2. aDATA READING AND VISUALIZATIONS.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ec0795d2",
   "metadata": {},
   "source": [
    "# HELPER MODULES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "af2fdb76",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<frozen importlib._bootstrap>:228: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject\n",
      "C:\\Users\\julmn\\AppData\\Local\\Temp\\ipykernel_7344\\1655117510.py:15: DeprecationWarning: `import pandas_profiling` is going to be deprecated by April 1st. Please use `import ydata_profiling` instead.\n",
      "  import pandas_profiling\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error,accuracy_score, roc_auc_score,f1_score,confusion_matrix,roc_curve\n",
    "from sklearn.preprocessing import StandardScaler, RobustScaler,MinMaxScaler,PolynomialFeatures\n",
    "from sklearn.preprocessing import OrdinalEncoder,LabelEncoder,OrdinalEncoder,OneHotEncoder\n",
    "from sklearn.model_selection import train_test_split, KFold ,GridSearchCV\n",
    "from sklearn.model_selection import train_test_split\n",
    "from imblearn.over_sampling import SMOTE\n",
    "seed=0\n",
    "\n",
    "from sklearn.ensemble import RandomForestRegressor,GradientBoostingRegressor\n",
    "from catboost import CatBoostRegressor,CatBoostClassifier\n",
    "from lightgbm import LGBMRegressor,LGBMClassifier\n",
    "from xgboost import XGBRegressor,XGBClassifier\n",
    "\n",
    "#pip install pandas-profiling\n",
    "import pandas_profiling\n",
    "import pandas as pd\n",
    "pd.set_option('display.max_columns', 100)\n",
    "pd.set_option('display.max_rows', 100)\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import os "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "937c4413",
   "metadata": {},
   "source": [
    "# DATA INGESTION"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b5629a1",
   "metadata": {},
   "source": [
    "**VALIDATION**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "70b83b2a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1932\n",
      "(175150, 11)\n"
     ]
    },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NE ID</th>\n",
       "      <th>endTime</th>\n",
       "      <th>access_success_rate</th>\n",
       "      <th>resource_utilition_rate</th>\n",
       "      <th>TA</th>\n",
       "      <th>bler</th>\n",
       "      <th>cqi</th>\n",
       "      <th>mcs</th>\n",
       "      <th>data_rate</th>\n",
       "      <th>fault_duration</th>\n",
       "      <th>relation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>B0017-25_24</td>\n",
       "      <td>2023-02-20 06:00:00</td>\n",
       "      <td>99.714558</td>\n",
       "      <td>8.678</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B0017-25_24</td>\n",
       "      <td>2023-02-20 07:00:00</td>\n",
       "      <td>99.927484</td>\n",
       "      <td>24.264</td>\n",
       "      <td>3.145402</td>\n",
       "      <td>10.015796</td>\n",
       "      <td>6.141206</td>\n",
       "      <td>6.544645</td>\n",
       "      <td>6.777114</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>B0017-25_24</td>\n",
       "      <td>2023-02-20 08:00:00</td>\n",
       "      <td>99.357688</td>\n",
       "      <td>84.004</td>\n",
       "      <td>2.923368</td>\n",
       "      <td>14.209819</td>\n",
       "      <td>5.582824</td>\n",
       "      <td>5.667775</td>\n",
       "      <td>1.175289</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B0017-25_24</td>\n",
       "      <td>2023-02-20 09:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>301.0</td>\n",
       "      <td>0.654162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>B0017-25_25</td>\n",
       "      <td>2023-02-20 19:00:00</td>\n",
       "      <td>99.264875</td>\n",
       "      <td>93.086</td>\n",
       "      <td>2.732594</td>\n",
       "      <td>16.947693</td>\n",
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       "         NE ID             endTime  access_success_rate  \\\n",
       "0  B0017-25_24 2023-02-20 06:00:00            99.714558   \n",
       "1  B0017-25_24 2023-02-20 07:00:00            99.927484   \n",
       "2  B0017-25_24 2023-02-20 08:00:00            99.357688   \n",
       "3  B0017-25_24 2023-02-20 09:00:00                  NaN   \n",
       "4  B0017-25_25 2023-02-20 19:00:00            99.264875   \n",
       "\n",
       "   resource_utilition_rate        TA       bler       cqi       mcs  \\\n",
       "0                    8.678  3.715410   7.653169  5.964988  5.403557   \n",
       "1                   24.264  3.145402  10.015796  6.141206  6.544645   \n",
       "2                   84.004  2.923368  14.209819  5.582824  5.667775   \n",
       "3                      NaN       NaN        NaN       NaN       NaN   \n",
       "4                   93.086  2.732594  16.947693  5.475508  4.719393   \n",
       "\n",
       "   data_rate  fault_duration  relation  \n",
       "0   6.815789             0.0  0.000000  \n",
       "1   6.777114             0.0  0.000000  \n",
       "2   1.175289             0.0  0.000000  \n",
       "3        NaN           301.0  0.654162  \n",
       "4   0.522540             0.0  0.000000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path=r\"F:\\ZINDI\\validation_clean\"\n",
    "file_list = os.listdir(path)\n",
    "\n",
    "all_dataframes_val = []\n",
    "for filename in file_list:\n",
    "    file_path = os.path.join(path, filename)  # Use os.path.join() to get the full file path\n",
    "    if filename.lower().endswith('.csv'):\n",
    "        df_val = pd.read_csv(file_path)\n",
    "        df_val=df_val.drop(columns=[\"Unnamed: 0\"])\n",
    "        df_val[\"NE ID\"]=df_val[\"NE ID\"]+\"_\"+filename.split(\"_\")[1].replace(\".csv\", \"\").replace(\" \", \"\")\n",
    "        all_dataframes_val.append(df_val)\n",
    "\n",
    "print(len(all_dataframes_val))\n",
    "\n",
    "test= pd.concat(all_dataframes_val, axis=0)\n",
    "test=test.sort_values(by=[\"NE ID\",\"endTime\"],ascending=True)\n",
    "test.to_csv('test.csv',index=False)\n",
    "\n",
    "test=pd.read_csv(\"test.csv\")\n",
    "test['endTime']=pd.to_datetime(test['endTime'])\n",
    "print(test.shape)\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "284274f2",
   "metadata": {},
   "source": [
    "**TRAIN**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5f5d8161",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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       "      <th>NE ID</th>\n",
       "      <th>endTime</th>\n",
       "      <th>access_success_rate</th>\n",
       "      <th>resource_utilition_rate</th>\n",
       "      <th>TA</th>\n",
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       "      <th>fault_duration</th>\n",
       "      <th>relation</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>908002</th>\n",
       "      <td>B0729-13_1</td>\n",
       "      <td>2023-02-27 23:00:00</td>\n",
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       "      <td>B0729-13_1</td>\n",
       "      <td>2023-02-28 00:00:00</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>35.853</td>\n",
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       "      <td>B0729-13_1</td>\n",
       "      <td>2023-02-28 01:00:00</td>\n",
       "      <td>100.000000</td>\n",
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       "      <td>9.725438</td>\n",
       "      <td>22.493861</td>\n",
       "      <td>950.0</td>\n",
       "      <td>0.99</td>\n",
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       "    <tr>\n",
       "      <th>908005</th>\n",
       "      <td>B0729-13_1</td>\n",
