copernicus_datasets.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from path import Path\n",
    "import os\n",
    "import pandas as pd\n",
    "import zipfile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# helper function to unzip\n",
    "def unzip_file(fpath):\n",
    "    fzip = os.listdir(fpath)[0]\n",
    "    with zipfile.ZipFile(f'{fpath}/{fzip}', \"r\") as zip_ref:\n",
    "        zip_ref.extractall(fpath)\n",
    "        \n",
    "    os.remove(f'{fpath}/{fzip}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# download root\n",
    "root = Path('./data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# making sub directories\n",
    "os.mkdir(root/'lending_club')\n",
    "os.mkdir(root/'mushroom')\n",
    "os.mkdir(root/'telco')\n",
    "os.mkdir(root/'ibm_attrition')\n",
    "os.mkdir(root/'wine_quality')\n",
    "os.mkdir(root/'pulsar')\n",
    "os.mkdir(root/'kepler')\n",
    "os.mkdir(root/'eeg')\n",
    "os.mkdir(root/'mobile_pricce')\n",
    "os.mkdir(root/'clinvar')\n",
    "os.mkdir(root/'lol')\n",
    "os.mkdir(root/'kepler_exoplanet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# grabbing sub directories\n",
    "sd_lending = (root/'lending_club')\n",
    "sd_mushroom = (root/'mushroom')\n",
    "sd_telco = (root/'telco')\n",
    "sd_ibm = (root/'ibm_attrition')\n",
    "sd_wine = (root/'wine_quality')\n",
    "sd_pulsar = (root/'pulsar')\n",
    "sd_kepler = (root/'kepler')\n",
    "sd_eeg = (root/'eeg')\n",
    "sd_mobile = (root/'mobile_pricce') # typo\n",
    "sd_clinvar = (root/'clinvar')\n",
    "sd_lol = (root/'lol')\n",
    "sd_exoplanet = (root/'kepler_exoplanet')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mushroom Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading mushroom-classification.zip to ./data\\mushroom\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/34.2k [00:00<?, ?B/s]\n",
      "100%|##########| 34.2k/34.2k [00:00<00:00, 35.2MB/s]\n"
     ]
    }
   ],
   "source": [
    "# mushroom data\n",
    "!kaggle datasets download -d uciml/mushroom-classification -p {sd_mushroom}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['mushroom-classification.zip']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking file structure\n",
    "os.listdir(sd_mushroom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# unzipping our mushroom file\n",
    "with zipfile.ZipFile(f'{sd_mushroom}/mushroom-classification.zip',\"r\") as zip_ref:\n",
    "    zip_ref.extractall(sd_mushroom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['mushroom-classification.zip', 'mushrooms.csv']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_mushroom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's remove our zipped file \\\n",
    "os.remove(f'{sd_mushroom}/mushroom-classification.zip')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>class</th>\n",
       "      <th>cap-shape</th>\n",
       "      <th>cap-surface</th>\n",
       "      <th>cap-color</th>\n",
       "      <th>bruises</th>\n",
       "      <th>odor</th>\n",
       "      <th>gill-attachment</th>\n",
       "      <th>gill-spacing</th>\n",
       "      <th>gill-size</th>\n",
       "      <th>gill-color</th>\n",
       "      <th>...</th>\n",
       "      <th>stalk-surface-below-ring</th>\n",
       "      <th>stalk-color-above-ring</th>\n",
       "      <th>stalk-color-below-ring</th>\n",
       "      <th>veil-type</th>\n",
       "      <th>veil-color</th>\n",
       "      <th>ring-number</th>\n",
       "      <th>ring-type</th>\n",
       "      <th>spore-print-color</th>\n",
       "      <th>population</th>\n",
       "      <th>habitat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <th>1</th>\n",
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       "      <th>2</th>\n",
       "      <td>e</td>\n",
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       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
       "      <td>y</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>p</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
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       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e</td>\n",
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       "      <td>k</td>\n",
       "      <td>...</td>\n",
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       "      <td>a</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  class cap-shape cap-surface cap-color bruises odor gill-attachment  \\\n",
       "0     p         x           s         n       t    p               f   \n",
       "1     e         x           s         y       t    a               f   \n",
       "2     e         b           s         w       t    l               f   \n",
       "3     p         x           y         w       t    p               f   \n",
       "4     e         x           s         g       f    n               f   \n",
       "\n",
       "  gill-spacing gill-size gill-color  ... stalk-surface-below-ring  \\\n",
       "0            c         n          k  ...                        s   \n",
       "1            c         b          k  ...                        s   \n",
       "2            c         b          n  ...                        s   \n",
       "3            c         n          n  ...                        s   \n",
       "4            w         b          k  ...                        s   \n",
       "\n",
       "  stalk-color-above-ring stalk-color-below-ring veil-type veil-color  \\\n",
       "0                      w                      w         p          w   \n",
       "1                      w                      w         p          w   \n",
       "2                      w                      w         p          w   \n",
       "3                      w                      w         p          w   \n",
       "4                      w                      w         p          w   \n",
       "\n",
       "  ring-number ring-type spore-print-color population habitat  \n",
       "0           o         p                 k          s       u  \n",
       "1           o         p                 n          n       g  \n",
       "2           o         p                 n          n       m  \n",
       "3           o         p                 k          s       u  \n",
       "4           o         e                 n          a       g  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking head of the file\n",
    "pd.read_csv(sd_mushroom/'mushrooms.csv').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lending Club data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# downloaded the file manually due to file size\n",
    "# unzipping has been done through the terminal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['loan.csv']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_lending)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2260668 entries, 0 to 2260667\n",
      "Columns: 145 entries, id to settlement_term\n",
      "dtypes: float64(105), int64(4), object(36)\n",
