150pMsgrcvdHGSuite3422LandsRowW1J6HL', '150pMt', '150pMtmsgrcvd18', '150pSMS', '150pday', '150perWKsub', '150perweeksub', '150pm', '150pmeg', '150pmin', '150pmmorefrommobile2BremovedMobyPOBox734LS27YF', '150pmsg', '150ppermessSubscription', '150ppm', '150ppmPOBox10183BhamB64XE', '150ppmsg', '150prcvd', '150ptext', '150ptone', '150pw', '150pwk', '150rcvd', '150week', '150wk', '151', '1526', '153', '15541', '15pmin', '16', '1680', '169', '16only', '177', '18', '180', '181104', '1843', '186', '18only', '18ptxt', '18yrs', '195', '1956669', '1AppleDayNo', '1Cup', '1DA', '1ER', '1Hanuman', '1His', '1IM', '1LemonDayNo', '1McFlyAll', '1Tulsi', '1U', '1Unbreakable', '1Winaweek', '1Winawk', '1YF', '1childish', '1hr', '1million', '1minMobsmore', '1minMobsmoreLKPOBOX177HP51FL', '1minmoremobsEMSPOBox45PO139WA', '1month', '1pm', '1st', '1st4Terms', '1stchoicecouk', '1stone', '1u', '1x150pwk', '2', '20', '200', '2000', '20000', '2003', '2004', '2005', '2006', '2007', '2025050', '20F', '20M12AQ', '20p', '20pmin', '21', '211104', '215', '21870000Hi', '21m', '21st', '22', '220CM2', '23', '2309', '230ish', '24', '241', '241004', '247MP', '24Hrs', '24M', '24hrs', '24th', '25', '250', '250k', '255', '25F', '25p', '260305', '261004', '261104', '2667', '26th', '2703', '27603', '28', '2814032', '285', '28days', '28th', '28thFebTCs', '290305', '29100', '29M', '2B', '2Bajarangabali', '2C', '2DOCDPLEASE', '2EZ', '2End', '2GETHA', '2GEVA', '2Hook', '2I', '2IM', '2KBSubject', '2MORO', '2MOROW', '2MORRO', '2MRW', '2MWEN', '2NITE', '2NITETELL', '2PX', '2Police', '2StopTx', '2StopTxt', '2U', '2Untamed', '2WATERSHD', '2WT', '2WU', '2When', '2bold', '2channel', '2day', '2daylove', '2exit', '2geva', '2go', '2godid', '2gthr', '2hrs', '2marrow', '2moro', '2morow', '2morro', '2morrow', '2morrowxxxx', '2mro', '2mrw', '2naughty', '2nd', '2nhite', '2nights', '2nite', '2optout', '2optoutD3WV', '2p', '2rcv', '2stop', '2stoptxt', '2u', '2u2', '2waxsto', '2wks', '2years', '2yr', '2yrs', '3', '30', '300', '3000', '300603', '300603tcsBCM4235WC1N3XXcallcost150ppmmobilesvary', '300p', '3030', '30Apr', '30pptxt', '30th', '31', '3100', '310303', '311004', '31pmsg150p', '32000', '3230', '32323', '326', '32F', '330', '3350', '3365', '350', '3510i', '35p', '3650', '36504', '3680', '3680Offer', '373', '3750', '375max', '38', '391784', '399', '3AJ', '3Cover', '3DB', '3G', '3GBP', '3Lions', '3MOBILE', '3Maruti', '3POUND', '3SS', '3Sentiment', '3U', '3UZ', '3Unkempt', '3Wife', '3XX', '3d', '3days', '3g', '3hrs', '3lp', '3miles', '3mins', '3optical', '3qxj9', '3rd', '3u', '3wk', '3wks', '3x', '4', '40', '400', '400minsCall', '402', '4041', '40411', '40533', '40GB', '40mph', '415', '41685', '41782', '420', '42049', '4217', '42478', '42810', '430', '434', '44', '4403LDNW1A7RW18', '447797706009', '447801259231', '447per', '448712404000Please', '449050000301', '449071512431', '449month', '45', '450', '450Ppw', '450p', '450pw', '45239', '46', '47', '4712', '4742', '48', '4882', '48922', '49557', '4BREKKIE', '4Cook', '4EVA', '4GET', '4JX', '4Lux', '4MY', '4Pavanaputra', '4Press', '4TCtxt', '4U', '4WARD', '4a', '4d', '4eva', '4few', '4fil', '4get', '4give', '4got', '4goten', '4info', '4mths', '4o', '4rowdy', '4some1', '4th', '4thNOVBEHIND', '4the', '4txt120p', '4txtú120', '4u', '4uTxt', '4ui', '4w', '4wrd', '4years', '5', '50', '500', '5000', '500000', '505060', '50award', '50p', '515', '515pm', '5226', '5249', '526', '528', '530', '532', '54', '542', '545', '5903', '5Gardener', '5Gently', '5I', '5K', '5Sankatmochan', '5Terror', '5WB', '5WE', '5WQ', '5digital', '5free', '5ful', '5ish', '5min', '5mls', '5month', '5p', '5pm', '5th', '5we', '5wkg', '5years', '6', '600', '6031', '60400thousadi', '60P', '60pmin', '61200', '61610', '62220Cncl', '6230', '62468', '62735', '630', '63miles', '645', '645pm', '650', '6669', '67441233', '68866', '69101', '69200', '69669', '69696', '69698', '69855', '6986618', '69876', '69888', '69888Nyt', '69911', '69969', '69988', '6Cruel', '6HL', '6HouseMaid', '6Ramaduth', '6WU', '6ZF', '6days', '6hrs', '6ish', '6missed', '6months', '6pm', '6romantic', '6th', '6times', '7', '700', '71', '725', '7250', '7250i', '730', '730ish', '730pm', '731', '74355', '750', '75000', '7548', '7634', '7684', '7732584351', '78', '786', '7876150ppm', '78pmin', '79', '7Children', '7Mahaveer', '7Romantic', '7WS', '7ZS', '7am', '7cfca1a', '7ish', '7oz', '7pm', '7shy', '7th', '8', '80', '800', '8000930705', '80062', '8007', '80082', '80086', '80122300pwk', '80155', '80160', '80182', '8027', '80488', '80488biz', '80608', '8077', '80878', '81010', '81151', '81303', '81618', '816183', '82242', '82277', '82277unsub', '82324', '82468', '830', '83021', '83039', '83049', '83110', '83118', '83222', '83332Please', '83338', '83355', '83370', '83383', '83435', '83600', '83738', '84', '84025', '84122', '84128', '84128custcare', '84199', '84484', '85', '850', '85023', '85069', '85222', '85233', '8552', '85555', '86021', '861', '863', '864233', '86688', '86888', '87021', '87066', '87070', '87077', '87121', '87131', '8714714', '87239', '87575', '8800', '88039', '88039SkilGmeTsCs087147403231WinawkAge16', '88066', '88088', '88222', '8830', '88600', '88800', '8883', '88877', '88877FREE', '88888', '89034', '89070', '89080', '89105', '89123', '89545', '89555', '89693', '89938', '8Attractive', '8Ball', '8Lovable', '8Neighbour', '8WP', '8am', '8hr', '8lb', '8o', '8pm', '8th', '9', '900', '9061100010', '9153', '924', '92H', '930', '945', '946', '95pax', '96', '97N7QP', '98321561', '9996', '9AE', '9YT', '9am', '9am11pm', '9decent', '9funny', '9ja', '9pm', '9t', '9th', 'A', 'A21', 'ABOUT', 'ABOUTAS', 'ABTA', 'ACCEPT', 'ACL03530150PM', 'ACTION', 'ACTUALLY', 'AD', 'ADAM', 'ADDAMSFA', 'ADP', 'ADRINK', 'AFEW', 'AFTER', 'AFTERNOON', 'AG', 'AGAIN', 'AGAINST', 'AGAINcall', 'AGE', 'AGESRING', 'AGO', 'AGOCUSOON', 'AGreen', 'AH', 'AIG', 'AINT', 'AL', 'ALERT', 'ALETTER', 'ALEX', 'ALL', 'ALRITE', 'ALSO', 'ALWAYS', 'AM', 'AMY', 'AN', 'ANAL', 'AND', 'ANNIE', 'ANS', 'ANSWER', 'ANTELOPE', 'ANYTHING', 'AOM', 'APPY', 'APRIL', 'ARE', 'AREA', 'ARIES', 'AROUND', 'ARR', 'AS', 'ASAP', 'ASKED', 'ASLEEP', 'ASTHERE', 'ASUSUAL1', 'AT', 'AUCTION', 'AUGUST', 'AV', 'AVA', 'AVE', 'AVENT', 'AWAITING', 'AWARD', 'AXIS', 'Aah', 'Aaniye', 'Aaooooright', 'Ab', 'Abbey', 'Abeg', 'Aberdeen', 'Abiola', 'About', 'Abt', 'Accept', 'Accident', 'AccommodationVouchers', 'Account', 'Accounts', 'Ache', 'Acnt', 'AcoEntry41', 'Activate', 'Active', 'Actually', 'Address', 'Admirer', 'Adrian', 'Adult', 'Aeronautics', 'Affectionate', 'Affectionsamp', 'Aft', 'After', 'AfterNoon', 'Afternoon', 'Afternoons', 'Aftr', 'Again', 'Agalla', 'Age', 'Ages', 'Ah', 'Ahhh', 'Ahhhhjust', 'Ahmad', 'Aight', 'Air', 'Airtel', 'Aiya', 'Aiyah', 'Aiyar', 'Aiyo', 'Aka', 'AkonLonely', 'Al', 'AlaikkumPride', 'Alaipayuthe', 'Aldrine', 'AlertFrom', 'Alex', 'Alfie', 'Algarve', 'All', 'AllahRakhesh', 'Allahmeet', 'Allo', 'Almost', 'Already', 'Alright', 'Alrite', 'Also', 'Although', 'Always', 'Alwys', 'Am', 'Amanda', 'Amazing', 'Ambrithmaduraimet', 'American', 'Ami', 'Amrca', 'Amrita', 'Amy', 'An', 'And', 'Annoying', 'Another', 'Any', 'Anyone', 'Anything', 'Anytime', 'Anyway', 'Anyways', 'Apart', 'Apnt', 'Apo', 'Apparently', 'Apply', 'Apps', 'Appt', 'ArPraveesh', 'Arabian', 'Arcade', 'Ard', 'Are', 'Argh', 'Argument', 'Armand', 'Arms', 'Arngd', 'Arrow', 'Arsenal', 'Arul', 'Arun', 'As', 'Ashley', 'Asian', 'Ask', 'Asking', 'Aslamalaikkuminsha', 'Astronomer', 