hw4_pandas_in_act.ipynb

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      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ]
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        "# Как импортировать файл nfl.csv?\n",
        "# Как эффективнее всего преобразовать значения из столбца Birthday в метки даты/времени?\n",
        "\n",
        "nfl = pd.read_csv(\"nfl.csv\", parse_dates = [\"Birthday\"])\n",
        "nfl.head()"
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              "             Name                  Team Position   Birthday   Salary\n",
              "0    Tremon Smith   Philadelphia Eagles       RB 1996-07-20   570000\n",
              "1  Shawn Williams    Cincinnati Bengals       SS 1991-05-13  3500000\n",
              "2     Adam Butler  New England Patriots       DT 1994-04-12   645000\n",
              "3     Derek Wolfe        Denver Broncos       DE 1990-02-24  8000000\n",
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      "cell_type": "code",
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        "# Какими двумя способами можно задать индекс объекта DataFrame для хра- нения имен игроков?\n",
        "#1\n",
        "nfl = pd.read_csv(\"nfl.csv\",index_col='Name', parse_dates = [\"Birthday\"])\n",
        "nfl.head()"
      ],
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              "                                Team Position   Birthday   Salary\n",
              "Name                                                             \n",
              "Tremon Smith     Philadelphia Eagles       RB 1996-07-20   570000\n",
              "Shawn Williams    Cincinnati Bengals       SS 1991-05-13  3500000\n",
              "Adam Butler     New England Patriots       DT 1994-04-12   645000\n",
              "Derek Wolfe           Denver Broncos       DE 1990-02-24  8000000\n",
              "Jake Ryan       Jacksonville Jaguars      OLB 1992-02-27  1000000"
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              "      <th>Tremon Smith</th>\n",
              "      <td>Philadelphia Eagles</td>\n",
              "      <td>RB</td>\n",
              "      <td>1996-07-20</td>\n",
              "      <td>570000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shawn Williams</th>\n",
              "      <td>Cincinnati Bengals</td>\n",
              "      <td>SS</td>\n",
              "      <td>1991-05-13</td>\n",
              "      <td>3500000</td>\n",
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              "    <tr>\n",
              "      <th>Adam Butler</th>\n",
              "      <td>New England Patriots</td>\n",
              "      <td>DT</td>\n",
              "      <td>1994-04-12</td>\n",
              "      <td>645000</td>\n",
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              "    <tr>\n",
              "      <th>Derek Wolfe</th>\n",
              "      <td>Denver Broncos</td>\n",
              "      <td>DE</td>\n",
              "      <td>1990-02-24</td>\n",
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      "source": [
        "#2\n",
        "nfl = nfl.reset_index().set_index('Name')\n",
        "nfl.head()"
      ],
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      "execution_count": 32,
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              "                                Team Position   Birthday   Salary\n",
              "Name                                                             \n",
              "Tremon Smith     Philadelphia Eagles       RB 1996-07-20   570000\n",
              "Shawn Williams    Cincinnati Bengals       SS 1991-05-13  3500000\n",
              "Adam Butler     New England Patriots       DT 1994-04-12   645000\n",
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              "      <th>Derek Wolfe</th>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Как подсчитать коли?чество игроков по командам в этом наборе данных?\n",
        "nfl.Team.value_counts().head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nNS9x5MF4J0d",
        "outputId": "bd0f3c38-a28b-43f8-b7c6-8c9c931b0a54"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "New York Jets          58\n",
              "Kansas City Chiefs     56\n",
              "Washington Redskins    56\n",
              "New Orleans Saints     55\n",
              "San Francisco 49Ers    55\n",
              "Name: Team, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Какие пять игроков наиболее высокооплачиваемые?\n",
        "nfl.sort_values('Salary',ascending=False).head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "HNPt3ZdL5kJF",
        "outputId": "139d8795-a83c-4c51-cb48-9c659ee2319f"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                 Team Position   Birthday    Salary\n",
              "Name                                                               \n",
              "Kirk Cousins        Minnesota Vikings       QB 1988-08-19  27500000\n",
              "Jameis Winston   Tampa Bay Buccaneers       QB 1994-01-06  20922000\n",
              "Marcus Mariota       Tennessee Titans       QB 1993-10-30  20922000\n",
              "Derek Carr            Oakland Raiders       QB 1991-03-28  19900000\n",
              "Jimmy Garoppolo   San Francisco 49Ers       QB 1991-11-02  17200000"
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              "\n",
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            ]
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Как отсортировать этот набор  данных сначала по командам в алфавитном порядке,\n",
        "# а затем по зарплатам в порядке убывания?\n",
        "nfl.sort_values(['Team','Salary'],ascending=[True, False])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "_8D4snnf6GQ0",
        "outputId": "98112025-098e-40c4-a19d-9e886e24767a"
      },
      "execution_count": 35,
      "outputs": [
        {
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          "data": {
            "text/plain": [
              "                                   Team Position   Birthday    Salary\n",
              "Name                                                                 \n",
              "Chandler Jones        Arizona Cardinals      OLB 1990-02-27  16500000\n",
              "Patrick Peterson      Arizona Cardinals       CB 1990-07-11  11000000\n",
              "Larry Fitzgerald      Arizona Cardinals       WR 1983-08-31  11000000\n",
              "David Johnson         Arizona Cardinals       RB 1991-12-16   5700000\n",
              "Justin Pugh           Arizona Cardinals        G 1990-08-15   5000000\n",
              "...                                 ...      ...        ...       ...\n",
              "Ross Pierschbacher  Washington Redskins        C 1995-05-05    495000\n",
              "Kelvin Harmon       Washington Redskins       WR 1996-12-15    495000\n",