      "memory usage: 2.4+ GB\n"
     ]
    }
   ],
   "source": [
    "# checking head of our data\n",
    "pd.read_csv(sd_lending/'loan.csv', low_memory=False).info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# experimenting with this dataset will require using dask or even rapids. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Telco Customer Churn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading telco-customer-churn.zip to ./data\\telco\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/172k [00:00<?, ?B/s]\n",
      "100%|##########| 172k/172k [00:00<00:00, 4.41MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d blastchar/telco-customer-churn -p {sd_telco}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['telco-customer-churn.zip']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_telco)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# unzipping file\n",
    "with zipfile.ZipFile(f'{sd_telco}/telco-customer-churn.zip',\"r\") as zip_ref:\n",
    "    zip_ref.extractall(sd_telco)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['telco-customer-churn.zip', 'WA_Fn-UseC_-Telco-Customer-Churn.csv']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_telco)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.remove(sd_telco/'telco-customer-churn.zip')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\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>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>...</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
       "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
       "2  3668-QPYBK    Male              0      No         No       2          Yes   \n",
       "3  7795-CFOCW    Male              0      No         No      45           No   \n",
       "4  9237-HQITU  Female              0      No         No       2          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
       "0  No phone service             DSL             No  ...               No   \n",
       "1                No             DSL            Yes  ...              Yes   \n",
       "2                No             DSL            Yes  ...               No   \n",
       "3  No phone service             DSL            Yes  ...              Yes   \n",
       "4                No     Fiber optic             No  ...               No   \n",
       "\n",
       "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
       "0          No          No              No  Month-to-month              Yes   \n",
       "1          No          No              No        One year               No   \n",
       "2          No          No              No  Month-to-month              Yes   \n",
       "3         Yes          No              No        One year               No   \n",
       "4          No          No              No  Month-to-month              Yes   \n",
       "\n",
       "               PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
       "0           Electronic check          29.85         29.85    No  \n",
       "1               Mailed check          56.95        1889.5    No  \n",
       "2               Mailed check          53.85        108.15   Yes  \n",
       "3  Bank transfer (automatic)          42.30       1840.75    No  \n",
       "4           Electronic check          70.70        151.65   Yes  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking head\n",
    "pd.read_csv(sd_telco/'WA_Fn-UseC_-Telco-Customer-Churn.csv').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IBM Attrition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading ibm-hr-analytics-attrition-dataset.zip to ./data\\ibm_attrition\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/50.1k [00:00<?, ?B/s]\n",
      "100%|##########| 50.1k/50.1k [00:00<00:00, 2.79MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d pavansubhasht/ibm-hr-analytics-attrition-dataset -p {sd_ibm}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ibm-hr-analytics-attrition-dataset.zip']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_ibm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# unzipping file\n",
    "unzip_file(sd_ibm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'WA_Fn-UseC_-HR-Employee-Attrition.csv'"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f = os.listdir(sd_ibm)[0]\n",
    "f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1102</td>\n",
       "      <td>Sales</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>49</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>279</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1373</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Other</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>3</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>33</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>1392</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>591</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age Attrition     BusinessTravel  DailyRate              Department  \\\n",
       "0   41       Yes      Travel_Rarely       1102                   Sales   \n",
       "1   49        No  Travel_Frequently        279  Research & Development   \n",
       "2   37       Yes      Travel_Rarely       1373  Research & Development   \n",
       "3   33        No  Travel_Frequently       1392  Research & Development   \n",
       "4   27        No      Travel_Rarely        591  Research & Development   \n",
       "\n",
       "   DistanceFromHome  Education EducationField  EmployeeCount  EmployeeNumber  \\\n",
       "0                 1          2  Life Sciences              1               1   \n",
       "1                 8          1  Life Sciences              1               2   \n",
       "2                 2          2          Other              1               4   \n",
       "3                 3          4  Life Sciences              1               5   \n",
       "4                 2          1        Medical              1               7   \n",
       "\n",
       "   ...  RelationshipSatisfaction StandardHours  StockOptionLevel  \\\n",
       "0  ...                         1            80                 0   \n",
       "1  ...                         4            80                 1   \n",
       "2  ...                         2            80                 0   \n",
       "3  ...                         3            80                 0   \n",
       "4  ...                         4            80                 1   \n",
       "\n",
       "   TotalWorkingYears  TrainingTimesLastYear WorkLifeBalance  YearsAtCompany  \\\n",
       "0                  8                      0               1               6   \n",
       "1                 10                      3               3              10   \n",
       "2                  7                      3               3               0   \n",
       "3                  8                      3               3               8   \n",
       "4                  6                      3               3               2   \n",
       "\n",