'At', 'Athletic', 'Atlanta', 'Atlast', 'Atleast', 'Auction', 'Audrey', 'Audrie', 'August', 'Auntie', 'Australia', 'Available', 'Ave', 'Avenge', 'Awarded', 'Awesome', 'Aww', 'Awww', 'Ay', 'B', 'B4', 'B4U', 'BA128NNFWFLY150ppm', 'BABE', 'BABEPROBPOP', 'BABES', 'BABESOZI', 'BABY', 'BABYHOPE', 'BACK', 'BACKWARDS', 'BAHAMAS', 'BAILIFF', 'BAK', 'BANG', 'BANK', 'BANNEDUK', 'BARMED', 'BATH', 'BBC', 'BBDELUXE', 'BBDpooja', 'BBDthts', 'BBlue', 'BCK', 'BCM1896WC1N3XX', 'BCM4284', 'BCMSFWC1N3XX', 'BCozI', 'BE', 'BEAUTIFUL', 'BED', 'BEDROOMLOVE', 'BEEN', 'BEER', 'BEFORE', 'BEGIN', 'BELIEVE', 'BEST', 'BETTER', 'BETTERSN', 'BIDS', 'BIG', 'BILL', 'BILLING', 'BIRD', 'BIRTHDAY', 'BIT', 'BK', 'BLOKE', 'BLOKES', 'BLOODSend', 'BMW', 'BOATIN', 'BONUS', 'BOO', 'BOOKS', 'BORED', 'BORING', 'BORNPLEASE', 'BOUT', 'BOUTxx', 'BOX', 'BOX139', 'BOX334SK38ch', 'BOX385', 'BOX420', 'BOX42WR29C', 'BOX95QU', 'BOX97N7QP', 'BOYF', 'BOYFRIEND', 'BRAND', 'BREAK', 'BREAKIN', 'BREATHE1', 'BRISTOL', 'BROKE', 'BROTHER', 'BSLVYL', 'BT', 'BTHERE', 'BTW', 'BTnational', 'BTnationalrate', 'BTooth', 'BUDDY', 'BUS', 'BUT', 'BUTTHERES', 'BUZ', 'BY', 'BYATCH', 'Baaaaaaaabe', 'Baaaaabe', 'Babe', 'Babes', 'Baby', 'BabyGoodbye', 'Back', 'Bad', 'Badrith', 'Bahamas', 'Ball', 'Balls', 'Bam', 'BangBabes', 'Bani', 'Bank', 'Barbie', 'Barkleys', 'Barry', 'Bbq', 'Bc', 'Bcm', 'Bcoz', 'Bday', 'Be', 'Bears', 'Beautiful', 'Beauty', 'Bec', 'Becaus', 'Because', 'Become', 'Becomes', 'Becoz', 'Been', 'Beer', 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'step', 'stereo', 'sterling', 'sterm', 'steve', 'stevelike', 'steyn', 'sth', 'stick', 'sticky', 'stifled', 'still', 'stillmaybe', 'stink', 'stitch', 'stock', 'stocked', 'stolen', 'stomach', 'stomp', 'stone', 'stoner', 'stool', 'stop', 'stopCost', 'stopped', 'stoptxtStop', 'stoptxtstop', 'store', 'storelike', 'story', 'str', 'str8', 'straight', 'strain', 'strange', 'stranger', 'strangersaw', 'street', 'streetshall', 'stress', 'stressed', 'stressful', 'stressfull', 'stretch', 'strewn', 'strict', 'strike', 'string', 'strip', 'stripe', 'strong', 'strongly', 'strt', 'strtd', 'struggling', 'sts', 'stubborn', 'stuck', 'studdying', 'student', 'studentsthis', 'studio', 'study', 'studying', 'studyn', 'stuff', 'stuff42moro', 'stuffed', 'stuffing', 'stuffleaving', 'stuffwhy', 'stunning', 'stupid', 'style', 'styling', 'stylish', 'sub', 'subject', 'subletting', 'submitted', 'submitting', 'subscribe', 'subscribed', 'subscriber', 'subscription', 'subscrition', 'subsequent', 'subtoitles', 'success', 'successful', 'successfully', 'suck', 'sucker', 'sudden', 'suddenly', 'sudn', 'sue', 'suffer', 'suffering', 'suffers', 'sufficient', 'sugar', 'sugardad', 'suggest', 'suggestion', 'suit', 'suite', 'suitemates', 'sum', 'sum1', 'sumfing', 'summer', 'summon', 'sumthin', 'sun', 'sun0819', 'sunday', 'sundayish', 'sunlight', 'sunny', 'sunoco', 'sunroof', 'sunshine', 'suntec', 'sup', 'super', 'superb', 'superior', 'supervisor', 'suply', 'supose', 'supplier', 'supply', 'support', 'supportproviding', 'supportvery', 'suppose', 'supposed', 'supreme', 'sura', 'sure', 'surely', 'surf', 'surfing', 'surgical', 'surname', 'surprise', 'surprised', 'surrender', 'surrounded', 'survey', 'surya', 'sutra', 'sux', 'suzy', 'svc', 'swalpa', 'swann', 'swashbuckling', 'swatch', 'sway', 'swear', 'sweater', 'sweatter', 'sweet', 'sweetie', 'swell', 'swhrt', 'swimming', 'swimsuit', 'swing', 'swiss', 'switch', 'swollen', 'swoop', 'swt', 'syd', 'syllabus', 'symbol', 'synced', 'syrup', 'system', 't', 'ta', 'table', 'tablet', 'tackle', 'taco', 'tactful', 'tactless', 'tag', 'tagged', 'tahan', 'tai', 'tait', 'take', 'taken', 'takenOnly', 'takin', 'taking', 'talent', 'talk', 'talking', 'tall', 'tallahassee', 'tallent', 'tamilnaduthen', 'tampa', 'tank', 'tantrum', 'tap', 'tape', 'tariff', 'tarpon', 'taste', 'tat', 'tattoo', 'tau', 'taught', 'taunton', 'tax', 'taxi', 'taxless', 'taxt', 'taylor', 'tb', 'tc', 'tddnewsletteremc1couk', 'tea', 'teach', 'teacher', 'teaching', 'teacoffee', 'team', 'tear', 'tease', 'teasing', 'tech', 'technical', 'technology', 'teenager', 'teeth', 'teethif', 'teethis', 'teju', 'tel', 'telephone', 'tell', 'telling', 'telly', 'telphone', 'telugu', 'teluguthts', 'temales', 'temp', 'temper', 'temple', 'ten', 'tendency', 'tensed', 'term', 'terrible', 'terrific', 'terrorist', 'tescos', 'test', 'testing', 'texas', 'text', 'textand', 'textbook', 'texted', 'textin', 'texting', 'textoperator', 'textsweekend', 'tgxxrz', 'th', 'thandiyachu', 'thangam', 'thangamits', 'thank', 'thanks', 'thanks2', 'thanksgiving', 'thanx', 'thanxxx', 'that2worzels', 'thatd', 'thatdont', 'thati', 'thatll', 'thatnow', 'thats', 'the4th', 'theKingshead', 'theater', 'theatre', 'themP', 'theme', 'themed', 'thenwill', 'theory', 'theplace', 'thepub', 'there', 'theredo', 'theregoodnight', 'therere', 'therexx', 'thesedays', 'thesis', 'thesmszonecom', 'theyll', 'theyre', 'thia', 'thin', 'thing', 'thinghow', 'think', 'thinkThis', 'thinked', 'thinkin', 'thinking', 'thinl', 'thirunelvali', 'thisdon', 'thk', 'thkin', 'thm', 'thnk', 'tho', 'thoso', 'thot', 'thou', 'though', 'thought', 'thoughtsI', 'thousand', 'thread', 'threat', 'three', 'threw', 'thriller', 'throat', 'throw', 'throwin', 'throwing', 'thrown', 'thru', 'thruRespect', 'tht', 'thts', 'thuglyfe', 'thurs', 'thursday', 'thus', 'thx', 'ti', 'tick', 'ticket', 'tiempo', 'tight', 'tightly', 'tigress', 'tihs', 'tiime', 'til', 'till', 'time', 'timeYour', 'timedhoni', 'timehope', 'timeslil', 'timeyou', 'timi', 'timin', 'timing', 'tiny', 'tip', 'tired', 'tiring', 'tirunelvai', 'tirunelvali', 'tirupur', 'titleso', 'tiwary', 'tix', 'tiz', 'tke', 'tkts', 'tlk', 'tm', 'tming', 'tmr', 'tmrw', 'tmw', 'toClaim', 'toDo', 'toa', 'toaday', 'tobacco', 'today', 'todayFrom', 'todayGood', 'todaybut', 'todaydo', 'todayhe', 'tog', 'together', 'tohar', 'toilet', 'tok', 'token', 'toking', 'tol', 'told', 'toldshe', 'tolerance', 'toleratbcs', 'tom', 'tomarrow', 'tomeandsaidTHIS', 'tomo', 'tomoCant', 'tomorro', 'tomorrow', 'tomorrowcall', 'tomorrowtoday', 'ton', 'tone', 'tones2youcouk', 'tonght', 'tongued', 'tonight', 'tonite', 'tonitebusy', 'tonitethings', 'tonsolitusaswell', 'tooLets', 'tooPray', 'took', 'tookplace', 'tool', 'tooo', 'toopray', 'toot', 'toothpaste', 'tootsie', 'top', 'topic', 'topicsorry', 'topped', 'toppoly', 'tor', 'torch', 'torrent', 'tortilla', 'torture', 'tosend', 'toshiba', 'toss', 'tot', 'total', 'totally', 'tote', 'touch', 'touched', 'tough', 'toughest', 'tour', 'towards', 'town', 'toyota', 'tp', 'track', 'trade', 'traffic', 'train', 'trained', 'training', 'trainners', 'tram', 'tranquility', 'transaction', 'transcribing', 'transfer', 'transferacc', 'transfered', 'transferred', 'transfr', 'transfred', 'transport', 'trash', 'trauma', 'travel', 'traveling', 'travelled', 'travelling', 'treacle', 'treadmill', 'treasure', 'treat', 'treated', 'treatin', 'treble', 'tree', 'trek', 'trend', 'trial', 'tried', 'trip', 'trishul', 'triumphed', 'tron', 'trouble', 'troubleshooting', 'trouser', 'truck', 'true', 'truekDo', 'truffle', 'truly', 'trust', 'trusting', 'truth', 'try', 'tryin', 'trying', 'tshirt', 'tsunami', 'tt', 'ttyl', 'tue', 'tues', 'tuesday', 'tui', 'tuition', 'tul', 'tune', 'turkey', 'turn', 'turned', 'turning', 'tuth', 'tv', 'tvhe', 'tvlol', 'twat', 'twelve', 'twenty', 'twice', 'twin', 'two', 'txt', 'txtX', 'txtin', 'txting', 'txtjourney', 'txts', 'tyler', 'type', 'typelyk', 'typical', 'u', 'uOthrwise', 'uSo', 'ubandu', 