       "      <td>2023-02-28 02:00:00</td>\n",
       "      <td>99.547511</td>\n",
       "      <td>1.728</td>\n",
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       "    <tr>\n",
       "      <th>908006</th>\n",
       "      <td>B0729-15_1</td>\n",
       "      <td>2023-02-09 01:00:00</td>\n",
       "      <td>99.977350</td>\n",
       "      <td>29.442</td>\n",
       "      <td>3.055147</td>\n",
       "      <td>10.424411</td>\n",
       "      <td>7.210986</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "             NE ID             endTime  access_success_rate  \\\n",
       "908002  B0729-13_1 2023-02-27 23:00:00            99.975315   \n",
       "908003  B0729-13_1 2023-02-28 00:00:00           100.000000   \n",
       "908004  B0729-13_1 2023-02-28 01:00:00           100.000000   \n",
       "908005  B0729-13_1 2023-02-28 02:00:00            99.547511   \n",
       "908006  B0729-15_1 2023-02-09 01:00:00            99.977350   \n",
       "\n",
       "        resource_utilition_rate        TA       bler       cqi        mcs  \\\n",
       "908002                   44.245  3.244196   9.938242  9.106802  11.470092   \n",
       "908003                   35.853  3.175133  10.320035  9.238970  11.740756   \n",
       "908004                   31.238  3.196790   9.079722  9.034929   9.725438   \n",
       "908005                    1.728  3.338323   6.922154  9.874873   8.773274   \n",
       "908006                   29.442  3.055147  10.424411  7.210986   9.657070   \n",
       "\n",
       "        data_rate  fault_duration  relation  \n",
       "908002  19.380749             0.0      0.00  \n",
       "908003  21.438768             0.0      0.00  \n",
       "908004  22.493861           950.0      0.99  \n",
       "908005  21.961071           209.0      0.99  \n",
       "908006   8.758230             0.0      0.00  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path=r\"F:\\ZINDI\\train\"\n",
    "file_list = os.listdir(path)\n",
    "\n",
    "all_dataframes_train = []\n",
    "for filename in file_list:\n",
    "    file_path = os.path.join(path, filename)  # Use os.path.join() to get the full file path\n",
    "    if filename.lower().endswith('.csv'): #and os.path.getsize(file_path) > 10 * 1024\n",
    "        df_train = pd.read_csv(file_path) \n",
    "        df_train[\"NE ID\"]=df_train[\"NE ID\"]+\"_\"+filename.split(\"_\")[1].replace(\".csv\", \"\").replace(\" \", \"\")\n",
    "        all_dataframes_train.append(df_train)\n",
    "\n",
    "print(len(all_dataframes_train))\n",
    "\n",
    "train= pd.concat(all_dataframes_train, axis=0)\n",
    "train=train.sort_values(by=[\"NE ID\",\"endTime\"],ascending=True)\n",
    "train.to_csv('train.csv',index=False)\n",
    "train=pd.read_csv(\"train.csv\")\n",
    "train['endTime']=pd.to_datetime(train['endTime'])\n",
    "print(train.shape)\n",
    "train.tail(1000)[80:85]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7534e24b",
   "metadata": {},
   "source": [
    "**COMBINE TRAIN & TEST**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1a23885a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1084072\n"
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       "      <th>resource_utilition_rate</th>\n",
       "      <th>TA</th>\n",
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       "      <th>37561</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 05:00:00</td>\n",
       "      <td>100.000000</td>\n",
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       "      <th>37562</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 06:00:00</td>\n",
       "      <td>100.000000</td>\n",
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       "      <th>37563</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 07:00:00</td>\n",
       "      <td>99.747899</td>\n",
       "      <td>14.521</td>\n",
       "      <td>2.963437</td>\n",
       "      <td>11.297409</td>\n",
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       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 08:00:00</td>\n",
       "      <td>99.829787</td>\n",
       "      <td>36.649</td>\n",
       "      <td>2.542375</td>\n",
       "      <td>12.062139</td>\n",
       "      <td>7.125136</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37565</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 09:00:00</td>\n",
       "      <td>99.860807</td>\n",
       "      <td>58.506</td>\n",
       "      <td>2.412703</td>\n",
       "      <td>12.039579</td>\n",
       "      <td>6.916188</td>\n",
       "      <td>7.704837</td>\n",
       "      <td>2.397028</td>\n",
       "      <td>57.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37566</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 10:00:00</td>\n",
       "      <td>99.844781</td>\n",
       "      <td>50.280</td>\n",
       "      <td>2.428769</td>\n",
       "      <td>12.145683</td>\n",
       "      <td>7.321369</td>\n",
       "      <td>8.263317</td>\n",
       "      <td>3.663715</td>\n",
       "      <td>2938.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37567</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 11:00:00</td>\n",
       "      <td>99.942639</td>\n",
       "      <td>46.411</td>\n",
       "      <td>2.510660</td>\n",
       "      <td>12.264153</td>\n",
       "      <td>7.599301</td>\n",
       "      <td>8.270461</td>\n",
       "      <td>5.753700</td>\n",
       "      <td>1089.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37568</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 12:00:00</td>\n",
       "      <td>90.738391</td>\n",
       "      <td>60.956</td>\n",
       "      <td>2.461951</td>\n",
       "      <td>12.093170</td>\n",
       "      <td>7.612720</td>\n",
       "      <td>9.045568</td>\n",
       "      <td>6.245630</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            NE ID             endTime  access_success_rate  \\\n",
       "37561  B0017-13_8 2023-02-17 05:00:00           100.000000   \n",
       "37562  B0017-13_8 2023-02-17 06:00:00           100.000000   \n",
       "37563  B0017-13_8 2023-02-17 07:00:00            99.747899   \n",
       "37564  B0017-13_8 2023-02-17 08:00:00            99.829787   \n",
       "37565  B0017-13_8 2023-02-17 09:00:00            99.860807   \n",
       "37566  B0017-13_8 2023-02-17 10:00:00            99.844781   \n",
       "37567  B0017-13_8 2023-02-17 11:00:00            99.942639   \n",
       "37568  B0017-13_8 2023-02-17 12:00:00            90.738391   \n",
       "\n",
       "       resource_utilition_rate        TA       bler        cqi       mcs  \\\n",
       "37561                    1.054  3.035211   1.884315  10.792361  2.912705   \n",
       "37562                    1.702  2.638554   5.715271  11.273952  9.487271   \n",
       "37563                   14.521  2.963437  11.297409   8.910144  9.713915   \n",
       "37564                   36.649  2.542375  12.062139   7.125136  7.467310   \n",
       "37565                   58.506  2.412703  12.039579   6.916188  7.704837   \n",
       "37566                   50.280  2.428769  12.145683   7.321369  8.263317   \n",
       "37567                   46.411  2.510660  12.264153   7.599301  8.270461   \n",
       "37568                   60.956  2.461951  12.093170   7.612720  9.045568   \n",
       "\n",
       "       data_rate  fault_duration  relation  predict_rows  IStrain  \n",
       "37561  89.909177             0.0  0.000000             0        1  \n",
       "37562  48.475408             0.0  0.000000             0        1  \n",
       "37563   8.450350             0.0  0.000000             0        1  \n",