       "  YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                  4                        0                     5  \n",
       "1                  7                        1                     7  \n",
       "2                  0                        0                     0  \n",
       "3                  7                        3                     0  \n",
       "4                  2                        2                     2  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking head\n",
    "pd.read_csv(f'{sd_ibm}/{f}').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Red Wine Quality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading red-wine-quality-cortez-et-al-2009.zip to ./data\\wine_quality\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/25.6k [00:00<?, ?B/s]\n",
      "100%|##########| 25.6k/25.6k [00:00<00:00, 12.9MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d uciml/red-wine-quality-cortez-et-al-2009 -p {sd_wine}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['red-wine-quality-cortez-et-al-2009.zip']"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_wine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['winequality-red.csv']"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unzipping file\n",
    "unzip_file(sd_wine)\n",
    "os.listdir(sd_wine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.098</td>\n",
       "      <td>25.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.9968</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.68</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.04</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.092</td>\n",
       "      <td>15.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.9970</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.65</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.2</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.56</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.075</td>\n",
       "      <td>17.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.9980</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "0            7.4              0.70         0.00             1.9      0.076   \n",
       "1            7.8              0.88         0.00             2.6      0.098   \n",
       "2            7.8              0.76         0.04             2.3      0.092   \n",
       "3           11.2              0.28         0.56             1.9      0.075   \n",
       "4            7.4              0.70         0.00             1.9      0.076   \n",
       "\n",
       "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "0                 11.0                  34.0   0.9978  3.51       0.56   \n",
       "1                 25.0                  67.0   0.9968  3.20       0.68   \n",
       "2                 15.0                  54.0   0.9970  3.26       0.65   \n",
       "3                 17.0                  60.0   0.9980  3.16       0.58   \n",
       "4                 11.0                  34.0   0.9978  3.51       0.56   \n",
       "\n",
       "   alcohol  quality  \n",
       "0      9.4        5  \n",
       "1      9.8        5  \n",
       "2      9.8        5  \n",
       "3      9.8        6  \n",
       "4      9.4        5  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reading file\n",
    "f = os.listdir(sd_wine)[0]\n",
    "pd.read_csv(f'{sd_wine}/{f}').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predicting a Pulsar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading predicting-a-pulsar-star.zip to ./data\\pulsar\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/771k [00:00<?, ?B/s]\n",
      "100%|##########| 771k/771k [00:00<00:00, 6.60MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d pavanraj159/predicting-a-pulsar-star -p {sd_pulsar}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['predicting-a-pulsar-star.zip']"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_pulsar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['pulsar_stars.csv']"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unzipping file\n",
    "unzip_file(sd_pulsar)\n",
    "os.listdir(sd_pulsar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>Mean of the integrated profile</th>\n",
       "      <th>Standard deviation of the integrated profile</th>\n",
       "      <th>Excess kurtosis of the integrated profile</th>\n",
       "      <th>Skewness of the integrated profile</th>\n",
       "      <th>Mean of the DM-SNR curve</th>\n",
       "      <th>Standard deviation of the DM-SNR curve</th>\n",
       "      <th>Excess kurtosis of the DM-SNR curve</th>\n",
       "      <th>Skewness of the DM-SNR curve</th>\n",
       "      <th>target_class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>140.562500</td>\n",
       "      <td>55.683782</td>\n",
       "      <td>-0.234571</td>\n",
       "      <td>-0.699648</td>\n",
       "      <td>3.199833</td>\n",
       "      <td>19.110426</td>\n",
       "      <td>7.975532</td>\n",
       "      <td>74.242225</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>102.507812</td>\n",
       "      <td>58.882430</td>\n",
       "      <td>0.465318</td>\n",
       "      <td>-0.515088</td>\n",
       "      <td>1.677258</td>\n",
       "      <td>14.860146</td>\n",
       "      <td>10.576487</td>\n",
       "      <td>127.393580</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>103.015625</td>\n",
       "      <td>39.341649</td>\n",
       "      <td>0.323328</td>\n",
       "      <td>1.051164</td>\n",
       "      <td>3.121237</td>\n",
       "      <td>21.744669</td>\n",
       "      <td>7.735822</td>\n",
       "      <td>63.171909</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>136.750000</td>\n",
       "      <td>57.178449</td>\n",
       "      <td>-0.068415</td>\n",
       "      <td>-0.636238</td>\n",
       "      <td>3.642977</td>\n",
       "      <td>20.959280</td>\n",
       "      <td>6.896499</td>\n",
       "      <td>53.593661</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>88.726562</td>\n",
       "      <td>40.672225</td>\n",
       "      <td>0.600866</td>\n",
       "      <td>1.123492</td>\n",
       "      <td>1.178930</td>\n",
       "      <td>11.468720</td>\n",
       "      <td>14.269573</td>\n",
       "      <td>252.567306</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Mean of the integrated profile  \\\n",
       "0                       140.562500   \n",
       "1                       102.507812   \n",
       "2                       103.015625   \n",
       "3                       136.750000   \n",
       "4                        88.726562   \n",
       "\n",
       "    Standard deviation of the integrated profile  \\\n",
       "0                                      55.683782   \n",
       "1                                      58.882430   \n",
       "2                                      39.341649   \n",
       "3                                      57.178449   \n",
       "4                                      40.672225   \n",
       "\n",