'ubi', 'ugos', 'uh', 'uif', 'uk', 'ull', 'ultimatum', 'um', 'umma', 'un', 'unable', 'unbelievable', 'unclaimed', 'uncle', 'uncomfortable', 'unconditionally', 'unconscious', 'unconsciously', 'unconvinced', 'uncountable', 'uncut', 'underdtand', 'understand', 'understanding', 'understood', 'underwear', 'undrstnd', 'undrstndng', 'unemployed', 'uneventful', 'unfolds', 'unfortunately', 'unfortuntly', 'unhappiness', 'unhappy', 'uni', 'uniform', 'unintentional', 'unintentionally', 'unique', 'uniqueI', 'unit', 'univ', 'university', 'unknown', 'unless', 'unlimited', 'unmits', 'unnecessarily', 'unrecognized', 'unredeemed', 'unsold', 'unsoldmike', 'unsoldnow', 'unspoken', 'unsubscribe', 'unsubscribed', 'unusual', 'upcharge', 'update', 'upgrade', 'upgrading', 'uphad', 'upload', 'uploaded', 'uploads', 'upon', 'upping', 'upset', 'upseti', 'upsetits', 'upstairs', 'upto', 'ur', 'ure', 'urgent', 'urgentbut', 'urgentlyits', 'urgnt', 'urination', 'url', 'urmomi', 'urself', 'us', 'usGET', 'usLET', 'usb', 'usc', 'uscedu', 'use', 'used', 'useful', 'useless', 'user', 'usf', 'using', 'usno', 'usps', 'usual', 'usualiam', 'usually', 'uterus', 'utter', 'uttered', 'uup', 'uv', 'uve', 'uwana', 'uwant', 'uworld', 'uxxxx', 'v', 'vaazhthukkal', 'vague', 'vaguely', 'vai', 'vale', 'valentine', 'valid', 'valuable', 'value', 'valueMorning', 'valued', 'valuing', 'varaya', 'vargu', 'various', 'varma', 'vary', 'vasai', 'vava', 'vday', 'vega', 'vegetable', 'veggie', 'vehicle', 'velachery', 'venaam', 'venugopal', 'verified', 'verify', 'verifying', 'version', 'versus', 'vewy', 'via', 'vibrant', 'vibrate', 'vibrator', 'vic', 'victor', 'victoria', 'vid', 'video', 'videochat', 'videopic', 'videosound', 'videosounds2', 'vidnot', 'view', 'vijay', 'vijaykanth', 'vikky', 'vikkyim', 'vilikkamt', 'vill', 'village', 'vinobanagar', 'violated', 'violence', 'virgil', 'virgin', 'virtual', 'visa', 'visionsmscom', 'visit', 'visiting', 'visitneed', 'visitor', 'vital', 'vitamin', 'vivek', 'viveki', 'vl', 'vldo', 'vodafone', 'vodka', 'voice', 'voicemail', 'volcano', 'vomit', 'vomitin', 'vomiting', 'vote', 'voted', 'voucher', 'vouchersText', 'vpist', 'vry', 'vth', 'vtired', 'w', 'w1t1jy', 'w8in', 'wa', 'wad', 'wadebridgeI', 'wahala', 'wahay', 'waheed', 'waheeda', 'waht', 'wait', 'waited', 'waitin', 'waiting', 'wake', 'waking', 'waliking', 'walk', 'walkabout', 'walked', 'walkin', 'walking', 'wall', 'wallet', 'wallpaper', 'wallpaperall', 'walmart', 'walsall', 'wamma', 'wan', 'wana', 'wanna', 'want', 'want2come', 'wanted', 'wanting', 'wap', 'warm', 'warming', 'warned', 'warner', 'warning', 'warranty', 'warwick', 'washob', 'wasnt', 'waste', 'wasted', 'wasting', 'wat', 'watch', 'watched', 'watchin', 'watching', 'watchng', 'water', 'watever', 'watevr', 'watll', 'wats', 'watt', 'wave', 'way', 'waythis', 'wc', 'wc1n3xx', 'weak', 'weakness', 'weapon', 'wear', 'wearing', 'weasel', 'weaseling', 'weather', 'web', 'web2mobile', 'webadres', 'website', 'websitenow', 'wed', 'weddin', 'wedding', 'wednesday', 'wee', 'weed', 'weeddeficient', 'week', 'weekday', 'weekend', 'weekly', 'weekstop', 'weigh', 'weighed', 'weight', 'weightHaha', 'weird', 'weirdest', 'weirdo', 'weirdy', 'welcome', 'well', 'welli', 'welltake', 'wellyou', 'welp', 'wen', 'wenever', 'went', 'wer', 'wereare', 'werent', 'wesley', 'west', 'western', 'westonzoyland', 'westshore', 'wet', 'wetherspoons', 'weve', 'whatever', 'whats', 'wheat', 'wheel', 'wheellock', 'whenever', 'whens', 'whereare', 'wherebtw', 'wheres', 'wherever', 'whether', 'whileamp', 'whillTake', 'whisper', 'white', 'whn', 'who', 'whole', 'whose', 'whr', 'wi', 'wicked', 'wicket', 'wid', 'widelivecomindex', 'wif', 'wife', 'wifedont', 'wifi', 'wihtuot', 'wikipediacom', 'wil', 'wildest', 'wildlife', 'willing', 'willpower', 'win', 'win150ppmx3age16', 'wind', 'window', 'windy', 'wine', 'wined', 'wining', 'winner', 'winning', 'winterstone', 'wipro', 'wiproyou', 'wisdom', 'wise', 'wish', 'wisheds', 'wishin', 'wishing', 'wishlist', 'wiskey', 'wit', 'withdraw', 'wither', 'within', 'without', 'witin', 'witot', 'witout', 'wiv', 'wizzle', 'wk', 'wkTXT', 'wkend', 'wkg', 'wkly', 'wknd', 'wks', 'wlcome', 'wld', 'wmlid1b6a5ecef91ff937819firsttrue180430JUL05', 'wmlid820554ad0a1705572711firsttrue', 'wnt', 'wo', 'woah', 'wocay', 'woke', 'woken', 'woman', 'womdarfull', 'wondar', 'wondarfull', 'wonder', 'wonderful', 'wondering', 'wont', 'woot', 'woould', 'woozles', 'worc', 'word', 'wordCOLLECT', 'wordSTART', 'wordnot', 'work', 'workAnd', 'workLove', 'workage', 'workin', 'working', 'workout', 'world', 'worldgnun', 'worldmay', 'worldvery', 'worm', 'worried', 'worry', 'worrying', 'worryuse', 'worse', 'worst', 'worth', 'worthless', 'wot', 'woul', 'would', 'woulda', 'wouldnt', 'wound', 'wow', 'wquestion', 'wrecked', 'wrench', 'wrenching', 'write', 'writhing', 'wrk', 'wrking', 'wrks', 'wrnog', 'wrong', 'wrongly', 'wrote', 'wt', 'wtc', 'wtf', 'wth', 'wthout', 'wud', 'wudnt', 'wuld', 'wuldnt', 'wun', 'www07781482378com', 'www4tcbiz', 'www80488biz', 'wwwApplausestorecom', 'wwwB4Utelecom', 'wwwIdewcom', 'wwwLdewcom', 'wwwLdewcom1win150ppmx3age16', 'wwwLdewcom1win150ppmx3age16subscription', 'wwwLdewcomsubs161win150ppmx3', 'wwwSMSacubootydelious', 'wwwSMSacugoldviking', 'wwwSMSacuhmmross', 'wwwSMSacunat27081980', 'wwwSMSacunatalie2k9', 'wwwareyouuniquecouk', 'wwwbridalpetticoatdreamscouk', 'wwwcashbincouk', 'wwwclubmobycom', 'wwwclubzedcouk', 'wwwcnupdatescomnewsletter', 'wwwcomuknet', 'wwwdbuknet', 'wwwflirtpartyus', 'wwwfullonsmscom', 'wwwgambtv', 'wwwgetzedcouk', 'wwwldewcom', 'wwwldewcom1win150ppmx3age16', 'wwwmovietriviatv', 'wwwmusictrivianet', 'wwworangecoukow', 'wwwphb1com', 'wwwregalportfoliocouk', 'wwwringtonekingcouk', 'wwwringtonescouk', 'wwwrtfsphostingcom', 'wwwsantacallingcom', 'wwwshortbreaksorguk', 'wwwsmsconet', 'wwwtcbiz', 'wwwtelediscountcouk', 'wwwtextcompcom', 'wwwtextpodnet', 'wwwtklscom', 'wwwtxt2shopcom', 'wwwtxt43com', 'wwwtxt82228com', 'wwwtxttowincouk', 'wwwwin82050couk', 'wylie', 'x', 'xafter', 'xam', 'xavier', 'xin', 'xins', 'xmas', 'xnet', 'xt', 'xuhui', 'xx', 'xxSP', 'xxx', 'xxxmobilemovieclubcomnQJKGIGHJJGCBL', 'xxxx', 'xxxxxxx', 'xxxxxxxx', 'xxxxxxxxxxxxxX', 'xy', 'ya', 'yah', 'yahoo', 'yalrigu', 'yam', 'yan', 'yard', 'yay', 'yck', 'yday', 'yeah', 'year', 'yelling', 'yellow', 'yeovil', 'yep', 'yer', 'yes', 'yest', 'yesterday', 'yet', 'yettys', 'yetunde', 'yi', 'yifeng', 'yijue', 'yijuehotmailcom', 'ym', 'yo', 'yoHere', 'yoga', 'yogasana', 'yor', 'yorge', 'youPhone', 'youTo', 'youany', 'youcarlos', 'youd', 'youdearwith', 'youdoing', 'youhow', 'youkwhere', 'yould', 'youll', 'youmoney', 'youmy', 'young', 'younger', 'youre', 'yourinclusive', 'youso', 'youthats', 'youuuuu', 'youve', 'youwanna', 'youwhen', 'yoville', 'yowifes', 'yr', 'ystrdayice', 'yummy', 'yun', 'yuo', 'yuou', 'zac', 'zealand', 'zed', 'zero', 'zhong', 'zoom', 'zyada', 'Ü', 'Üll', 'é', 'ü', 'üll', '〨ud']\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_count "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6xWiRVuZ5t6U",
        "outputId": "3b1153f0-6288-416f-cd8a-2e918bdac1c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<5572x11045 sparse matrix of type '<class 'numpy.int64'>'\n",
              "\twith 56326 stored elements in Compressed Sparse Row format>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Lets use the small data set\n"
      ],
      "metadata": {
        "id": "Kwl8eyaZ8D90"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_sample = df[0:20]\n",