       "37564   2.897868            46.0  0.654162             0        1  \n",
       "37565   2.397028            57.0  0.654162             0        1  \n",
       "37566   3.663715          2938.0  0.654162             0        1  \n",
       "37567   5.753700          1089.0  0.654162             0        1  \n",
       "37568   6.245630            25.0  0.654162             0        1  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[\"predict_rows\"]=0\n",
    "test[\"predict_rows\"]=0\n",
    "\n",
    "train[\"IStrain\"]=1\n",
    "test[\"IStrain\"]=0\n",
    "\n",
    "test.loc[test[\"fault_duration\"] > 0, \"predict_rows\"] = 1\n",
    "\n",
    "combined_df=pd.concat([train,test]) \n",
    "combined_df.sort_values(by=[\"NE ID\",\"endTime\"],inplace=True)\n",
    "print(len(combined_df))\n",
    "combined_df[combined_df[\"NE ID\"]==\"B0017-13_8\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a40b269",
   "metadata": {},
   "source": [
    "**TARGET VARIABLE**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f25d5c60",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>NE ID</th>\n",
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       "      <th>access_success_rate</th>\n",
       "      <th>resource_utilition_rate</th>\n",
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       "      <td>B0017-13_8</td>\n",
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      "text/plain": [
       "            NE ID             endTime  access_success_rate  \\\n",
       "37561  B0017-13_8 2023-02-17 05:00:00           100.000000   \n",
       "37562  B0017-13_8 2023-02-17 06:00:00           100.000000   \n",
       "37563  B0017-13_8 2023-02-17 07:00:00            99.747899   \n",
       "37564  B0017-13_8 2023-02-17 08:00:00            99.829787   \n",
       "37565  B0017-13_8 2023-02-17 09:00:00            99.860807   \n",
       "37566  B0017-13_8 2023-02-17 10:00:00            99.844781   \n",
       "37567  B0017-13_8 2023-02-17 11:00:00            99.942639   \n",
       "37568  B0017-13_8 2023-02-17 12:00:00            90.738391   \n",
       "\n",
       "       resource_utilition_rate        TA       bler        cqi       mcs  \\\n",
       "37561                    1.054  3.035211   1.884315  10.792361  2.912705   \n",
       "37562                    1.702  2.638554   5.715271  11.273952  9.487271   \n",
       "37563                   14.521  2.963437  11.297409   8.910144  9.713915   \n",
       "37564                   36.649  2.542375  12.062139   7.125136  7.467310   \n",
       "37565                   58.506  2.412703  12.039579   6.916188  7.704837   \n",
       "37566                   50.280  2.428769  12.145683   7.321369  8.263317   \n",
       "37567                   46.411  2.510660  12.264153   7.599301  8.270461   \n",
       "37568                   60.956  2.461951  12.093170   7.612720  9.045568   \n",
       "\n",
       "       data_rate  fault_duration  relation  predict_rows  IStrain  data_roc  \\\n",
       "37561  89.909177             0.0  0.000000             0        1       NaN   \n",
       "37562  48.475408             0.0  0.000000             0        1 -0.460840   \n",
       "37563   8.450350             0.0  0.000000             0        1 -0.825678   \n",
       "37564   2.897868            46.0  0.654162             0        1 -0.657071   \n",
       "37565   2.397028            57.0  0.654162             0        1 -0.172830   \n",
       "37566   3.663715          2938.0  0.654162             0        1  0.528440   \n",
       "37567   5.753700          1089.0  0.654162             0        1  0.570455   \n",
       "37568   6.245630            25.0  0.654162             0        1  0.085498   \n",
       "\n",
       "       data_rate_t+1_trend  \n",
       "37561                    1  \n",
       "37562                    1  \n",
       "37563                    1  \n",
       "37564                    1  \n",
       "37565                    1  \n",
       "37566                    0  \n",
       "37567                    0  \n",
       "37568                    0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df['data_roc']=combined_df.groupby('NE ID',group_keys=False)['data_rate'].apply(lambda x: x.pct_change())#.fillna(0))\n",
    "\n",
    "def data_rate_change(group):\n",
    "    group['data_rate_t+1_trend'] = group['data_roc'].apply(lambda x: 0 if x >= 0 else 1)\n",
    "    return group\n",
    "\n",
    "train_grouped = combined_df.groupby('NE ID', as_index=False, group_keys=False).apply(data_rate_change)\n",
    "\n",
    "# Now you can drop the 'data_roc' column if you want\n",
    "#train_grouped = train_grouped.drop(columns=['data_roc'])\n",
    "\n",
    "# Merge back the data from the grouped DataFrames to the original DataFrames\n",
    "combined_df = train_grouped.reset_index(drop=True)\n",
    "combined_df[combined_df[\"NE ID\"]==\"B0017-13_8\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5dafe7f",
   "metadata": {},
   "source": [
    "# DATA REDUCTION"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36b4a329",
   "metadata": {},
   "source": [
    "**DROP IDS WITH DURATION GREATER THAN ONE IN ALL ROWS OF EACH ID**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2f69e1cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before: 1084072\n",
      "After: 1080657\n"
     ]
    },
    {
     "data": {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>37564</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 08:00:00</td>\n",
       "      <td>99.829787</td>\n",
       "      <td>36.649</td>\n",
       "      <td>2.542375</td>\n",
       "      <td>12.062139</td>\n",
       "      <td>7.125136</td>\n",
       "      <td>7.467310</td>\n",
       "      <td>2.897868</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.657071</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37565</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 09:00:00</td>\n",
       "      <td>99.860807</td>\n",
       "      <td>58.506</td>\n",
       "      <td>2.412703</td>\n",
       "      <td>12.039579</td>\n",
       "      <td>6.916188</td>\n",
       "      <td>7.704837</td>\n",
       "      <td>2.397028</td>\n",
       "      <td>57.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.172830</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37566</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 10:00:00</td>\n",
       "      <td>99.844781</td>\n",
       "      <td>50.280</td>\n",
       "      <td>2.428769</td>\n",
       "      <td>12.145683</td>\n",
       "      <td>7.321369</td>\n",
       "      <td>8.263317</td>\n",
       "      <td>3.663715</td>\n",
       "      <td>2938.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.528440</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37567</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 11:00:00</td>\n",
       "      <td>99.942639</td>\n",
       "      <td>46.411</td>\n",
       "      <td>2.510660</td>\n",
       "      <td>12.264153</td>\n",
       "      <td>7.599301</td>\n",
       "      <td>8.270461</td>\n",
       "      <td>5.753700</td>\n",
       "      <td>1089.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.570455</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37568</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 12:00:00</td>\n",
       "      <td>90.738391</td>\n",
       "      <td>60.956</td>\n",
       "      <td>2.461951</td>\n",
       "      <td>12.093170</td>\n",
       "      <td>7.612720</td>\n",
       "      <td>9.045568</td>\n",
       "      <td>6.245630</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.085498</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            NE ID             endTime  access_success_rate  \\\n",