       "    Excess kurtosis of the integrated profile  \\\n",
       "0                                   -0.234571   \n",
       "1                                    0.465318   \n",
       "2                                    0.323328   \n",
       "3                                   -0.068415   \n",
       "4                                    0.600866   \n",
       "\n",
       "    Skewness of the integrated profile   Mean of the DM-SNR curve  \\\n",
       "0                            -0.699648                   3.199833   \n",
       "1                            -0.515088                   1.677258   \n",
       "2                             1.051164                   3.121237   \n",
       "3                            -0.636238                   3.642977   \n",
       "4                             1.123492                   1.178930   \n",
       "\n",
       "    Standard deviation of the DM-SNR curve  \\\n",
       "0                                19.110426   \n",
       "1                                14.860146   \n",
       "2                                21.744669   \n",
       "3                                20.959280   \n",
       "4                                11.468720   \n",
       "\n",
       "    Excess kurtosis of the DM-SNR curve   Skewness of the DM-SNR curve  \\\n",
       "0                              7.975532                      74.242225   \n",
       "1                             10.576487                     127.393580   \n",
       "2                              7.735822                      63.171909   \n",
       "3                              6.896499                      53.593661   \n",
       "4                             14.269573                     252.567306   \n",
       "\n",
       "   target_class  \n",
       "0             0  \n",
       "1             0  \n",
       "2             0  \n",
       "3             0  \n",
       "4             0  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking head\n",
    "f = os.listdir(sd_pulsar)[0]\n",
    "pd.read_csv(f'{sd_pulsar}/{f}').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exoplanet Hunting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading kepler-labelled-time-series-data.zip to ./data\\kepler\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/55.9M [00:00<?, ?B/s]\n",
      "  2%|1         | 1.00M/55.9M [00:00<00:06, 9.56MB/s]\n",
      "  5%|5         | 3.00M/55.9M [00:00<00:05, 10.3MB/s]\n",
      "  9%|8         | 5.00M/55.9M [00:00<00:04, 11.4MB/s]\n",
      " 13%|#2        | 7.00M/55.9M [00:00<00:04, 12.0MB/s]\n",
      " 16%|#6        | 9.00M/55.9M [00:00<00:03, 12.7MB/s]\n",
      " 20%|#9        | 11.0M/55.9M [00:00<00:03, 13.1MB/s]\n",
      " 23%|##3       | 13.0M/55.9M [00:01<00:03, 13.5MB/s]\n",
      " 27%|##6       | 15.0M/55.9M [00:01<00:03, 13.7MB/s]\n",
      " 30%|###       | 17.0M/55.9M [00:01<00:02, 14.0MB/s]\n",
      " 34%|###3      | 19.0M/55.9M [00:01<00:02, 14.1MB/s]\n",
      " 38%|###7      | 21.0M/55.9M [00:01<00:02, 14.1MB/s]\n",
      " 41%|####1     | 23.0M/55.9M [00:01<00:02, 14.3MB/s]\n",
      " 45%|####4     | 25.0M/55.9M [00:01<00:02, 14.3MB/s]\n",
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      " 63%|######2   | 35.0M/55.9M [00:02<00:01, 14.7MB/s]\n",
      " 66%|######6   | 37.0M/55.9M [00:02<00:01, 14.9MB/s]\n",
      " 70%|######9   | 39.0M/55.9M [00:02<00:01, 14.5MB/s]\n",
      " 73%|#######3  | 41.0M/55.9M [00:03<00:01, 14.6MB/s]\n",
      " 77%|#######6  | 43.0M/55.9M [00:03<00:00, 15.1MB/s]\n",
      " 80%|########  | 45.0M/55.9M [00:03<00:00, 14.3MB/s]\n",
      " 84%|########4 | 47.0M/55.9M [00:03<00:00, 14.0MB/s]\n",
      " 88%|########7 | 49.0M/55.9M [00:03<00:00, 14.8MB/s]\n",
      " 91%|#########1| 51.0M/55.9M [00:03<00:00, 13.9MB/s]\n",
      " 95%|#########4| 53.0M/55.9M [00:03<00:00, 15.0MB/s]\n",
      " 98%|#########8| 55.0M/55.9M [00:04<00:00, 14.7MB/s]\n",
      "100%|##########| 55.9M/55.9M [00:04<00:00, 14.3MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d keplersmachines/kepler-labelled-time-series-data -p {sd_kepler}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['kepler-labelled-time-series-data.zip']"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_kepler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['exoTest.csv', 'exoTrain.csv']"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unzipping file\n",
    "unzip_file(sd_kepler)\n",
    "os.listdir(sd_kepler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>FLUX.1</th>\n",
       "      <th>FLUX.2</th>\n",
       "      <th>FLUX.3</th>\n",
       "      <th>FLUX.4</th>\n",
       "      <th>FLUX.5</th>\n",
       "      <th>FLUX.6</th>\n",
       "      <th>FLUX.7</th>\n",
       "      <th>FLUX.8</th>\n",
       "      <th>FLUX.9</th>\n",
       "      <th>...</th>\n",
       "      <th>FLUX.3188</th>\n",
       "      <th>FLUX.3189</th>\n",
       "      <th>FLUX.3190</th>\n",
       "      <th>FLUX.3191</th>\n",
       "      <th>FLUX.3192</th>\n",
       "      <th>FLUX.3193</th>\n",
       "      <th>FLUX.3194</th>\n",
       "      <th>FLUX.3195</th>\n",
       "      <th>FLUX.3196</th>\n",
       "      <th>FLUX.3197</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>93.85</td>\n",
       "      <td>83.81</td>\n",
       "      <td>20.10</td>\n",
       "      <td>-26.98</td>\n",
       "      <td>-39.56</td>\n",
       "      <td>-124.71</td>\n",
       "      <td>-135.18</td>\n",
       "      <td>-96.27</td>\n",
       "      <td>-79.89</td>\n",
       "      <td>...</td>\n",
       "      <td>-78.07</td>\n",
       "      <td>-102.15</td>\n",
       "      <td>-102.15</td>\n",
       "      <td>25.13</td>\n",
       "      <td>48.57</td>\n",
       "      <td>92.54</td>\n",
       "      <td>39.32</td>\n",
       "      <td>61.42</td>\n",
       "      <td>5.08</td>\n",
       "      <td>-39.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>-38.88</td>\n",
       "      <td>-33.83</td>\n",
       "      <td>-58.54</td>\n",
       "      <td>-40.09</td>\n",
       "      <td>-79.31</td>\n",
       "      <td>-72.81</td>\n",
       "      <td>-86.55</td>\n",
       "      <td>-85.33</td>\n",
       "      <td>-83.97</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.28</td>\n",
       "      <td>-32.21</td>\n",
       "      <td>-32.21</td>\n",
       "      <td>-24.89</td>\n",
       "      <td>-4.86</td>\n",
       "      <td>0.76</td>\n",
       "      <td>-11.70</td>\n",
       "      <td>6.46</td>\n",
       "      <td>16.00</td>\n",
       "      <td>19.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>532.64</td>\n",
       "      <td>535.92</td>\n",
       "      <td>513.73</td>\n",
       "      <td>496.92</td>\n",
       "      <td>456.45</td>\n",
       "      <td>466.00</td>\n",
       "      <td>464.50</td>\n",
       "      <td>486.39</td>\n",
       "      <td>436.56</td>\n",
       "      <td>...</td>\n",
       "      <td>-71.69</td>\n",
       "      <td>13.31</td>\n",
       "      <td>13.31</td>\n",
       "      <td>-29.89</td>\n",