        "data_sample"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 964
        },
        "id": "A7K-HqkH8OhV",
        "outputId": "a7f781cd-5ddd-4b13-f001-781322cc6801"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-a837e50c-b373-462b-b7c0-4148fcd9ea1d\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>clean_data</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "      <td>[go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "      <td>[free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[u, dun, say, early, hor, u, c, already, say]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "      <td>[nah, dont, think, go, usf, life, around, though]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>spam</td>\n",
              "      <td>FreeMsg Hey there darling it's been 3 week's now and no word back! I'd like some fun you up for ...</td>\n",
              "      <td>[freemsg, hey, darling, 3, week, word, back, id, like, fun, still, tb, ok, xxx, std, chgs, send,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>ham</td>\n",
              "      <td>Even my brother is not like to speak with me. They treat me like aids patent.</td>\n",
              "      <td>[even, brother, like, speak, treat, like, aid, patent]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>ham</td>\n",
              "      <td>As per your request 'Melle Melle (Oru Minnaminunginte Nurungu Vettam)' has been set as your call...</td>\n",
              "      <td>[per, request, melle, melle, oru, minnaminunginte, nurungu, vettam, set, callertune, caller, pre...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>spam</td>\n",
              "      <td>WINNER!! As a valued network customer you have been selected to receivea £900 prize reward! To c...</td>\n",
              "      <td>[winner, valued, network, customer, selected, receivea, 900, prize, reward, claim, call, 0906170...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>spam</td>\n",
              "      <td>Had your mobile 11 months or more? U R entitled to Update to the latest colour mobiles with came...</td>\n",
              "      <td>[mobile, 11, month, u, r, entitled, update, latest, colour, mobile, camera, free, call, mobile, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>ham</td>\n",
              "      <td>I'm gonna be home soon and i don't want to talk about this stuff anymore tonight, k? I've cried ...</td>\n",
              "      <td>[im, gonna, home, soon, dont, want, talk, stuff, anymore, tonight, k, ive, cried, enough, today]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>spam</td>\n",
              "      <td>SIX chances to win CASH! From 100 to 20,000 pounds txt&gt; CSH11 and send to 87575. Cost 150p/day, ...</td>\n",
              "      <td>[six, chance, win, cash, 100, 20000, pound, txt, csh11, send, 87575, cost, 150pday, 6days, 16, t...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>spam</td>\n",
              "      <td>URGENT! You have won a 1 week FREE membership in our £100,000 Prize Jackpot! Txt the word: CLAIM...</td>\n",
              "      <td>[urgent, 1, week, free, membership, 100000, prize, jackpot, txt, word, claim, 81010, tc, wwwdbuk...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>ham</td>\n",
              "      <td>I've been searching for the right words to thank you for this breather. I promise i wont take yo...</td>\n",
              "      <td>[ive, searching, right, word, thank, breather, promise, wont, take, help, granted, fulfil, promi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>ham</td>\n",
              "      <td>I HAVE A DATE ON SUNDAY WITH WILL!!</td>\n",
              "      <td>[date, sunday]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>spam</td>\n",
              "      <td>XXXMobileMovieClub: To use your credit, click the WAP link in the next txt message or click here...</td>\n",
              "      <td>[xxxmobilemovieclub, use, credit, click, wap, link, next, txt, message, click, httpwap, xxxmobil...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>ham</td>\n",
              "      <td>Oh k...i'm watching here:)</td>\n",
              "      <td>[oh, kim, watching]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>ham</td>\n",
              "      <td>Eh u remember how 2 spell his name... Yes i did. He v naughty make until i v wet.</td>\n",
              "      <td>[eh, u, remember, 2, spell, name, yes, v, naughty, make, v, wet]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>ham</td>\n",
              "      <td>Fine if thats the way u feel. Thats the way its gota b</td>\n",
              "      <td>[fine, way, u, feel, way, gota, b]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>spam</td>\n",
              "      <td>England v Macedonia - dont miss the goals/team news. Txt ur national team to 87077 eg ENGLAND to...</td>\n",
              "      <td>[england, v, macedonia, dont, miss, goalsteam, news, txt, ur, national, team, 87077, eg, england...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            ],
            "text/plain": [
              "   label  ...                                                                                           clean_data\n",
              "0    ham  ...  [go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]\n",
              "1    ham  ...                                                                       [ok, lar, joking, wif, u, oni]\n",
              "2   spam  ...  [free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...\n",
              "3    ham  ...                                                        [u, dun, say, early, hor, u, c, already, say]\n",
              "4    ham  ...                                                    [nah, dont, think, go, usf, life, around, though]\n",
              "5   spam  ...  [freemsg, hey, darling, 3, week, word, back, id, like, fun, still, tb, ok, xxx, std, chgs, send,...\n",
              "6    ham  ...                                               [even, brother, like, speak, treat, like, aid, patent]\n",
              "7    ham  ...  [per, request, melle, melle, oru, minnaminunginte, nurungu, vettam, set, callertune, caller, pre...\n",
              "8   spam  ...  [winner, valued, network, customer, selected, receivea, 900, prize, reward, claim, call, 0906170...\n",
              "9   spam  ...  [mobile, 11, month, u, r, entitled, update, latest, colour, mobile, camera, free, call, mobile, ...\n",
              "10   ham  ...     [im, gonna, home, soon, dont, want, talk, stuff, anymore, tonight, k, ive, cried, enough, today]\n",
              "11  spam  ...  [six, chance, win, cash, 100, 20000, pound, txt, csh11, send, 87575, cost, 150pday, 6days, 16, t...\n",
              "12  spam  ...  [urgent, 1, week, free, membership, 100000, prize, jackpot, txt, word, claim, 81010, tc, wwwdbuk...\n",
              "13   ham  ...  [ive, searching, right, word, thank, breather, promise, wont, take, help, granted, fulfil, promi...\n",
              "14   ham  ...                                                                                       [date, sunday]\n",
              "15  spam  ...  [xxxmobilemovieclub, use, credit, click, wap, link, next, txt, message, click, httpwap, xxxmobil...\n",
              "16   ham  ...                                                                                  [oh, kim, watching]\n",