       "37561  B0017-13_8 2023-02-17 05:00:00           100.000000   \n",
       "37562  B0017-13_8 2023-02-17 06:00:00           100.000000   \n",
       "37563  B0017-13_8 2023-02-17 07:00:00            99.747899   \n",
       "37564  B0017-13_8 2023-02-17 08:00:00            99.829787   \n",
       "37565  B0017-13_8 2023-02-17 09:00:00            99.860807   \n",
       "37566  B0017-13_8 2023-02-17 10:00:00            99.844781   \n",
       "37567  B0017-13_8 2023-02-17 11:00:00            99.942639   \n",
       "37568  B0017-13_8 2023-02-17 12:00:00            90.738391   \n",
       "\n",
       "       resource_utilition_rate        TA       bler        cqi       mcs  \\\n",
       "37561                    1.054  3.035211   1.884315  10.792361  2.912705   \n",
       "37562                    1.702  2.638554   5.715271  11.273952  9.487271   \n",
       "37563                   14.521  2.963437  11.297409   8.910144  9.713915   \n",
       "37564                   36.649  2.542375  12.062139   7.125136  7.467310   \n",
       "37565                   58.506  2.412703  12.039579   6.916188  7.704837   \n",
       "37566                   50.280  2.428769  12.145683   7.321369  8.263317   \n",
       "37567                   46.411  2.510660  12.264153   7.599301  8.270461   \n",
       "37568                   60.956  2.461951  12.093170   7.612720  9.045568   \n",
       "\n",
       "       data_rate  fault_duration  relation  predict_rows  IStrain  data_roc  \\\n",
       "37561  89.909177             0.0  0.000000             0        1       NaN   \n",
       "37562  48.475408             0.0  0.000000             0        1 -0.460840   \n",
       "37563   8.450350             0.0  0.000000             0        1 -0.825678   \n",
       "37564   2.897868            46.0  0.654162             0        1 -0.657071   \n",
       "37565   2.397028            57.0  0.654162             0        1 -0.172830   \n",
       "37566   3.663715          2938.0  0.654162             0        1  0.528440   \n",
       "37567   5.753700          1089.0  0.654162             0        1  0.570455   \n",
       "37568   6.245630            25.0  0.654162             0        1  0.085498   \n",
       "\n",
       "       data_rate_t+1_trend  \n",
       "37561                    1  \n",
       "37562                    1  \n",
       "37563                    1  \n",
       "37564                    1  \n",
       "37565                    1  \n",
       "37566                    0  \n",
       "37567                    0  \n",
       "37568                    0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Before:\", len(combined_df))\n",
    "\n",
    "# Group by 'NE ID'\n",
    "grouped = combined_df.groupby('NE ID')\n",
    "\n",
    "# Function to drop groups with more than one row with fault_duration > 0\n",
    "def drop_groups(group):\n",
    "    if (group['fault_duration'] > 0).sum() == len(group):\n",
    "        return group.head(1)  # Keep only the first row\n",
    "    else:\n",
    "        pass  # Return an empty DataFrame to drop the group\n",
    "\n",
    "# Apply the function to each group\n",
    "filtered_groups = grouped.apply(drop_groups)\n",
    "\n",
    "drop_cols=filtered_groups[\"NE ID\"].unique().tolist()\n",
    "combined_df=combined_df[~combined_df[\"NE ID\"].isin(drop_cols)]\n",
    "print(\"After:\", len(combined_df)) \n",
    "combined_df[combined_df[\"NE ID\"]==\"B0017-13_8\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c439a8ad",
   "metadata": {},
   "source": [
    "**AVERAGE THE ROWS WITH DURATION >0 MANY TIMES INSTEAD OF DROPPING THE DATAFRAMES**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6972f48f",
   "metadata": {},
   "source": [
    "**ONLY PICK THE FIRST ROW OF DURATION>0**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8d12a04c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before: 1080657\n",
      "After: 995512\n"
     ]
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NE ID</th>\n",
       "      <th>endTime</th>\n",
       "      <th>access_success_rate</th>\n",
       "      <th>resource_utilition_rate</th>\n",
       "      <th>TA</th>\n",
       "      <th>bler</th>\n",
       "      <th>cqi</th>\n",
       "      <th>mcs</th>\n",
       "      <th>data_rate</th>\n",
       "      <th>fault_duration</th>\n",
       "      <th>relation</th>\n",
       "      <th>predict_rows</th>\n",
       "      <th>IStrain</th>\n",
       "      <th>data_roc</th>\n",
       "      <th>data_rate_t+1_trend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35624</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 05:00:00</td>\n",
       "      <td>100.000000</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>35625</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 06:00:00</td>\n",
       "      <td>100.000000</td>\n",
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       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35626</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 07:00:00</td>\n",
       "      <td>99.747899</td>\n",
       "      <td>14.521</td>\n",
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       "    <tr>\n",
       "      <th>35627</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 08:00:00</td>\n",
       "      <td>99.829787</td>\n",
       "      <td>36.649</td>\n",
       "      <td>2.542375</td>\n",
       "      <td>12.062139</td>\n",
       "      <td>7.125136</td>\n",
       "      <td>7.467310</td>\n",
       "      <td>2.897868</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.654162</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.657071</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            NE ID             endTime  access_success_rate  \\\n",
       "35624  B0017-13_8 2023-02-17 05:00:00           100.000000   \n",
       "35625  B0017-13_8 2023-02-17 06:00:00           100.000000   \n",
       "35626  B0017-13_8 2023-02-17 07:00:00            99.747899   \n",
       "35627  B0017-13_8 2023-02-17 08:00:00            99.829787   \n",
       "\n",
       "       resource_utilition_rate        TA       bler        cqi       mcs  \\\n",
       "35624                    1.054  3.035211   1.884315  10.792361  2.912705   \n",
       "35625                    1.702  2.638554   5.715271  11.273952  9.487271   \n",
       "35626                   14.521  2.963437  11.297409   8.910144  9.713915   \n",
       "35627                   36.649  2.542375  12.062139   7.125136  7.467310   \n",
       "\n",
       "       data_rate  fault_duration  relation  predict_rows  IStrain  data_roc  \\\n",
       "35624  89.909177             0.0  0.000000             0        1       NaN   \n",
       "35625  48.475408             0.0  0.000000             0        1 -0.460840   \n",
       "35626   8.450350             0.0  0.000000             0        1 -0.825678   \n",
       "35627   2.897868            46.0  0.654162             0        1 -0.657071   \n",
       "\n",
       "       data_rate_t+1_trend  \n",
       "35624                    1  \n",
       "35625                    1  \n",
       "35626                    1  \n",
       "35627                    1  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Before:\", len(combined_df))\n",
    "# Group by 'NE ID'\n",
    "grouped = combined_df.groupby('NE ID')\n",
    "\n",
    "# Function to filter rows\n",
    "def filter_rows(group):\n",
    "    rows_with_fault_duration_zero = group[group['fault_duration'] == 0]\n",
    "    first_fault_duration_gt_zero_index = group[group['fault_duration'] > 0].index[0]\n",