       "      <td>-20.88</td>\n",
       "      <td>5.06</td>\n",
       "      <td>-11.80</td>\n",
       "      <td>-28.91</td>\n",
       "      <td>-70.02</td>\n",
       "      <td>-96.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>326.52</td>\n",
       "      <td>347.39</td>\n",
       "      <td>302.35</td>\n",
       "      <td>298.13</td>\n",
       "      <td>317.74</td>\n",
       "      <td>312.70</td>\n",
       "      <td>322.33</td>\n",
       "      <td>311.31</td>\n",
       "      <td>312.42</td>\n",
       "      <td>...</td>\n",
       "      <td>5.71</td>\n",
       "      <td>-3.73</td>\n",
       "      <td>-3.73</td>\n",
       "      <td>30.05</td>\n",
       "      <td>20.03</td>\n",
       "      <td>-12.67</td>\n",
       "      <td>-8.77</td>\n",
       "      <td>-17.31</td>\n",
       "      <td>-17.35</td>\n",
       "      <td>13.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>-1107.21</td>\n",
       "      <td>-1112.59</td>\n",
       "      <td>-1118.95</td>\n",
       "      <td>-1095.10</td>\n",
       "      <td>-1057.55</td>\n",
       "      <td>-1034.48</td>\n",
       "      <td>-998.34</td>\n",
       "      <td>-1022.71</td>\n",
       "      <td>-989.57</td>\n",
       "      <td>...</td>\n",
       "      <td>-594.37</td>\n",
       "      <td>-401.66</td>\n",
       "      <td>-401.66</td>\n",
       "      <td>-357.24</td>\n",
       "      <td>-443.76</td>\n",
       "      <td>-438.54</td>\n",
       "      <td>-399.71</td>\n",
       "      <td>-384.65</td>\n",
       "      <td>-411.79</td>\n",
       "      <td>-510.54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 3198 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   LABEL   FLUX.1   FLUX.2   FLUX.3   FLUX.4   FLUX.5   FLUX.6  FLUX.7  \\\n",
       "0      2    93.85    83.81    20.10   -26.98   -39.56  -124.71 -135.18   \n",
       "1      2   -38.88   -33.83   -58.54   -40.09   -79.31   -72.81  -86.55   \n",
       "2      2   532.64   535.92   513.73   496.92   456.45   466.00  464.50   \n",
       "3      2   326.52   347.39   302.35   298.13   317.74   312.70  322.33   \n",
       "4      2 -1107.21 -1112.59 -1118.95 -1095.10 -1057.55 -1034.48 -998.34   \n",
       "\n",
       "    FLUX.8  FLUX.9  ...  FLUX.3188  FLUX.3189  FLUX.3190  FLUX.3191  \\\n",
       "0   -96.27  -79.89  ...     -78.07    -102.15    -102.15      25.13   \n",
       "1   -85.33  -83.97  ...      -3.28     -32.21     -32.21     -24.89   \n",
       "2   486.39  436.56  ...     -71.69      13.31      13.31     -29.89   \n",
       "3   311.31  312.42  ...       5.71      -3.73      -3.73      30.05   \n",
       "4 -1022.71 -989.57  ...    -594.37    -401.66    -401.66    -357.24   \n",
       "\n",
       "   FLUX.3192  FLUX.3193  FLUX.3194  FLUX.3195  FLUX.3196  FLUX.3197  \n",
       "0      48.57      92.54      39.32      61.42       5.08     -39.54  \n",
       "1      -4.86       0.76     -11.70       6.46      16.00      19.93  \n",
       "2     -20.88       5.06     -11.80     -28.91     -70.02     -96.67  \n",
       "3      20.03     -12.67      -8.77     -17.31     -17.35      13.98  \n",
       "4    -443.76    -438.54    -399.71    -384.65    -411.79    -510.54  \n",
       "\n",
       "[5 rows x 3198 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reading our trail file\n",
    "f = os.listdir(sd_kepler)[1]\n",
    "pd.read_csv(f'{sd_kepler}/{f}').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EEG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading confused-eeg.zip to ./data\\eeg\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/109M [00:00<?, ?B/s]\n",
      "  1%|          | 1.00M/109M [00:00<00:26, 4.19MB/s]\n",
      "  3%|2         | 3.00M/109M [00:00<00:21, 5.25MB/s]\n",
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      " 10%|#         | 11.0M/109M [00:01<00:10, 10.1MB/s]\n",
      " 12%|#1        | 13.0M/109M [00:01<00:09, 11.1MB/s]\n",
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      " 17%|#7        | 19.0M/109M [00:01<00:07, 13.1MB/s]\n",
      " 19%|#9        | 21.0M/109M [00:01<00:06, 13.6MB/s]\n",
      " 21%|##1       | 23.0M/109M [00:01<00:06, 13.7MB/s]\n",
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      " 30%|###       | 33.0M/109M [00:02<00:05, 13.9MB/s]\n",
      " 32%|###2      | 35.0M/109M [00:02<00:05, 14.2MB/s]\n",
      " 34%|###3      | 37.0M/109M [00:02<00:05, 14.9MB/s]\n",
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      " 40%|###9      | 43.0M/109M [00:03<00:04, 14.8MB/s]\n",
      " 41%|####1     | 45.0M/109M [00:03<00:04, 14.8MB/s]\n",
      " 43%|####3     | 47.0M/109M [00:03<00:04, 14.6MB/s]\n",
      " 45%|####5     | 49.0M/109M [00:03<00:04, 14.6MB/s]\n",
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      " 51%|#####     | 55.0M/109M [00:04<00:03, 14.6MB/s]\n",
      " 52%|#####2    | 57.0M/109M [00:04<00:03, 14.8MB/s]\n",
      " 54%|#####4    | 59.0M/109M [00:04<00:03, 14.7MB/s]\n",
      " 56%|#####6    | 61.0M/109M [00:04<00:03, 14.5MB/s]\n",
      " 58%|#####7    | 63.0M/109M [00:04<00:03, 14.6MB/s]\n",
      " 60%|#####9    | 65.0M/109M [00:04<00:03, 14.4MB/s]\n",
      " 62%|######1   | 67.0M/109M [00:05<00:03, 14.5MB/s]\n",
      " 63%|######3   | 69.0M/109M [00:05<00:02, 14.4MB/s]\n",
      " 65%|######5   | 71.0M/109M [00:05<00:02, 14.4MB/s]\n",
      " 67%|######7   | 73.0M/109M [00:05<00:02, 14.5MB/s]\n",
      " 69%|######8   | 75.0M/109M [00:05<00:02, 14.4MB/s]\n",
      " 71%|#######   | 77.0M/109M [00:05<00:02, 14.5MB/s]\n",
      " 73%|#######2  | 79.0M/109M [00:05<00:02, 14.3MB/s]\n",
      " 74%|#######4  | 81.0M/109M [00:06<00:02, 14.0MB/s]\n",
      " 76%|#######6  | 83.0M/109M [00:06<00:01, 13.7MB/s]\n",
      " 78%|#######8  | 85.0M/109M [00:06<00:01, 13.8MB/s]\n",
      " 80%|#######9  | 87.0M/109M [00:06<00:01, 14.1MB/s]\n",
      " 82%|########1 | 89.0M/109M [00:06<00:01, 14.1MB/s]\n",
      " 84%|########3 | 91.0M/109M [00:06<00:01, 14.3MB/s]\n",
      " 85%|########5 | 93.0M/109M [00:06<00:01, 14.2MB/s]\n",
      " 87%|########7 | 95.0M/109M [00:07<00:01, 14.4MB/s]\n",
      " 89%|########9 | 97.0M/109M [00:07<00:00, 13.4MB/s]\n",
      " 91%|######### | 99.0M/109M [00:07<00:00, 14.7MB/s]\n",
      " 93%|#########2| 101M/109M [00:07<00:00, 14.6MB/s] \n",
      " 95%|#########4| 103M/109M [00:07<00:00, 13.8MB/s]\n",
      " 96%|#########6| 105M/109M [00:07<00:00, 14.7MB/s]\n",
      " 98%|#########8| 107M/109M [00:08<00:00, 14.0MB/s]\n",
      "100%|##########| 109M/109M [00:08<00:00, 14.9MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d wanghaohan/confused-eeg -p {sd_eeg}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['confused-eeg.zip']"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_eeg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['demographic_info.csv', 'EEG_data.csv', 'videos']"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unzipping\n",
    "unzip_file(sd_eeg)\n",
    "os.listdir(sd_eeg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# removing other data\n",