              "17   ham  ...                                     [eh, u, remember, 2, spell, name, yes, v, naughty, make, v, wet]\n",
              "18   ham  ...                                                                   [fine, way, u, feel, way, gota, b]\n",
              "19  spam  ...  [england, v, macedonia, dont, miss, goalsteam, news, txt, ur, national, team, 87077, eg, england...\n",
              "\n",
              "[20 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_count_sample = count_vect.fit_transform(data_sample['message'])\n",
        "x_count_sample"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xGx23PXi8apE",
        "outputId": "e2c88b17-6e87-4152-b376-fcb30e3a71e2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<20x248 sparse matrix of type '<class 'numpy.int64'>'\n",
              "\twith 274 stored elements in Compressed Sparse Row format>"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_count_df =pd.DataFrame(x_count_sample.toarray())\n",
        "x_count_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "pPdGTj2t85IL",
        "outputId": "a80f8633-6378-4a7c-f769-6edcf13559a2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "[5 rows x 248 columns]"
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          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_count_df.columns = count_vect.get_feature_names()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RhUkzc998-Dk",
        "outputId": "c82ef109-0f4d-4606-8094-aa1e44d34a9d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_count_df.head()"
      ],
      "metadata": {
        "colab": {
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          "height": 299
        },
        "id": "29P4DKc59mOY",
        "outputId": "759b1f43-9409-4ebb-9490-b3dfb5637168"
      },
      "execution_count": null,
      "outputs": [
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b4340b8f-eafd-47b6-8edb-ab5a4c874dcc')\"\n",
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            ],
            "text/plain": [
              "   08002986030  ...  xxxmobilemovieclubcomnQJKGIGHJJGCBL\n",
              "0            0  ...                                    0\n",
              "1            0  ...                                    0\n",
              "2            0  ...                                    0\n",
              "3            0  ...                                    0\n",
              "4            0  ...                                    0\n",
              "\n",
              "[5 rows x 248 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## N- Gram vectorizer"
      ],
      "metadata": {
        "id": "vk3FnYKW93Qc"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Have to change the Pre_processing function to have cleaned text in form of sentence"
      ],
      "metadata": {
        "id": "G2WeKOgClS2b"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def pre_process_data_n_gram(text_data):\n",
        "  no_punct = \"\".join([char for char in text_data if char not in string.punctuation])\n",
        "  tokenzie_text = re.split('\\W+', no_punct)\n",
        "  # Note change is made in below line to retain the sentence.\n",
        "  stop_words_removal = \" \".join([word for word in tokenzie_text if word not in stop_words])\n",
        "  return stop_words_removal\n"
      ],
      "metadata": {
        "id": "KOJDXlrclhRw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['clean_sentence'] = df['message'].apply( lambda x: pre_process_data_n_gram(x.lower()))\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "id": "3QTEMoZ0m_kp",
        "outputId": "b2266dcd-7e47-4eeb-96d1-d9f6715dc7db"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>clean_data</th>\n",
              "      <th>clean_sentence</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "      <td>[go, jurong, point, crazy, available, bugis, n, great, world, la, e, buffet, cine, got, amore, wat]</td>\n",
              "      <td>go jurong point crazy available bugis n great world la e buffet cine got amore wat</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>[ok, lar, joking, wif, u, oni]</td>\n",
              "      <td>ok lar joking wif u oni</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "      <td>[free, entry, 2, wkly, comp, win, fa, cup, final, tkts, 21st, may, 2005, text, fa, 87121, receiv...</td>\n",
              "      <td>free entry 2 wkly comp win fa cup final tkts 21st may 2005 text fa 87121 receive entry questions...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>[u, dun, say, early, hor, u, c, already, say]</td>\n",
              "      <td>u dun say early hor u c already say</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "      <td>[nah, dont, think, go, usf, life, around, though]</td>\n",
              "      <td>nah dont think goes usf lives around though</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  "
            ],
            "text/plain": [
              "  label  ...                                                                                       clean_sentence\n",
              "0   ham  ...                   go jurong point crazy available bugis n great world la e buffet cine got amore wat\n",
              "1   ham  ...                                                                              ok lar joking wif u oni\n",
              "2  spam  ...  free entry 2 wkly comp win fa cup final tkts 21st may 2005 text fa 87121 receive entry questions...\n",
              "3   ham  ...                                                                  u dun say early hor u c already say\n",
              "4   ham  ...                                                          nah dont think goes usf lives around though\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We still require count vecotrizer"
      ],
      "metadata": {
        "id": "jIQAlEadmTeZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "\n",
        "count_vect_n_gram = CountVectorizer(ngram_range=(2,2))"
      ],
      "metadata": {
        "id": "X1gURN6rmiIh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x_count = count_vect_n_gram.fit_transform(df['clean_sentence'])\n",
        "x_count.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IDKwKHP8nZhQ",
        "outputId": "738973f2-63a7-470d-a526-6634d0f3f108"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5572, 31990)"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_count"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NzruaLHEnrW_",
        "outputId": "bad4f09f-cf66-4637-8838-cc008133e272"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<5572x31990 sparse matrix of type '<class 'numpy.int64'>'\n",
              "\twith 43788 stored elements in Compressed Sparse Row format>"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "count_vect_n_gram.get_feature_names"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6xXVZtHent1Q",
        "outputId": "74d156ef-2f7c-4aa4-d58a-45c18ad9d862"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method CountVectorizer.get_feature_names of CountVectorizer(ngram_range=(2, 2))>"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Lets view it on sample data"
      ],
      "metadata": {
        "id": "0f4rD7Dkn45H"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_sample = df[:20]\n",