    "    row_with_first_fault_duration_gt_zero = group.loc[first_fault_duration_gt_zero_index:first_fault_duration_gt_zero_index]\n",
    "    return pd.concat([rows_with_fault_duration_zero, row_with_first_fault_duration_gt_zero])\n",
    "\n",
    "# Apply the function to each group and reset index\n",
    "combined_df = grouped.apply(filter_rows).reset_index(drop=True)\n",
    "print(\"After:\", len(combined_df))\n",
    "combined_df[combined_df[\"NE ID\"]==\"B0017-13_8\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f94734be",
   "metadata": {},
   "source": [
    "**DROP ALL ROWS WITH 0 IN THE 'DATA_RATE' COLUMN AND 0 IN THE 'FAULT_DURATION' COLUMN**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a5c04ef4",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before: 995512\n",
      "Before: 957160\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NE ID</th>\n",
       "      <th>endTime</th>\n",
       "      <th>access_success_rate</th>\n",
       "      <th>resource_utilition_rate</th>\n",
       "      <th>TA</th>\n",
       "      <th>bler</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35624</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 05:00:00</td>\n",
       "      <td>100.000000</td>\n",
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       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 06:00:00</td>\n",
       "      <td>100.000000</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>35626</th>\n",
       "      <td>B0017-13_8</td>\n",
       "      <td>2023-02-17 07:00:00</td>\n",
       "      <td>99.747899</td>\n",
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      ],
      "text/plain": [
       "            NE ID             endTime  access_success_rate  \\\n",
       "35624  B0017-13_8 2023-02-17 05:00:00           100.000000   \n",
       "35625  B0017-13_8 2023-02-17 06:00:00           100.000000   \n",
       "35626  B0017-13_8 2023-02-17 07:00:00            99.747899   \n",
       "35627  B0017-13_8 2023-02-17 08:00:00            99.829787   \n",
       "\n",
       "       resource_utilition_rate        TA       bler        cqi       mcs  \\\n",
       "35624                    1.054  3.035211   1.884315  10.792361  2.912705   \n",
       "35625                    1.702  2.638554   5.715271  11.273952  9.487271   \n",
       "35626                   14.521  2.963437  11.297409   8.910144  9.713915   \n",
       "35627                   36.649  2.542375  12.062139   7.125136  7.467310   \n",
       "\n",
       "       data_rate  fault_duration  relation  predict_rows  IStrain  data_roc  \\\n",
       "35624  89.909177             0.0  0.000000             0        1       NaN   \n",
       "35625  48.475408             0.0  0.000000             0        1 -0.460840   \n",
       "35626   8.450350             0.0  0.000000             0        1 -0.825678   \n",
       "35627   2.897868            46.0  0.654162             0        1 -0.657071   \n",
       "\n",
       "       data_rate_t+1_trend  \n",
       "35624                    1  \n",
       "35625                    1  \n",
       "35626                    1  \n",
       "35627                    1  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Before:\", len(combined_df))\n",
    "combined_df = combined_df.loc[(combined_df['data_rate'] != 0) | (combined_df['fault_duration'] != 0)]\n",
    "print(\"Before:\", len(combined_df))\n",
    "combined_df[combined_df[\"NE ID\"]==\"B0017-13_8\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55c32267",
   "metadata": {},
   "source": [
    "# VISUALIZE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4826a2d",
   "metadata": {},
   "source": [
    "**NULL VALS AND INCOSISTENT DFS**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "20381aae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NE ID                          0\n",
      "endTime                        0\n",
      "access_success_rate        50335\n",
      "resource_utilition_rate     2150\n",
      "TA                          2796\n",
      "bler                        2545\n",
      "cqi                         2485\n",
      "mcs                         2486\n",
      "data_rate                   2905\n",
      "fault_duration                 0\n",
      "relation                       0\n",
      "predict_rows                   0\n",
      "IStrain                        0\n",
      "data_roc                    9077\n",
      "data_rate_t+1_trend            0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(combined_df.isnull().sum())\n",
    "#combined_df.fillna(0,inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be0184cf",
   "metadata": {},
   "source": [
    "**ADVERSERIAL VALIDATION**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "58ef9ac2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adversarial Validation ROC-AUC Score: 0.8224635306112992\n"
     ]
    }
   ],
   "source": [
    "y = combined_df['IStrain']\n",
    "X = combined_df[[\n",
    " 'access_success_rate',\n",
    " 'resource_utilition_rate',\n",
    " 'TA',\n",
    " 'bler',\n",
    " 'cqi',\n",
    " 'mcs',\n",
    " 'data_rate',\n",
    " 'fault_duration',\n",
    " 'relation',\n",
    "]]\n",
    "\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(X, y, test_size=0.2, random_state=seed)\n",
    "\n",
    "model = LGBMClassifier(random_state=seed) \n",
    "model.fit(X_train, y_train)\n",
    "# Predict the probabilities of being in the train set for the validation data\n",
    "valid_pred_proba = model.predict_proba(X_valid)[:, 1]\n",
    "\n",
    "# Calculate the ROC-AUC score for adversarial validation\n",
    "roc_auc = roc_auc_score(y_valid, valid_pred_proba)\n",
    "print(\"Adversarial Validation ROC-AUC Score:\", roc_auc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cc7475cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 Features:\n",
      "TA\n",
      "cqi\n",
      "resource_utilition_rate\n",
      "data_rate\n",
      "bler\n",
      "access_success_rate\n",
      "mcs\n",
      "fault_duration\n",
      "relation\n",
      "Adversarial Validation ROC-AUC Score: 0.821982891801414\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x201d4fcfd60>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = LGBMClassifier(random_state=42)\n",
    "model.fit(X_train, y_train)\n",
    "feature_importances = model.feature_importances_\n",
    "sorted_indices = feature_importances.argsort()[::-1]\n",
    "top_10_features = sorted_indices[:10]\n",
    "print(\"Top 10 Features:\")\n",
    "for feature_index in top_10_features:\n",
    "    print(X_train.columns[feature_index])\n",
    "    pass\n",
    "\n",
    "#Predict the probabilities of being in the train set for the validation data\n",
    "valid_pred_proba = model.predict_proba(X_valid)[:, 1]\n",
    "roc_auc = roc_auc_score(y_valid, valid_pred_proba)\n",
    "print(\"Adversarial Validation ROC-AUC Score:\", roc_auc)\n",
    "fpr, tpr, _ = roc_curve(y_valid, valid_pred_proba)\n",
    "\n",
    "#Plot the ROC curve\n",
    "plt.figure(figsize=(15, 3))\n",
    "plt.plot(fpr, tpr, color='b', lw=2, label='ROC curve (AUC = %0.4f)' % roc_auc)\n",
    "plt.plot([0, 1], [0, 1], color='r', lw=2, linestyle='--', label='Random')\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Adversarial Validation ROC Curve')\n",
    "plt.legend(loc='lower right')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61ff5023",
   "metadata": {},
   "source": [
    "**BAR PLOTS-NUMERICAL**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "25959579",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['predict_rows', 'IStrain']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numeric_cols=[]\n",