    "# used bash terminal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['EEG_data.csv']"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_eeg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>SubjectID</th>\n",
       "      <th>VideoID</th>\n",
       "      <th>Attention</th>\n",
       "      <th>Mediation</th>\n",
       "      <th>Raw</th>\n",
       "      <th>Delta</th>\n",
       "      <th>Theta</th>\n",
       "      <th>Alpha1</th>\n",
       "      <th>Alpha2</th>\n",
       "      <th>Beta1</th>\n",
       "      <th>Beta2</th>\n",
       "      <th>Gamma1</th>\n",
       "      <th>Gamma2</th>\n",
       "      <th>predefinedlabel</th>\n",
       "      <th>user-definedlabeln</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>278.0</td>\n",
       "      <td>301963.0</td>\n",
       "      <td>90612.0</td>\n",
       "      <td>33735.0</td>\n",
       "      <td>23991.0</td>\n",
       "      <td>27946.0</td>\n",
       "      <td>45097.0</td>\n",
       "      <td>33228.0</td>\n",
       "      <td>8293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>-50.0</td>\n",
       "      <td>73787.0</td>\n",
       "      <td>28083.0</td>\n",
       "      <td>1439.0</td>\n",
       "      <td>2240.0</td>\n",
       "      <td>2746.0</td>\n",
       "      <td>3687.0</td>\n",
       "      <td>5293.0</td>\n",
       "      <td>2740.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>758353.0</td>\n",
       "      <td>383745.0</td>\n",
       "      <td>201999.0</td>\n",
       "      <td>62107.0</td>\n",
       "      <td>36293.0</td>\n",
       "      <td>130536.0</td>\n",
       "      <td>57243.0</td>\n",
       "      <td>25354.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>2012240.0</td>\n",
       "      <td>129350.0</td>\n",
       "      <td>61236.0</td>\n",
       "      <td>17084.0</td>\n",
       "      <td>11488.0</td>\n",
       "      <td>62462.0</td>\n",
       "      <td>49960.0</td>\n",
       "      <td>33932.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>1005145.0</td>\n",
       "      <td>354328.0</td>\n",
       "      <td>37102.0</td>\n",
       "      <td>88881.0</td>\n",
       "      <td>45307.0</td>\n",
       "      <td>99603.0</td>\n",
       "      <td>44790.0</td>\n",
       "      <td>29749.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SubjectID  VideoID  Attention  Mediation    Raw      Delta     Theta  \\\n",
       "0        0.0      0.0       56.0       43.0  278.0   301963.0   90612.0   \n",
       "1        0.0      0.0       40.0       35.0  -50.0    73787.0   28083.0   \n",
       "2        0.0      0.0       47.0       48.0  101.0   758353.0  383745.0   \n",
       "3        0.0      0.0       47.0       57.0   -5.0  2012240.0  129350.0   \n",
       "4        0.0      0.0       44.0       53.0   -8.0  1005145.0  354328.0   \n",
       "\n",
       "     Alpha1   Alpha2    Beta1     Beta2   Gamma1   Gamma2  predefinedlabel  \\\n",
       "0   33735.0  23991.0  27946.0   45097.0  33228.0   8293.0              0.0   \n",
       "1    1439.0   2240.0   2746.0    3687.0   5293.0   2740.0              0.0   \n",
       "2  201999.0  62107.0  36293.0  130536.0  57243.0  25354.0              0.0   \n",
       "3   61236.0  17084.0  11488.0   62462.0  49960.0  33932.0              0.0   \n",
       "4   37102.0  88881.0  45307.0   99603.0  44790.0  29749.0              0.0   \n",
       "\n",
       "   user-definedlabeln  \n",
       "0                 0.0  \n",
       "1                 0.0  \n",
       "2                 0.0  \n",
       "3                 0.0  \n",
       "4                 0.0  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking head\n",
    "f = os.listdir(sd_eeg)[0]\n",
    "pd.read_csv(f'{sd_eeg}/{f}').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mobile Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading mobile-price-classification.zip to ./data\\mobile_pricce\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/70.6k [00:00<?, ?B/s]\n",
      "100%|##########| 70.6k/70.6k [00:00<00:00, 3.29MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d iabhishekofficial/mobile-price-classification -p {sd_mobile}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['mobile-price-classification.zip']"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_mobile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['test.csv', 'train.csv']"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unzipping\n",
    "unzip_file(sd_mobile)\n",
    "os.listdir(sd_mobile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>battery_power</th>\n",
       "      <th>blue</th>\n",
       "      <th>clock_speed</th>\n",
       "      <th>dual_sim</th>\n",
       "      <th>fc</th>\n",
       "      <th>four_g</th>\n",
       "      <th>int_memory</th>\n",
       "      <th>m_dep</th>\n",
       "      <th>mobile_wt</th>\n",
       "      <th>n_cores</th>\n",
       "      <th>...</th>\n",
       "      <th>px_height</th>\n",
       "      <th>px_width</th>\n",
       "      <th>ram</th>\n",
       "      <th>sc_h</th>\n",
       "      <th>sc_w</th>\n",
       "      <th>talk_time</th>\n",
       "      <th>three_g</th>\n",
       "      <th>touch_screen</th>\n",
       "      <th>wifi</th>\n",
       "      <th>price_range</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>842</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.6</td>\n",
       "      <td>188</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>756</td>\n",
       "      <td>2549</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1021</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "      <td>0.7</td>\n",
       "      <td>136</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>905</td>\n",
       "      <td>1988</td>\n",
       "      <td>2631</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>563</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>41</td>\n",
       "      <td>0.9</td>\n",
       "      <td>145</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>1263</td>\n",
       "      <td>1716</td>\n",
       "      <td>2603</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>615</td>\n",
       "      <td>1</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0.8</td>\n",
       "      <td>131</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>1216</td>\n",
       "      <td>1786</td>\n",
       "      <td>2769</td>\n",
       "      <td>16</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1821</td>\n",
       "      <td>1</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>44</td>\n",
       "      <td>0.6</td>\n",
       "      <td>141</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>1208</td>\n",
       "      <td>1212</td>\n",
       "      <td>1411</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   battery_power  blue  clock_speed  dual_sim  fc  four_g  int_memory  m_dep  \\\n",
       "0            842     0          2.2         0   1       0           7    0.6   \n",
       "1           1021     1          0.5         1   0       1          53    0.7   \n",