        "data_sample.count"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gj1dTE-Yn-QO",
        "outputId": "e04a9139-1692-43de-8a93-a299744f4204"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method DataFrame.count of    label  ...                                                                                       clean_sentence\n",
              "0    ham  ...                   go jurong point crazy available bugis n great world la e buffet cine got amore wat\n",
              "1    ham  ...                                                                              ok lar joking wif u oni\n",
              "2   spam  ...  free entry 2 wkly comp win fa cup final tkts 21st may 2005 text fa 87121 receive entry questions...\n",
              "3    ham  ...                                                                  u dun say early hor u c already say\n",
              "4    ham  ...                                                          nah dont think goes usf lives around though\n",
              "5   spam  ...              freemsg hey darling 3 weeks word back id like fun still tb ok xxx std chgs send 150 rcv\n",
              "6    ham  ...                                                       even brother like speak treat like aids patent\n",
              "7    ham  ...  per request melle melle oru minnaminunginte nurungu vettam set callertune callers press 9 copy f...\n",
              "8   spam  ...  winner valued network customer selected receivea 900 prize reward claim call 09061701461 claim c...\n",
              "9   spam  ...  mobile 11 months u r entitled update latest colour mobiles camera free call mobile update co fre...\n",
              "10   ham  ...                     im gonna home soon dont want talk stuff anymore tonight k ive cried enough today\n",
              "11  spam  ...  six chances win cash 100 20000 pounds txt csh11 send 87575 cost 150pday 6days 16 tsandcs apply r...\n",
              "12  spam  ...  urgent 1 week free membership 100000 prize jackpot txt word claim 81010 tc wwwdbuknet lccltd pob...\n",
              "13   ham  ...  ive searching right words thank breather promise wont take help granted fulfil promise wonderful...\n",
              "14   ham  ...                                                                                          date sunday\n",
              "15  spam  ...  xxxmobilemovieclub use credit click wap link next txt message click httpwap xxxmobilemovieclubco...\n",
              "16   ham  ...                                                                                      oh kim watching\n",
              "17   ham  ...                                                  eh u remember 2 spell name yes v naughty make v wet\n",
              "18   ham  ...                                                                           fine way u feel way gota b\n",
              "19  spam  ...  england v macedonia dont miss goalsteam news txt ur national team 87077 eg england 87077 trywale...\n",
              "\n",
              "[20 rows x 4 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_count_sample = count_vect_n_gram.fit_transform(data_sample['clean_sentence'])\n",
        "df_x_count_sample = pd.DataFrame(x_count_sample.toarray())\n",
        "df_x_count_sample.columns = count_vect_n_gram.get_feature_names()\n",
        "df_x_count_sample"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 821
        },
        "id": "8JJF6AC_oM6_",
        "outputId": "acd9d33e-568a-40cc-8899-fc2b592969d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20 rows × 225 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-153af68c-2fe0-4bbd-bb5c-3ed87e2e01d1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "    09061701461 claim  100 20000  ...  xxxmobilemovieclub use  yes naughty\n",
              "0                   0          0  ...                       0            0\n",
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              "17                  0          0  ...                       0            1\n",
              "18                  0          0  ...                       0            0\n",
              "19                  0          0  ...                       0            0\n",
              "\n",
              "[20 rows x 225 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## TF -IDF vectorizer "
      ],
      "metadata": {
        "id": "r1c2dtpqe12G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "\n",
        "\n",
        "# Have to change the preprocessing function to have the data in terms of words.\n",
        "def pre_process_data_tfidf(text_data):\n",
        "  no_punct = \"\".join([char for char in text_data if char not in string.punctuation])\n",
        "  tokenzie_text = re.split('\\W+', no_punct)\n",
        "  # Note change is made in below line to retain the sentence.\n",
        "  stop_words_n_lemma = [wn.lemmatize(word) for word in tokenzie_text if word not in stop_words]\n",
        "  return stop_words_n_lemma\n",
        "\n"
      ],
      "metadata": {
        "id": "Es4c9nmWpTeV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tf_idf_vec = TfidfVectorizer(analyzer = pre_process_data_tfidf )\n",
        "\n",
        "x_count=tf_idf_vec.fit_transform(df['message'])\n",
        "\n",
        "print(x_count.shape)\n",
        "print(tf_idf_vec.get_feature_names())\n",
        "\n",
        "data_sample = df[:20]\n",
        "data_sample.count\n",
        "\n",
        "x_count_sample = tf_idf_vec.fit_transform(data_sample['clean_sentence'])\n",
        "df_x_count_sample = pd.DataFrame(x_count_sample.toarray())\n",
        "df_x_count_sample.columns = tf_idf_vec.get_feature_names()\n",
        "df_x_count_sample\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 874
        },
        "id": "2CzB8z4UfWsu",
        "outputId": "af2519e8-ff72-490b-c88a-51a60f5e5f9a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.\n",
            "  warnings.warn(msg, category=FutureWarning)\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.\n",
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              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.174417</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.198423</td>\n",
              "      <td>0.198423</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.198423</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.174417</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.198423</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.133378</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.174417</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.198423</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.304187</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.408943</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.367563</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.367563</td>\n",