              "Wes Martin          Washington Redskins        G 1996-05-09    495000\n",
              "Jimmy Moreland      Washington Redskins       CB 1995-08-26    495000\n",
              "Jeremy Reaves       Washington Redskins       SS 1996-08-29    495000\n",
              "\n",
              "[1655 rows x 4 columns]"
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              "      <th>Chandler Jones</th>\n",
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              "      <td>1990-02-27</td>\n",
              "      <td>16500000</td>\n",
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              "    <tr>\n",
              "      <th>Patrick Peterson</th>\n",
              "      <td>Arizona Cardinals</td>\n",
              "      <td>CB</td>\n",
              "      <td>1990-07-11</td>\n",
              "      <td>11000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Larry Fitzgerald</th>\n",
              "      <td>Arizona Cardinals</td>\n",
              "      <td>WR</td>\n",
              "      <td>1983-08-31</td>\n",
              "      <td>11000000</td>\n",
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              "    <tr>\n",
              "      <th>David Johnson</th>\n",
              "      <td>Arizona Cardinals</td>\n",
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              "      <td>1991-12-16</td>\n",
              "      <td>5700000</td>\n",
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              "      <th>Justin Pugh</th>\n",
              "      <td>Arizona Cardinals</td>\n",
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              "      <th>Ross Pierschbacher</th>\n",
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              "      <td>C</td>\n",
              "      <td>1995-05-05</td>\n",
              "      <td>495000</td>\n",
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              "    <tr>\n",
              "      <th>Kelvin Harmon</th>\n",
              "      <td>Washington Redskins</td>\n",
              "      <td>WR</td>\n",
              "      <td>1996-12-15</td>\n",
              "      <td>495000</td>\n",
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              "    <tr>\n",
              "      <th>Wes Martin</th>\n",
              "      <td>Washington Redskins</td>\n",
              "      <td>G</td>\n",
              "      <td>1996-05-09</td>\n",
              "      <td>495000</td>\n",
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              "      <td>1995-08-26</td>\n",
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              "      <td>495000</td>\n",
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              "<p>1655 rows × 4 columns</p>\n",
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              "          const element = document.querySelector('#df-a6add2bc-acb5-4ff2-8528-c3b21ae7d840');\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",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Кто самый возрастной игрок в списке команды «Нью-Йорк Джетс» и когда он родился?\n",
        "nfl1 = nfl.reset_index().set_index(keys = 'Team')\n",
        "nfl1.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "ogbeYinc6uiB",
        "outputId": "040fc7d2-1395-4d2a-957f-ef5ed016c7b0"
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      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                Name Position   Birthday   Salary\n",
              "Team                                                             \n",
              "Philadelphia Eagles     Tremon Smith       RB 1996-07-20   570000\n",
              "Cincinnati Bengals    Shawn Williams       SS 1991-05-13  3500000\n",
              "New England Patriots     Adam Butler       DT 1994-04-12   645000\n",
              "Denver Broncos           Derek Wolfe       DE 1990-02-24  8000000\n",
              "Jacksonville Jaguars       Jake Ryan      OLB 1992-02-27  1000000"
            ],
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Philadelphia Eagles</th>\n",
              "      <td>Tremon Smith</td>\n",
              "      <td>RB</td>\n",
              "      <td>1996-07-20</td>\n",
              "      <td>570000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cincinnati Bengals</th>\n",
              "      <td>Shawn Williams</td>\n",
              "      <td>SS</td>\n",
              "      <td>1991-05-13</td>\n",
              "      <td>3500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>New England Patriots</th>\n",
              "      <td>Adam Butler</td>\n",
              "      <td>DT</td>\n",
              "      <td>1994-04-12</td>\n",
              "      <td>645000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Denver Broncos</th>\n",
              "      <td>Derek Wolfe</td>\n",
              "      <td>DE</td>\n",
              "      <td>1990-02-24</td>\n",
              "      <td>8000000</td>\n",
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              "    <tr>\n",
              "      <th>Jacksonville Jaguars</th>\n",
              "      <td>Jake Ryan</td>\n",
              "      <td>OLB</td>\n",
              "      <td>1992-02-27</td>\n",
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              "          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",
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    },
    {
      "cell_type": "code",
      "source": [
        "nfl1.loc[\"New York Jets\"].sort_values('Birthday').head(1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "llxGUHjO7rXF",
        "outputId": "39d034f5-70f1-431b-d1a2-5d1d20459d8c"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     Name Position   Birthday   Salary\n",
              "Team                                                  \n",
              "New York Jets  Ryan Kalil        C 1985-03-29  2400000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-72aae595-d2c9-4c45-9430-66d30e566e80\">\n",
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              "    <tr>\n",
              "      <th>New York Jets</th>\n",
              "      <td>Ryan Kalil</td>\n",
              "      <td>C</td>\n",
              "      <td>1985-03-29</td>\n",
              "      <td>2400000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-72aae595-d2c9-4c45-9430-66d30e566e80')\"\n",
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              "       width=\"24px\">\n",
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              "\n",
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              "          document.querySelector('#df-72aae595-d2c9-4c45-9430-66d30e566e80 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-72aae595-d2c9-4c45-9430-66d30e566e80');\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",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    }
  ]
}