       "2            563     1          0.5         1   2       1          41    0.9   \n",
       "3            615     1          2.5         0   0       0          10    0.8   \n",
       "4           1821     1          1.2         0  13       1          44    0.6   \n",
       "\n",
       "   mobile_wt  n_cores  ...  px_height  px_width   ram  sc_h  sc_w  talk_time  \\\n",
       "0        188        2  ...         20       756  2549     9     7         19   \n",
       "1        136        3  ...        905      1988  2631    17     3          7   \n",
       "2        145        5  ...       1263      1716  2603    11     2          9   \n",
       "3        131        6  ...       1216      1786  2769    16     8         11   \n",
       "4        141        2  ...       1208      1212  1411     8     2         15   \n",
       "\n",
       "   three_g  touch_screen  wifi  price_range  \n",
       "0        0             0     1            1  \n",
       "1        1             1     0            2  \n",
       "2        1             1     0            2  \n",
       "3        1             0     0            2  \n",
       "4        1             1     0            1  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking header\n",
    "pd.read_csv(f'{sd_mobile}/train.csv').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Genetic Variation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading clinvar-conflicting.zip to ./data\\clinvar\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/3.43M [00:00<?, ?B/s]\n",
      " 29%|##9       | 1.00M/3.43M [00:00<00:00, 8.34MB/s]\n",
      "100%|##########| 3.43M/3.43M [00:00<00:00, 19.4MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d kevinarvai/clinvar-conflicting -p {sd_clinvar}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['clinvar-conflicting.zip']"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_clinvar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['clinvar_conflicting.csv']"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unzip_file(sd_clinvar)\n",
    "os.listdir(sd_clinvar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>CHROM</th>\n",
       "      <th>POS</th>\n",
       "      <th>REF</th>\n",
       "      <th>ALT</th>\n",
       "      <th>AF_ESP</th>\n",
       "      <th>AF_EXAC</th>\n",
       "      <th>AF_TGP</th>\n",
       "      <th>CLNDISDB</th>\n",
       "      <th>CLNDISDBINCL</th>\n",
       "      <th>CLNDN</th>\n",
       "      <th>...</th>\n",
       "      <th>SIFT</th>\n",
       "      <th>PolyPhen</th>\n",
       "      <th>MOTIF_NAME</th>\n",
       "      <th>MOTIF_POS</th>\n",
       "      <th>HIGH_INF_POS</th>\n",
       "      <th>MOTIF_SCORE_CHANGE</th>\n",
       "      <th>LoFtool</th>\n",
       "      <th>CADD_PHRED</th>\n",
       "      <th>CADD_RAW</th>\n",
       "      <th>BLOSUM62</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>955563</td>\n",
       "      <td>G</td>\n",
       "      <td>C</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>MedGen:C3808739,OMIM:615120|MedGen:CN169374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Myasthenic_syndrome,_congenital,_8|not_specified</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.421</td>\n",
       "      <td>11.390</td>\n",
       "      <td>1.133255</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>955597</td>\n",
       "      <td>G</td>\n",
       "      <td>T</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.42418</td>\n",
       "      <td>0.2826</td>\n",
       "      <td>MedGen:CN169374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not_specified</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.421</td>\n",
       "      <td>8.150</td>\n",
       "      <td>0.599088</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>955619</td>\n",
       "      <td>G</td>\n",
       "      <td>C</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.03475</td>\n",
       "      <td>0.0088</td>\n",
       "      <td>MedGen:C3808739,OMIM:615120|MedGen:CN169374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Myasthenic_syndrome,_congenital,_8|not_specified</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.421</td>\n",
       "      <td>3.288</td>\n",
       "      <td>0.069819</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>957640</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.02016</td>\n",
       "      <td>0.0328</td>\n",
       "      <td>MedGen:C3808739,OMIM:615120|MedGen:CN169374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Myasthenic_syndrome,_congenital,_8|not_specified</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.421</td>\n",
       "      <td>12.560</td>\n",
       "      <td>1.356499</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>976059</td>\n",
       "      <td>C</td>\n",
       "      <td>T</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00022</td>\n",
       "      <td>0.0010</td>\n",
       "      <td>MedGen:CN169374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>not_specified</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.421</td>\n",
       "      <td>17.740</td>\n",
       "      <td>2.234711</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  CHROM     POS REF ALT  AF_ESP  AF_EXAC  AF_TGP  \\\n",
       "0     1  955563   G   C  0.0000  0.00000  0.0000   \n",
       "1     1  955597   G   T  0.0000  0.42418  0.2826   \n",
       "2     1  955619   G   C  0.0000  0.03475  0.0088   \n",
       "3     1  957640   C   T  0.0318  0.02016  0.0328   \n",
       "4     1  976059   C   T  0.0000  0.00022  0.0010   \n",
       "\n",
       "                                      CLNDISDB CLNDISDBINCL  \\\n",
       "0  MedGen:C3808739,OMIM:615120|MedGen:CN169374          NaN   \n",
       "1                              MedGen:CN169374          NaN   \n",
       "2  MedGen:C3808739,OMIM:615120|MedGen:CN169374          NaN   \n",
       "3  MedGen:C3808739,OMIM:615120|MedGen:CN169374          NaN   \n",
       "4                              MedGen:CN169374          NaN   \n",
       "\n",
       "                                              CLNDN  ... SIFT PolyPhen  \\\n",
       "0  Myasthenic_syndrome,_congenital,_8|not_specified  ...  NaN      NaN   \n",
       "1                                     not_specified  ...  NaN      NaN   \n",
       "2  Myasthenic_syndrome,_congenital,_8|not_specified  ...  NaN      NaN   \n",
       "3  Myasthenic_syndrome,_congenital,_8|not_specified  ...  NaN      NaN   \n",
       "4                                     not_specified  ...  NaN      NaN   \n",
       "\n",
       "  MOTIF_NAME MOTIF_POS HIGH_INF_POS MOTIF_SCORE_CHANGE  LoFtool  CADD_PHRED  \\\n",
       "0        NaN       NaN          NaN                NaN    0.421      11.390   \n",
       "1        NaN       NaN          NaN                NaN    0.421       8.150   \n",
       "2        NaN       NaN          NaN                NaN    0.421       3.288   \n",
       "3        NaN       NaN          NaN                NaN    0.421      12.560   \n",