              "      <td>0.367563</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.367563</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.237559</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.237559</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.237559</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.208818</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.188426</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.237559</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.331667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.331667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.331667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.223607</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.223607</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.231645</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.231645</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.231645</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.231645</td>\n",
              "      <td>0.231645</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.231645</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>0.1971</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1971</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.132489</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.263507</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.263507</td>\n",
              "      <td>0.263507</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.263507</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.226209</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.226209</td>\n",
              "      <td>0.198841</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.226209</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.226209</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.226209</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.226209</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.198841</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.226209</td>\n",
              "      <td>0.152056</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.198841</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.257957</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.257957</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.257957</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.257957</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.173397</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.257957</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.226749</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.204605</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.257957</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.239719</td>\n",
              "      <td>0.239719</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.239719</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.239719</td>\n",
              "      <td>0.239719</td>\n",
              "      <td>0.190139</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.183274</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.272652</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.272652</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.272652</td>\n",
              "      <td>0.272652</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.57735</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.250482</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.191546</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.500963</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.284957</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.284957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.343973</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.231215</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.687946</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.184795</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.210229</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.420459</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.210229</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.141314</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.210229</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.184795</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20 rows × 220 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5d4aadb1-3257-46ad-abb0-835fc4a60362')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
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              "      \n",
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              "    .colab-df-container {\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5d4aadb1-3257-46ad-abb0-835fc4a60362 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5d4aadb1-3257-46ad-abb0-835fc4a60362');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "    08002986030  ...       yes\n",
              "0        0.0000  ...  0.000000\n",
              "1        0.0000  ...  0.000000\n",
              "2        0.0000  ...  0.000000\n",
              "3        0.0000  ...  0.000000\n",
              "4        0.0000  ...  0.000000\n",
              "5        0.0000  ...  0.000000\n",
              "6        0.0000  ...  0.000000\n",
              "7        0.0000  ...  0.000000\n",
              "8        0.0000  ...  0.000000\n",
              "9        0.1971  ...  0.000000\n",
              "10       0.0000  ...  0.000000\n",
              "11       0.0000  ...  0.000000\n",
              "12       0.0000  ...  0.000000\n",
              "13       0.0000  ...  0.000000\n",
              "14       0.0000  ...  0.000000\n",
              "15       0.0000  ...  0.000000\n",
              "16       0.0000  ...  0.000000\n",
              "17       0.0000  ...  0.284957\n",
              "18       0.0000  ...  0.000000\n",
              "19       0.0000  ...  0.000000\n",
              "\n",
              "[20 rows x 220 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Feature Engineering : Feature Creation"
      ],
      "metadata": {
        "id": "_E-T8J3Ih_hK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Read the text "
      ],
      "metadata": {
        "id": "dnSRFCWGizZC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd \n",
        "headers = ['label','message']\n",
        "df = pd.read_csv('SMSSpamCollection', sep='\\t', names = headers)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "re9L5f6ni17x",
        "outputId": "514314f8-e8cd-424b-f3cb-0ac481b22ca1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "\n",
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              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8682e087-9ad3-4a65-ba9c-8e746f0e725a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8682e087-9ad3-4a65-ba9c-8e746f0e725a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8682e087-9ad3-4a65-ba9c-8e746f0e725a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label                                                                                              message\n",
              "0   ham  Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...\n",
              "1   ham                                                                        Ok lar... Joking wif u oni...\n",
              "2  spam  Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...\n",
              "3   ham                                                    U dun say so early hor... U c already then say...\n",
              "4   ham                                        Nah I don't think he goes to usf, he lives around here though"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create a Feature to count the number of character isn meassage exclude the white spaces."