    "categorical_cols=[]\n",
    "\n",
    "for column in [col for col in train.columns.tolist() if col not in [\"target\"]]:\n",
    "    if train[column].nunique()>30:\n",
    "        numeric_cols.append(column)\n",
    "    elif train[column].nunique()<30:\n",
    "        categorical_cols.append(column)\n",
    "categorical_cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "27091d7a",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0Z6F8Yi5rk3R8j3fSzKwbOEE2M+s73gB2iYgtgC2BiZImAKcDZ0bExsBiYErefwqwOJefmfdD0jjSjzNtBkwEzpXUT1I/4CfAXsA44MC8r5lZU3GCbGbWR0TySl4dkB8B7AJcmcunAfvk5Ul5nbx9V0nK5dMj4o2ImAO0ke49vw3QFhFPRMSbwPS8r5lZU3GCbGbWh+QrvfcDC4CbgceBJfnXSQHmASPz8khgLkDe/hLp10nfLS85plK5mVlTcYJsZtaHRMTbEbElMIp0xXfTnm6DpCMkzZY0e+HChT1dvZlZh5wgm5n1QRGxBLgN2A4YJql/3jQKmJ+X5wOjAfL21YFFxfKSYyqVl9Y9NSLGR8T44cOHd1eXzMy6jRNkM7M+QtJwScPy8mBgd+ARUqK8b95tMnBNXp6R18nbb42IyOUH5LtcbACMBe4B7gXG5rtiDCRN5JtR946ZmXWz/h3vYmZmLWIEMC3fbWIl4IqI+J2kh4Hpkk4B/gJcmPe/ELhUUhvwIinhJSIeknQF8DCwDDgyIt4GkPQ1YCbQD7goIh7que6ZmXUPJ8hmZn1ERDwAbFWm/AnSeOTS8teB/Sqc61Tg1DLl1wPXr3BjzcwayEMszMzMzMwKnCCbmZmZmRU4QTYzMzMzK3CCbGZmZmZW4ATZzMzMzKzACbKZmZmZWYETZDMzMzOzAifIZmZmZmYFTpDNzMzMzArqliBLGiTpHkl/lfSQpJNz+QaS7pbUJulySQNz+cp5vS1vH1M41wm5/FFJexbKJ+ayNknHF8rL1mFmZmZm1pF6XkF+A9glIrYAtgQmSpoAnA6cGREbA4uBKXn/KcDiXH5m3g9J44ADgM2AicC5kvpJ6gf8BNgLGAccmPelSh1mZmZmZlXVLUGO5JW8OiA/AtgFuDKXTwP2ycuT8jp5+66SlMunR8QbETEHaAO2yY+2iHgiIt4EpgOT8jGV6jAzMzMzq6quY5Dzld77gQXAzcDjwJKIWJZ3mQeMzMsjgbkAeftLwFrF8pJjKpWvVaWO0vYdIWm2pNkLFy5cgZ6amZmZWauoa4IcEW9HxJbAKNIV303rWV9nRcTUiBgfEeOHDx/e6OaYmZmZWS/QI3exiIglwG3AdsAwSf3zplHA/Lw8HxgNkLevDiwqlpccU6l8UZU6zMzMzMyqquddLIZLGpaXBwO7A4+QEuV9826TgWvy8oy8Tt5+a0RELj8g3+ViA2AscA9wLzA237FiIGki34x8TKU6zMzMzMyq6t/xLl02ApiW7zaxEnBFRPxO0sPAdEmnAH8BLsz7XwhcKqkNeJGU8BIRD0m6AngYWAYcGRFvA0j6GjAT6AdcFBEP5XMdV6EOMzMzM7Oq6pYgR8QDwFZlyp8gjUcuLX8d2K/CuU4FTi1Tfj1wfa11mJmZmZl1xL+kZ2ZmZmZW4ATZzMzMzKzACbKZmZmZWYETZDMzMzOzAifIZmZmZmYFTpDNzMzMzAqcIJuZmZmZFThBNjMzMzMrcIJsZmZmZlZQU4IsaYdayszMrP4ck83M6qvWK8j/U2OZmZnVn2OymVkd9a+2UdJ2wPbAcEnHFDYNBfrVs2FmZvZeKxqTJY0GLgHWAQKYGhFnS1oTuBwYAzwJ7B8RiyUJOBvYG/gncGhE/G8+12TgO/nUp0TEtFy+NXAxMBi4HjgqImIFum1m1uM6uoI8EFiNlEgPKTyWAvvWt2lmZlZiRWPyMuDYiBgHTACOlDQOOB64JSLGArfkdYC9gLH5cQRwHkBOqE8CtgW2AU6StEY+5jzg8MJxE1egv2ZmDVH1CnJE/AH4g6SLI+KpHmqTmZmVsaIxOSKeBZ7Nyy9LegQYCUwCdsq7TQNmAcfl8kvyFeC7JA2TNCLve3NEvAgg6WZgoqRZwNCIuCuXXwLsA9zQlf6amTVK1QS5YGVJU0lfv717TETsUo9GmZlZVSsckyWNAbYC7gbWyckzwHOkIRiQkue5hcPm5bJq5fPKlJuZNZVaE+RfA+cDFwBv1685ZmZWgxWKyZJWA34DHB0RS9NQ4yQiQlJdxwxLOoI0ZIP11luvnlWZmXVJrQnysog4r64tMTOzWnU5JksaQEqOL4uI3+bi5yWNiIhn8xCKBbl8PjC6cPioXDaf5UMy2stn5fJRZfZ/j4iYCkwFGD9+vCfwmVmvU+tt3q6V9FVJIySt2f6oa8vMzKySLsXkfFeKC4FHIuKMwqYZwOS8PBm4plB+iJIJwEt5KMZMYA9Ja+TJeXsAM/O2pZIm5LoOKZzLzKxp1HoFuT1wfqtQFsCG3dscMzOrQVdj8g7AwcCDku7PZScCpwFXSJoCPAXsn7ddT7rFWxvpNm+HAUTEi5K+D9yb9/te+4Q94Kssv83bDXiCnpk1oZoS5IjYoN4NMTOz2nQ1JkfEHYAqbN61zP4BHFnhXBcBF5Upnw1s3pX2mZn1FjUlyJIOKVceEZd0b3PMzKwjjslmZvVV6xCLjxeWB5GuNPwv6ReZzMysZzkmm5nVUa1DLL5eXJc0DJhejwaZmVl1jslmZvVV610sSr0KVB0DJ2m0pNskPSzpIUlH5fI1Jd0s6bH87xq5XJLOkdQm6QFJHyuca3Le/zFJkwvlW0t6MB9zTp41XbEOM7MW1WFMNjOz2tWUIEu6VtKM/LgOeBS4qoPDlgHHRsQ4YAJwpKRxwPHALRExFrglrwPsBYzNjyOA83LdawInAdsC2wAnFRLe84DDC8dNzOWV6jAza3pdjMlmZlajWscg/6iwvAx4KiLmVdoZIN8P89m8/LKkR0g/OTqJ5TeYn0a6ufxxufySPGv6LknD8g3rdwJubr+FkKSbgYmSZgFDI+KuXH4JsA/plkKV6jAzawWdjslmZla7mq4gR8QfgL8DQ4A1gDc7U4mkMcBWwN3AOjl5BngOWCcvjwTmFg6bl8uqlc8rU06VOkrbdYSk2ZJmL1y4sDNdMjNrmBWNyWZmVl2tQyz2B+4B9iPdQP5uSfvWeOxqpJ81PToilha35avFdf2Z0Wp1RMTUiBgfEeOHDx9ez2aYmXWbFYnJZmbWsVqHWPwf4OMRsQBA0nDg98CV1Q6SNICUHF8WEb/Nxc9LGhERz+YhFAty+XxgdOHwUblsPsuHS7SXz8rlo8rsX60OM7NW0KWYbGZmtan1LhYrtQfibFFHx+Y7SlwIPBIRZxQ2zWD5z6ROBq4plB+S72YxAXgpD5OYCewhaY08OW8PYGbetlTShFzXISXnKleHmVkr6HRMNjOz2tV6BflGSTOBX+X1LwDXd3DMDsDBwIOS7s9lJwKnAVdImgI8Rfp6kHy+vYE24J/AYQAR8aKk7wP35v2+1z5hD/gqcDEwmDQ574ZcXqkOM7NW0JWYbGZmNaqaIEvamDTh7VuS/hXYMW/6M3BZtWMj4g5AFTbvWmb/AI6scK6LgIvKlM8GNi9TvqhcHWZmzWxFYrKZmdWuoyvIZwEnAOQxxL8FkPSRvO0zdWybmZm911k4JpuZ1V1HY9bWiYgHSwtz2Zi6tMjMzCpxTDYz6wEdJcjDqmwb3I3tMDOzjg2rss0x2cysm3SUIM+WdHhpoaR/B+6rT5PMzKwCx2Qzsx7Q0Rjko4GrJB3E8uA7HhgIfK6O7TIzs/c7GsdkM7O6q5ogR8TzwPaSdmb53SKui4hb694yMzN7D8dkM7OeUdN9kCPiNuC2OrfFzMxq4JhsZlZf/uUlMzMzM7MCJ8hmZmZmZgVOkM3MzMzMCpwgm5mZmZkVOEE2MzMzMytwgmxmZmZmVuAE2czMzMyswAmymZmZmVmBE2QzMzMzswInyGZmZmZmBU6Qzcz6CEkXSVog6W+FsjUl3SzpsfzvGrlcks6R1CbpAUkfKxwzOe//mKTJhfKtJT2YjzlHknq2h2Zm3cMJsplZ33ExMLGk7HjglogYC9yS1wH2AsbmxxHAeZASauAkYFtgG+Ck9qQ673N44bjSuszMmoITZDOzPiIi/gi8WFI8CZiWl6cB+xTKL4nkLmCYpBHAnsDNEfFiRCwGbgYm5m1DI+KuiAjgksK5zMyaihNkM7O+bZ2IeDYvPwesk5dHAnML+83LZdXK55Upfx9JR0iaLWn2woULV7wHZmbdzAmymZkBkK/8Rg/UMzUixkfE+OHDh9e7OjOzTnOCbGbWtz2fh0eQ/12Qy+cDowv7jcpl1cpHlSk3M2s6dUuQGzVbulIdZmZW1gygPbZOBq4plB+S4/ME4KU8FGMmsIekNXJ83QOYmbctlTQhx+NDCucyM2sq9byCfDGNmS1dqQ4zsz5N0q+APwObSJonaQpwGrC7pMeA3fI6wPXAE0Ab8DPgqwAR8SLwfeDe/PheLiPvc0E+5nHghp7ol5lZd+tfrxNHxB8ljSkpngTslJenAbOA4yjMlgbuktQ+W3on8mxpAEnts6VnkWdL5/L22dI3VKnDzKxPi4gDK2zatcy+ARxZ4TwXAReVKZ8NbL4ibTQz6w16egxyT8yWrlTH+3gmtZmZmZmVatgkvZ6YLd1RHZ5JbWZmZmalejpB7onZ0pXqMDMzMzPrUE8nyD0xW7pSHWZmZmZmHarbJL08W3onYG1J80h3ozgNuCLPnH4K2D/vfj2wN2nm8z+BwyDNlpbUPlsa3j9b+mJgMGlyXvts6Up1mJmZmZl1qJ53sWjIbOmIWFSuDjMzMzOzWviX9MzMzMzMCpwgm5mZmZkVOEE2MzMzMytwgmxmZmZmVuAE2czMzMyswAmymZmZmVmBE2QzMzMzswInyGZmZmZmBU6QzczMzMwKnCCbmZmZmRU4QTYzMzMzK3CCbGZmZmZW4ATZzMzMzKzACbKZmZmZWYETZDMzMzOzAifIZmZmZmYFTpDNzMzMzAqcIJuZmZmZFThBNjMzMzMrcIJsZmZmZlbgBNnMzMzMrMAJspmZmZlZgRNkMzMzM7OClk2QJU2U9KikNknHN7o9ZmZ9heOvmTW7lkyQJfUDfgLsBYwDDpQ0rrGtMjNrfY6/ZtYKWjJBBrYB2iLiiYh4E5gOTGpwm8ysxR0w9c+NbkJv4PhrZj2qHrG3f7efsXcYCcwtrM8Dti3dSdIRwBF59RVJj3aynrWBF7rUwt6p1foDrdenVusPtFifLv9yl/qzfj3a0iAdxl/H3rJarU+t1h9ovT61VH+6GHuhQvxt1QS5JhExFZja1eMlzY6I8d3YpIZqtf5A6/Wp1foDrdenVutPPTj2vl+r9anV+gOt1yf3p7pWHWIxHxhdWB+Vy8zMrL4cf82s6bVqgnwvMFbSBpIGAgcAMxrcJjOzvsDx18yaXksOsYiIZZK+BswE+gEXRcRDdaiqy18R9lKt1h9ovT61Wn+g9frUav3plB6Kv634HLdan1qtP9B6fXJ/qlBEdOf5zMzMzMyaWqsOsTAzMzMz6xInyGZmZmZmBU6QzczMzMwKnCB3gqRNJG0naUD+OVXrpSSp+K/1Pn6NrDMcf5uD39e9n1+j2jhBrpGkfwWuAU4BLgSOlDS0sa3qPpJGSxooadW83uz/Nz6Q/+0PLdEfv0ZNRFn7cqPb0+xaOf76fd37+TVqHt0Ze1vmSaknSQOALwBTImJXUqAeDRzXCkFa0qeAG4AfAz+XtElEvNOsbxpJnwauljQVOFnSmGbuD/g1aiaSJgEXARdJ+kT4VkErpJXjr9/XvZ9fo+bR3bG36Z+QHjQUGJuXrwJ+BwwAvtisV4jyH1qjgdOArwH/CdwDzJK0WTO+aSRtBJwDnABcCrwKXC5pbDP2B0DSSOB0/Br1epK2IL1WvwbuBs6T9EVJqzW2ZU2vpeKvY29zcOxtHvWIvS35QyHdLSLeknQG8HVJj0fE7ZLuAEYCewM/bWwLuyYiQtIzwJ+Bx4AFEfEjSW8BN0naOSL+0dhWdtoLwG0RMSt/cN4BLAMulfSFiHiqsc3rHEmDSX26HfgHrfEaLQJuaJXXqMQHgb9HxPUAkp4EjgIC+JWklSLinQa2r+m0Yvx17O39HHubTrfH3qb9a6EBbgduAg6W9C8R8XZE/BJYF9iisU3rPEkbS/o4MAxYHTio/euIiDgbOBs4UdKgZrhCI2lHSV8ClgIfknR8ZMAPgetIr12/ZugPvPt10Y9I/8fWBA5r8tdogqSDge2A7SUd0+yvURn3A0slbZsD8o2kKzb/KWl7J8dd1jLx17G393PsbUr3082x11eQaxQRr0u6jPTXyAmSNgXeANYBnm1o4zpJaQzSfwGLgQeBy4BzJPWLiB/k3a4gfQ3zRm8eQ5m/ElqFdBWpP/AKsD/pL/zXIuLs/NXRPcCkiHi7gc2tmaRPkr4uOioi5kj6FnB77tMZebemeI0AJH2WNMHqAWAJ8F3gVEmvR8S5zfgatZO0LTAIeDUiZucrF18Anpc0NyJukLQxsC9wZwOb2rRaJf469vZ+jr3No96x1wlyJ0TEYkk/Ax4Gvgy8DnwpIp5vbMtqJ2l70l+MX4yIvygN1N8G2B64S+n2SdOBHYGtSVc5FjeouR3KfxW+Imka8DYpQK8B7ALcKWlZRPwEGAFsImkI8EpvD2qk5/6CiJgpaT1gNeA7wLmSXgduIV0N6PWvkaS1gCNJ/+f+JukS4DXg68C0fMHiPJrvNULSXqSrFLcBH5TUFhHHSDof+AZpvOztpMRu5ca1tPk1e/x17G2a97Vjb+9/jXok9qoJnodeKQezaLavTHOQ/lBEXJzXhwMXR8SnJG1ICgSvA9sCh0bEgw1rbCdIOgZYD7gWOBx4CNgKWBuYQ/og2r+J+vMNYGAe83Yn8AzwOPAJYAHwFOmD9d96e58krU56Xc4BbiZ9FfZwfqwPbATcC3yS5nqN+pGuAF4XEZcq3VHhJuDBiDhc0n8Cm5D+D44mfUj9tXEtbh3NGH8de5umP469vVxPxV4nyH1M/o+1akQszcsjSG+gvSPiWUnrA/PzPi81sq2doTQ7d7+IOE3SsaTZ4adExMmSBgJDI+KFxraydpI+AlwJ/AWYGRE/l/Qh4DDgroi4RtIaEdFrr14USdqX9JXkW8D1EfE9SXsAuwEzgNnAkIhY2MBmdpqk44BnIuLSQtmdwJ8i4luS1gA2B+ZExLxGtdMaz7G3OTj2NoeeiL2epNfHRJrcsjSvijQm6cUcoL8EnAgMaKYAnb1G+orocOArpDFX20j6SkS82UwBGiD/Jf9N0tWkDXLZP0g3eF8977akIY3rgoi4khSQbwf+N5fdRLp111oR8XqzBOj8YdluPul+vOsVyj4LbCRpXEQsjojbnRybY29zcOztvXo69noMch8WEctIY8jmSvoBsAfpq73XGty0TouIZyTNJd2r8siIuFbSzkBbg5u2Im4ATgK+K6n99jtbkCb50AzjxIryGNJbgf0lvUmaXLE+0DTDDvIkqyskzYiIAyLiF5I2Af4kaYeIeDoiXsj9872PrSzH3l7PsbeXaUTs9RCLPkxphP4A4JH8764R8VhjW9V1Sjfe/0BE3JfXW+Kes5I+RpqFuzJpzGJTjBMrR9Iw4BDg86Txlt9ulnG5Sj8z+xvgt6QxiCtHxIF52/dJVy/OJY17Owj4VETMaVBzrRdz7G0Ojr29Q6NirxNkQ9KhwL0R8VCj29IdJKnZ/sLva/JsaRW+cm4KktYl3e91EHA+8FYhUH+OdLP6rYGzIuJvDWuoNQXHXutpjr2dqNP/l81Bzazz8i2UpgJvRsSBkjYj3SKpmX+NynqQY69Z5/VU7PUkPWu68VRmvUFELCLfj1fSo8A1pPvBmtXEsdes83oq9jpBNjProjxD/wHS7PbP+W4VZmb11xOx1wmymVkX5Xtt7g3s0cwTeMzMmklPxF6PQTYzWwGSBkXE641uh5lZX1Lv2OsE2czMzMyswEMszMzMzMwKnCCbmZmZmRU4QTYzMzMzK3CCbGZmZmZW4ATZ+jRJ+0gKSZs2sA1HS1qlUfWbmTWC46/1Zk6Qra87ELgj/9soRwMO0GbW1zj+Wq/lBNn6LEmrATsCU4ADctlOkv4g6RpJT0g6TdJBku6R9KCkjfJ+YyTdKukBSbdIWi+XXyxp30IdrxTOO0vSlZL+LukyJd8A1gVuk3RbDz8FZmYN4fhrvZ0TZOvLJgE3RsQ/gEWSts7lWwBfAT4MHAx8KCK2AS4Avp73+R9gWkR8FLgMOKeG+rYiXa0YB2wI7BAR5wDPADtHxM7d0iszs97P8dd6NSfI1pcdCEzPy9NZ/jXfvRHxbES8ATwO3JTLHwTG5OXtgF/m5UtJV0I6ck9EzIuId4D7C+cyM+trHH+tV+vf6AaYNYKkNYFdgI9ICqAfEMB1wBuFXd8prL9Dx++ZZeQ/PCWtBAwsbCue9+0azmVm1nIcf60Z+Aqy9VX7ApdGxPoRMSYiRgNzgE/UePyd5HFzwEHA7Xn5SaD9q8LPAgNqONfLwJAa6zUza3aOv9brOUG2vupA4KqSst9Q+2zqrwOHSXqANE7uqFz+M+CTkv5K+hrw1RrONRW40ZNEzKyPcPy1Xk8R0eg2mJmZmZn1Gr6CbGZmZmZW4ATZzMzMzKzACbKZmZmZWYETZDMzMzOzAifIZmZmZmYFTpDNzMzMzAqcIJuZmZmZFfx/+rLPugpxBuwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for column in numeric_cols:\n",
    "    plt.figure(figsize=(10, 3))\n",
    "    plt.subplot(1, 2, 1)  # Create a subplot for train data\n",
    "    #plt.hist(train[column])\n",
    "    sns.histplot(train, x=column) \n",
    "    plt.title(f\"Train {column}\")\n",
    "    plt.xlabel(\"Amount\")\n",
    "    plt.ylabel(\"Count\")\n",
    "    plt.xticks(rotation=45)  # Rotate x-labels by 45 degrees\n",
    "    \n",
    "    plt.subplot(1, 2, 2)  # Create a subplot for test data\n",
    "    #plt.hist(test[column])\n",
    "    sns.histplot(test, x=column) \n",
    "    plt.title(f\"Test {column}\")\n",
    "    plt.xlabel(\"Amount\")\n",
    "    plt.ylabel(\"Count\")\n",
    "    plt.xticks(rotation=45)  # Rotate x-labels by 45 degrees\n",
    "    \n",
    "    plt.tight_layout()  # Adjust spacing between subplots\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8505508f",
   "metadata": {},
   "source": [
    "**BOX PLOTS**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8b19bc09",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Tgf0y86421CZJMoslqe1G+5i3lZn5EuAVQD9wA7ABeGNEHNmm+iRpQjOLJan9djsHOTPvzcyrM/P3gLcBbwDuaXVhkqTfMoslqX122yBHxOSIeH1EfB64Cfg58KaWVyZJGmQWS1L7jPYmvdNpHKVYCPwI+CJwUWZua1NtkjThmcWS1H6jvUnvfcAXgEsz8+E21SNJejqzWJLabMQGOTNf1c5CJEnPZBZLUvuN5YtCJEmSpAnDBlmSJEkqsUGWJEmSSmyQJUmSpBIbZEmSJKnEBlmSJEkqsUGWJEmSSmyQJUmSpBIbZEmSJKnEBlmSJEkqsUGWJEmSSiZ3uoBm6+np6XQJmmB8zknj5+tGzeTzSc1WuwZ58eLFnS5BE4zPOWn8fN2omXw+qdmcYiFJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJZM7XYD2zqRfP8T0e9Y3aV/9AE3Z36RfPwQcvNf7kaQq6rZsNpOl8bFBrrCenp6m7m/z5p0AzJ3bjBA9uOn1SVIVdGc2m8nSeNggV9jixYs7XYIkaQizWao+5yBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSVRGa29w4jtgL37uHNDwQebGI5nVa38UD9xlS38UD9xlTV8RyemXM6ded7kcVVfbx3x3FVi+Oqjm4f07BZ3PYGeW9ExG2ZOb/TdTRL3cYD9RtT3cYD9RtT3cbT7er6eDuuanFc1VHVMTnFQpIkSSqxQZYkSZJKqtYgr+50AU1Wt/FA/cZUt/FA/cZUt/F0u7o+3o6rWhxXdVRyTJWagyxJkiS1WtWOIEuSJEktZYMsSZIkldggS6q0iIhO1yBJGl5VM7qrG+SIODoiXhIRUyJiUqfraYaIeH1ELOl0Ha1W1RdEWURM73QNzRQRh0XE1IjYt7je1a//sYiIE4GTOl1H3dUxi2Hi5DHUI5MH1C2boZ75DNXO6K79D4iINwFfA1YA1wN/HhH7dbaqvRMRrwauBDZ2upZmi4gTI+LkiDgBIDOzyoEcEa8BLo6IaZ2upRki4rXATcC1wGci4ujM3FXlEC7+j9YC2ztdS53VMYuh3nkM9cvkAXXLZqhnPkP1M7orH/yImAK8FfjjzDyVRjgfBry3qsEcEScBnwUuysxvRcT+EXF4RMzodG17KyIWAJ8DzgEui4jrobqBXIznI8Ctmbl9yLpKjScaDgM+DFwMvB/4EXBLRDy/qiEcES8DbgD+NDNvj4iZxfLpxb+VG1M3qmMWQ73zGOqXyQPqlM1Q33yGemR0Nxe4H3BkcfmrwDeAKcDbq/hCAPqBHcDvRMRs4B+AvwbWRMRZFR0TxenW84APZuZFxeXnRsSXoXqBHBHHAJ8CPpmZt0TE7OL08rFQvfFk43Mc7wf+Bfg3YEtmfpRGIH8zIo7KzF2drHEPHQd8H+iPiMOB1RFxHbAuIo4sfrFU5v+py9Uti6GmeQz1y+QBdctmqHU+Qw0yuisb5MzcAfwV8KaIeHnxBPke8BPgZZ2sbU9l5s+B1wIfB+4EvgC8DtgAnAkc0Lnq9lxmPgXcUbr+aGa+FDg4Iv6mWFalD9ueTuNU166IOAP4O+CDwF9FxCqozngioqc4vToL2B84Z6D2zFwJrKRxdGlatwfVgGJMxwB/D/wA+FMaIfxDGkcrfgxcGxHPrsr/UzerYxZDffMYapnJA2qTzVDPfIZ6ZXRXNsiF7wLfBN4REa/IzKcy8wvAocALO1vansnMO2mE8Icz89OZuSszb6ARxr/b2erGJyKOKl3dTOOUa3kMbwRmR8Tz21vZnhkYT2beDnweeD7wSeDLwNnAO4HnRcTLO1bkOETE62gE1EeB5TTG9GcR8b7SZl8CfgP8ptuDCp42putozB29lcb80Q9m5jWZ+SMap8030xiXmqN2WQz1ymOoXyYPqFs2Qz3zGeqX0ZM7XcBIMnN7RHweSOB9EfFcGg/owcB/dbS4vZCZGym9KSQizgTmUKExFS+CL0XE1zPz7Mz8XEQcDXw/Il6amb/IzAcjYiewb4fL3a1hxvP9iNgBfCczv1pstiki7qNxWrarFfMr/xJ4e2beERGrgd+n8U7iHxanYL9I4wjgi2kcwXi4Q+WOyTBjug44OzMXR8Q+pU1PBo4AZgBPdqDU2qlrFkM98hjql8kD6pbNUM98hnpmdNd/1XRETAVeCvwJjXdCrszMO0a/VfcrTplcALwHeHNm/muHSxqTaHwEzVdo/JV4ErBPZr6tWHcl8Ac05okdSOMNIq/NzP/sULm7Ncx4pmbm24t10zPzieLymcBfAGdl5r2dqncsiqA6KjPXFNfnAGsy87URcQSwlMZr6UTg/My8u2PFjtEIY7qexv/Hk8WyPwYuoRHQlXg9VUldsxiqm8dQv0weUMdshnrmM9Qzo7u+QR5Q/FWVFZ6w/jRFIJ8MPJCZ93S6nvGIiEOBR4FpNE6l7CgF8huBQ2j85fuJzPxpxwodo2HG85vMPKe0/jwa7zC+oCLjmQTsm5mPFpd/B/hHYGFm/lfxhonNxTa/6mStYzXKmF6dmVuLXywXA6ur9nqqmrplMVQ7j6F+mTygbtkM9cxnqGdGV6ZBVneKxjvAVwNPZubbivltj1fhL/nhlMbzRGb+UUQ8D3glsCEz/6Oz1Y1fREym8cvla5l5akT8EfBy4F0DR2CqZoQxHQtclZmPdrY6qbPqlskD6pbNUM98hvpktA2y9lpEHEhj7tFJwCTglMy8r7NV7bkh4wng5Mys1JzEoSJiDY15la+mQqftRjNkTBdk5l2drUjqDnXL5AF1zGaoZz5D9TO6a9+kp+oo3vxxF7AAOL3qQTzMeCobwMWp4yk0jkpMAU7NzH/rbFV7p45jkpqpbpk8oE7ZDPXNsrqMywZZey0iDgAW0phrVPm/fOs0nuLjgZ4s3qxzaxVDaqg6jklqpjplWFndxlXXLKvLuJxioaaIiGk55Ks/q6yG44ms2Yu9jmOSmqVuGTagjuOqa5ZVfVw2yJIkSVJJN3+TniRJktR2NsiSJElSiQ2yJEmSVGKDLEmSJJXYIKvrRcS3I+I1Q5a9KyL+eoy3/2BEnLabbW6JiPnDLD8/Iq4dX8WSVD9msSYSG2RVwY3A2UOWnV0sH1VETMrMD2TmzS2pTJImDrNYE4YNsqrgy8BrI2IqQETMAw4F3hYRt0XEv0bE8oGNI6IvIq6OiB8Db46INRFxVrHuAxFxa0T8NCJWF9/4M+AdEfGTYt3vDy0iIuZExFeK298aES9t5aAlqcuYxZowbJDV9TLzIeBHNL5eFBpHLL4EXJ6Z84HjgJMj4rjSzfoz80WZ+cUhu7s2M0/IzBcA04HXldbNyMzjgT8DbhimlJXAxzPzBOBM4G/3cmiSVBlmsSYSG2RVRfnU3sApvbcURybuAJ4PHFPa/u9G2M8rI+L/RsTdwKuK25Xvg8z8DrBfRMwactvTgGsj4ifA14ttZu7xiCSpesxiTQiTO12ANEZfAz4eES8CZgAPAe8BTsjMhyNiDTCttP22oTuIiGnAp4D5mbkpIq4YcpuhXys59PqzgP9Rt685laRxMIs1IXgEWZWQmY8D36Zxuu1GYD8awfuriDiY357yG81AAD9YHG04a8j6twJExMuAX2Xmr4as/yaweOBKRBw/zmFIUqWZxZooPIKsKrkR+CpwdmbeExF3APcAm4Dv7+7GmflIRHwa+CnwAHDrkE22F/ucArxzmF1cAnwyIu6i8dr5DrBoTwcjSRVlFqv2InPomQtJkiRp4nKKhSRJklRigyxJkiSV2CBLkiRJJTbIkiRJUokNsiRJklRigyxJkiSV2CBLkiRJJf8fb1F+hccv6jQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for column in numeric_cols:\n",
    "    if train[column].dtype in [int, float]:\n",
    "        plt.figure(figsize=(10, 3))\n",
    "        plt.subplot(1, 2, 1)  # Create a subplot for train data\n",
    "        #plt.boxplot(x=train[column])\n",
    "        sns.boxplot(x=train[column])\n",
    "        plt.title(f\"Train {column}\")\n",
    "        plt.xlabel(\"Variable\")\n",
    "        plt.ylabel(\"Value\")\n",
    "        plt.xticks(rotation=45)  # Rotate x-labels by 45 degrees\n",
    "\n",
    "        plt.subplot(1, 2, 2)  # Create a subplot for test data\n",
    "        #plt.boxplot(test[column])\n",
    "        sns.boxplot(x=test[column])\n",
    "        plt.title(f\"Test {column}\")\n",
    "        plt.xlabel(\"Variable\")\n",
    "        plt.ylabel(\"Value\")\n",
    "        plt.xticks(rotation=45)  # Rotate x-labels by 45 degrees\n",
    "\n",
    "        plt.tight_layout()  # Adjust spacing between subplots\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e04dca8",
   "metadata": {},
   "source": [
    "**TIME FEATURES VIZES**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2aa675e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "train[\"hour\"] = train[\"endTime\"].dt.hour\n",
    "test[\"hour\"] = test[\"endTime\"].dt.hour\n",