       "4        NaN       NaN          NaN                NaN    0.421      17.740   \n",
       "\n",
       "   CADD_RAW BLOSUM62  \n",
       "0  1.133255     -2.0  \n",
       "1  0.599088      NaN  \n",
       "2  0.069819      1.0  \n",
       "3  1.356499      NaN  \n",
       "4  2.234711      NaN  \n",
       "\n",
       "[5 rows x 46 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(f'{sd_clinvar}/clinvar_conflicting.csv', low_memory=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## League of Legends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading league-of-legends.zip to ./data\\lol\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/2.99M [00:00<?, ?B/s]\n",
      " 33%|###3      | 1.00M/2.99M [00:00<00:00, 8.03MB/s]\n",
      "100%|##########| 2.99M/2.99M [00:00<00:00, 15.5MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d datasnaek/league-of-legends -p {sd_lol}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['league-of-legends.zip']"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_lol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['champion_info.json',\n",
       " 'champion_info_2.json',\n",
       " 'games.csv',\n",
       " 'summoner_spell_info.json']"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unzip_file(sd_lol)\n",
    "os.listdir(sd_lol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['games.csv']"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.remove(f'{sd_lol}/champion_info.json')\n",
    "os.remove(f'{sd_lol}/champion_info_2.json')\n",
    "os.remove(f'{sd_lol}/summoner_spell_info.json')\n",
    "os.listdir(sd_lol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gameId</th>\n",
       "      <th>creationTime</th>\n",
       "      <th>gameDuration</th>\n",
       "      <th>seasonId</th>\n",
       "      <th>winner</th>\n",
       "      <th>firstBlood</th>\n",
       "      <th>firstTower</th>\n",
       "      <th>firstInhibitor</th>\n",
       "      <th>firstBaron</th>\n",
       "      <th>firstDragon</th>\n",
       "      <th>...</th>\n",
       "      <th>t2_towerKills</th>\n",
       "      <th>t2_inhibitorKills</th>\n",
       "      <th>t2_baronKills</th>\n",
       "      <th>t2_dragonKills</th>\n",
       "      <th>t2_riftHeraldKills</th>\n",
       "      <th>t2_ban1</th>\n",
       "      <th>t2_ban2</th>\n",
       "      <th>t2_ban3</th>\n",
       "      <th>t2_ban4</th>\n",
       "      <th>t2_ban5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>51</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3229566029</td>\n",
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       "      <td>9</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>67</td>\n",
       "      <td>238</td>\n",
       "      <td>51</td>\n",
       "      <td>420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3327363504</td>\n",
       "      <td>1504360103310</td>\n",
       "      <td>1493</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>157</td>\n",
       "      <td>238</td>\n",
       "      <td>121</td>\n",
       "      <td>57</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3326856598</td>\n",
       "      <td>1504348503996</td>\n",
       "      <td>1758</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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>0</td>\n",
       "      <td>164</td>\n",
       "      <td>18</td>\n",
       "      <td>141</td>\n",
       "      <td>40</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3330080762</td>\n",
       "      <td>1504554410899</td>\n",
       "      <td>2094</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>86</td>\n",
       "      <td>11</td>\n",
       "      <td>201</td>\n",
       "      <td>122</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       gameId   creationTime  gameDuration  seasonId  winner  firstBlood  \\\n",
       "0  3326086514  1504279457970          1949         9       1           2   \n",
       "1  3229566029  1497848803862          1851         9       1           1   \n",
       "2  3327363504  1504360103310          1493         9       1           2   \n",
       "3  3326856598  1504348503996          1758         9       1           1   \n",
       "4  3330080762  1504554410899          2094         9       1           2   \n",
       "\n",
       "   firstTower  firstInhibitor  firstBaron  firstDragon  ...  t2_towerKills  \\\n",
       "0           1               1           1            1  ...              5   \n",
       "1           1               1           0            1  ...              2   \n",
       "2           1               1           1            2  ...              2   \n",
       "3           1               1           1            1  ...              0   \n",
       "4           1               1           1            1  ...              3   \n",
       "\n",
       "   t2_inhibitorKills  t2_baronKills  t2_dragonKills  t2_riftHeraldKills  \\\n",
       "0                  0              0               1                   1   \n",
       "1                  0              0               0                   0   \n",
       "2                  0              0               1                   0   \n",
       "3                  0              0               0                   0   \n",
       "4                  0              0               1                   0   \n",
       "\n",
       "   t2_ban1  t2_ban2  t2_ban3  t2_ban4  t2_ban5  \n",
       "0      114       67       43       16       51  \n",
       "1       11       67      238       51      420  \n",
       "2      157      238      121       57       28  \n",
       "3      164       18      141       40       51  \n",
       "4       86       11      201      122       18  \n",
       "\n",
       "[5 rows x 61 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(f'{sd_lol}/games.csv').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exo Planet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading kepler-exoplanet-search-results.zip to ./data\\kepler_exoplanet\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  0%|          | 0.00/1.16M [00:00<?, ?B/s]\n",
      " 86%|########6 | 1.00M/1.16M [00:00<00:00, 8.76MB/s]\n",
      "100%|##########| 1.16M/1.16M [00:00<00:00, 9.91MB/s]\n"
     ]
    }
   ],
   "source": [
    "!kaggle datasets download -d nasa/kepler-exoplanet-search-results -p {sd_exoplanet}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['kepler-exoplanet-search-results.zip']"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(sd_exoplanet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
  },
  {
   "cell_type": "code",
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   "source": []
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   "source": []
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   "source": []
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  {
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  {
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   "cell_type": "code",
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