      ],
      "metadata": {
        "id": "GmtoR3R6jvVZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['message_len']= df['message'].apply(lambda x:len(x)-x.count(\" \"))\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "N59CobPWj5_4",
        "outputId": "afd3bbaa-bdf5-4cd1-d34e-c3727434404e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-a78fe1b6-478a-4814-94ac-da0818a66956\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
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              "        vertical-align: top;\n",
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              "\n",
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              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>message_len</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "      <td>92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "      <td>128</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "      <td>49</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a78fe1b6-478a-4814-94ac-da0818a66956')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a78fe1b6-478a-4814-94ac-da0818a66956 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a78fe1b6-478a-4814-94ac-da0818a66956');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ... message_len\n",
              "0   ham  ...          92\n",
              "1   ham  ...          24\n",
              "2  spam  ...         128\n",
              "3   ham  ...          39\n",
              "4   ham  ...          49\n",
              "\n",
              "[5 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create Feature whith % of text having punctuation\n"
      ],
      "metadata": {
        "id": "JhDgafkAktqX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import string\n",
        "def count_punct(text):\n",
        "  count= sum([1 for char in text if char in string.punctuation])\n",
        "  total_len = len(text)-text.count(\" \")\n",
        "  return (count/total_len)*100\n",
        "df['percent_punctuation'] = df['message'].apply(lambda x : count_punct(x))\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 250
        },
        "id": "-iG6sXAUk3ku",
        "outputId": "1a6015b9-dc1d-48ea-d791-86f19d4819be"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>label</th>\n",
              "      <th>message</th>\n",
              "      <th>message_len</th>\n",
              "      <th>percent_punctuation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ham</td>\n",
              "      <td>Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there g...</td>\n",
              "      <td>92</td>\n",
              "      <td>9.782609</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ham</td>\n",
              "      <td>Ok lar... Joking wif u oni...</td>\n",
              "      <td>24</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>spam</td>\n",
              "      <td>Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive ...</td>\n",
              "      <td>128</td>\n",
              "      <td>4.687500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ham</td>\n",
              "      <td>U dun say so early hor... U c already then say...</td>\n",
              "      <td>39</td>\n",
              "      <td>15.384615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ham</td>\n",
              "      <td>Nah I don't think he goes to usf, he lives around here though</td>\n",
              "      <td>49</td>\n",
              "      <td>4.081633</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5ec8f667-f3be-4d27-85ae-3cc6337589a3')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5ec8f667-f3be-4d27-85ae-3cc6337589a3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5ec8f667-f3be-4d27-85ae-3cc6337589a3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  label  ... percent_punctuation\n",
              "0   ham  ...            9.782609\n",
              "1   ham  ...           25.000000\n",
              "2  spam  ...            4.687500\n",
              "3   ham  ...           15.384615\n",
              "4   ham  ...            4.081633\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Evaluate Created Features"
      ],
      "metadata": {
        "id": "PkXSEg9gmE0L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from matplotlib import pyplot\n",
        "import numpy as np\n",
        "%matplotlib inline"
      ],
      "metadata": {
        "id": "oX1mEApgmbXS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Create the bins\n",
        "bins = np.linspace(0,200,40)\n",
        "pyplot.hist(df[df['label'] == 'spam']['message_len'], bins, alpha=0.5, density=True, label='spam')\n",
        "pyplot.hist(df[df['label'] == 'ham']['message_len'], bins, alpha=0.5, density=True, label='ham')\n",
        "pyplot.legend(loc=\"upper left\")\n",
        "pyplot.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "TvLXboRXmiIK",
        "outputId": "4137d9f0-0e44-4015-9375-1dda5d1f39aa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create the bins\n",
        "bins = np.linspace(0,50,40)\n",
        "pyplot.hist(df[df['label'] == 'spam']['percent_punctuation'], bins, alpha=0.5, density=True, label='spam')\n",
        "pyplot.hist(df[df['label'] == 'ham']['percent_punctuation'], bins, alpha=0.5, density=True, label='ham')\n",
        "pyplot.legend(loc=\"upper right\")\n",
        "pyplot.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "EzpINPYnoEZA",
        "outputId": "d76d992d-d350-43d7-c951-a1af69e12c21"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# check if transformation is require on the features"
      ],
      "metadata": {
        "id": "mJqkLPS5pzcp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "bins = np.linspace(0,200,40)\n",
        "pyplot.hist(df['message_len'],bins)\n",
        "pyplot.title('Message length distribution')\n",
        "pyplot.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "oXfd-IPrqkVv",
        "outputId": "418503f7-75fd-46ad-9a3e-904bc85ce613"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bins = np.linspace(0,50,40)\n",
        "pyplot.hist(df['percent_punctuation'],bins)\n",
        "pyplot.title('Punctuation Percent distribution')\n",
        "pyplot.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "MXFnAcdKsCNf",
        "outputId": "56e29bb5-d96a-425d-e362-938307ead226"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Box cox tranformation on Punction percent distribution"
      ],
      "metadata": {
        "id": "IPp154Q2sNK-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "bins = 40\n",
        "for i in range(1,6):\n",
        "  pyplot.hist((df['percent_punctuation'])**(1/i),bins)\n",
        "  pyplot.title(f\"Tansfromation for 1/{i}\")\n",
        "  pyplot.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "YTJ9hKfq_SOt",
        "outputId": "9a622a18-135c-4748-cd87-49b564ae23a4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "Q8Dsuc1u_wMk"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}