    "combined_df[\"hour\"] = combined_df[\"endTime\"].dt.hour"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad2353b3",
   "metadata": {},
   "source": [
    "**VIOLIN PLOTS**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "098589b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'for column in numeric_cols:\\n    if train[column].dtype in [int, float]:\\n        plt.figure(figsize=(10, 3))\\n        plt.subplot(1, 2, 1)  # Create a subplot for train data\\n        #plt.violinplot(train[column].values)\\n        sns.violinplot(x=train[column])\\n        plt.title(f\"Train {column}\")\\n        plt.xlabel(\"Variable\")\\n        plt.ylabel(\"Value\")\\n        plt.xticks(rotation=45)  # Rotate x-labels by 45 degrees\\n\\n        plt.subplot(1, 2, 2)  # Create a subplot for test data\\n        #plt.violinplot(test[column])\\n        sns.violinplot(x=test[column])\\n        plt.title(f\"Test {column}\")\\n        plt.xlabel(\"Variable\")\\n        plt.ylabel(\"Value\")\\n        plt.xticks(rotation=45)  # Rotate x-labels by 45 degrees\\n\\n        plt.tight_layout()  # Adjust spacing between subplots\\n        plt.show()'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"for column in numeric_cols:\n",
    "    if train[column].dtype in [int, float]:\n",
    "        plt.figure(figsize=(10, 3))\n",
    "        plt.subplot(1, 2, 1)  # Create a subplot for train data\n",
    "        #plt.violinplot(train[column].values)\n",
    "        sns.violinplot(x=train[column])\n",
    "        plt.title(f\"Train {column}\")\n",
    "        plt.xlabel(\"Variable\")\n",
    "        plt.ylabel(\"Value\")\n",
    "        plt.xticks(rotation=45)  # Rotate x-labels by 45 degrees\n",
    "\n",
    "        plt.subplot(1, 2, 2)  # Create a subplot for test data\n",
    "        #plt.violinplot(test[column])\n",
    "        sns.violinplot(x=test[column])\n",
    "        plt.title(f\"Test {column}\")\n",
    "        plt.xlabel(\"Variable\")\n",
    "        plt.ylabel(\"Value\")\n",
    "        plt.xticks(rotation=45)  # Rotate x-labels by 45 degrees\n",
    "\n",
    "        plt.tight_layout()  # Adjust spacing between subplots\n",
    "        plt.show()\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5f0a6558",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming you have a DataFrame named 'data' with columns 'hour' and 'data_rate'\n",
    "hourly_mean = train.groupby(\"hour\")[\"data_rate\"].mean()\n",
    "\n",
    "plt.figure(figsize=(12, 4))\n",
    "sns.barplot(x=hourly_mean.index, y=hourly_mean.values)\n",
    "plt.xlabel(\"Hour\")\n",
    "plt.ylabel(\"Average Data Rate\")\n",
    "plt.title(\"Average Data Rate by Hour\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "03726503",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming you have a DataFrame named 'data' with columns 'hour' and 'data_rate'\n",
    "hourly_mean = test.groupby(\"hour\")[\"data_rate\"].mean()\n",
    "\n",
    "plt.figure(figsize=(12, 4))\n",
    "sns.barplot(x=hourly_mean.index, y=hourly_mean.values)\n",
    "plt.xlabel(\"Hour\")\n",
    "plt.ylabel(\"Average Data Rate\")\n",
    "plt.title(\"Average Data Rate by Hour\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "13786cea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate the percentage distribution of values in the 'hour' column for combined_df and test\n",
    "train_hour_percentage = (combined_df['hour'].value_counts() / len(combined_df)) * 100\n",
    "test_hour_percentage = (test['hour'].value_counts() / len(test)) * 100\n",
    "\n",
    "# Set up the figure with subplots\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
    "\n",
    "# Plot combined_df data on the left subplot\n",
    "sns.barplot(x=train_hour_percentage.index, y=train_hour_percentage.values, ax=axes[0], color='blue', alpha=0.4)\n",
    "axes[0].set_xlabel('Hour')\n",
    "axes[0].set_ylabel('Percentage (%)')\n",
    "axes[0].set_title('Percentage Distribution of Hours (Train)')\n",
    "axes[0].set_xticklabels(axes[0].get_xticklabels(), rotation=0)\n",
    "\n",
    "# Plot test data on the right subdata_rate_t+1_trendplot\n",
    "sns.barplot(x=test_hour_percentage.index, y=test_hour_percentage.values, ax=axes[1], color='red', alpha=0.4)\n",
    "axes[1].set_xlabel('Hour')\n",
    "axes[1].set_ylabel('Percentage (%)')\n",
    "axes[1].set_title('Percentage Distribution of Hours (Test)')\n",
    "axes[1].set_xticklabels(axes[1].get_xticklabels(), rotation=0)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "916c0e77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Group by \"hour\" and \"data_rate_t+1_trend\", then count occurrences\n",
    "count_df = combined_df.groupby([\"hour\", \"data_rate_t+1_trend\"]).size().reset_index(name=\"count\")\n",
    "\n",
    "# Pivot the table to make a categorical plot\n",
    "pivot_df = count_df.pivot(index=\"hour\", columns=\"data_rate_t+1_trend\", values=\"count\").fillna(0)\n",
    "\n",
    "# Create a stacked bar plot\n",
    "pivot_df.plot(kind=\"bar\", stacked=True, figsize=(10, 6))\n",
    "\n",
    "# Adding labels and title\n",
    "plt.xlabel(\"Hour\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.title(\"Count of data_rate_t+1_trend by Hour\")\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd0cc421",
   "metadata": {},
   "source": [
    "**CORRELATION MATRIX**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bd9df366",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\julmn\\AppData\\Local\\Temp\\ipykernel_7344\\3750398325.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  sns.heatmap(test.corr(), annot=True, cmap='coolwarm', center=0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.heatmap(test.corr(), annot=True, cmap='coolwarm', center=0)\n",
    "plt.title('Correlation Matrix Heatmap')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "12414668",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\julmn\\AppData\\Local\\Temp\\ipykernel_7344\\3856160855.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  sns.heatmap(train.corr(), annot=True, cmap='coolwarm', center=0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "sns.heatmap(train.corr(), annot=True, cmap='coolwarm', center=0)\n",
    "plt.title('Correlation Matrix Heatmap')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f79b64b",
   "metadata": {},
   "source": [
    "**HISTOGRAMS**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ce7581fe",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test.hist(bins=50, figsize=(12, 8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "588cb40a",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test.hist(bins=50, figsize=(12, 8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b92d41ea",
   "metadata": {},
   "source": [
    "**PAIR PLOTS**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a3318661",
   "metadata": {},
   "outputs": [],
   "source": [
    "#sns.pairplot(test, vars=test.columns.tolist()) #['Year of manufacture', 'Mileage', 'Engine Size']\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "42b49cb2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#sns.pairplot(train, vars=train.columns.tolist()) #['Year of manufacture', 'Mileage', 'Engine Size']\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "958e69dc",
   "metadata": {},
   "source": [
    "**OVERALL VISUALISATION USING PANDAS PROFILING**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "67d322a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#profile = pandas_profiling.ProfileReport(combined_df)\n",
    "# Save the report to an HTML file\n",
    "#profile.to_file(\"combined_df_report2.html\")\n",
    "#profile"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}