Reading data from multiple Datasets- EDA and Data pre-processing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "t1 = pd.read_csv(\"C:/Users/Arkaprabha_B/Desktop/train1.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Employee Number</th>\n",
       "      <th>Employee Name</th>\n",
       "      <th>Employee Department</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
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       "      <td>HR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XYZ</td>\n",
       "      <td>Finance</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "   Employee Number Employee Name Employee Department\n",
       "0             1001           ABC                  HR\n",
       "1             1002           XYZ             Finance"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "t2 = pd.read_csv(\"C:/Users/Arkaprabha_B/Desktop/train2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Employee Job Level</th>\n",
       "      <th>Employee Salary</th>\n",
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       "      <td>80000</td>\n",
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       "      <td>125000</td>\n",
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      "text/plain": [
       "   Employee Job Level  Employee Salary\n",
       "0                   1            50000\n",
       "1                   2            80000\n",
       "2                   3           125000"
      ]
     },
     "execution_count": 45,
     "metadata": {},
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   ],
   "source": [
    "t2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "t3 = pd.read_csv(\"C:/Users/Arkaprabha_B/Desktop/train3.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
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     "data": {
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       "      <th>Employee Id</th>\n",
       "      <th>Employee Job Level</th>\n",
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       "      <td>1001</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
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      "text/plain": [
       "   Employee Id   Employee Job Level\n",
       "0          1001                   1\n",
       "1          1002                   1\n",
       "2          1003                   1\n",
       "3          1004                   3\n",
       "4          1005                   2"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "t1.rename(columns = {'Employee Number':'Empid'}, inplace = True) \n",
    "t3.rename(columns = {'Employee Id ':'Empid'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Empid', 'Employee Name', 'Employee Department'], dtype='object')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Empid', 'Employee Job Level'], dtype='object')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t3.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs = [t1,t3]\n",
    "from functools import reduce\n",
    "df_final2 = reduce(lambda left,right: pd.merge(left,right,on='Empid'), dfs)\n",
    "EmpID = df_final2['Empid']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Empid</th>\n",
       "      <th>Employee Name</th>\n",
       "      <th>Employee Department</th>\n",
       "      <th>Employee Job Level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>1001</td>\n",
       "      <td>ABC</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XYZ</td>\n",
       "      <td>Finance</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>PQR</td>\n",
       "      <td>HR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>Ramesh</td>\n",
       "      <td>Sales</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>Suresh</td>\n",
       "      <td>Finance</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
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       "      <td>DEF</td>\n",
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      "text/plain": [
       "   Empid Employee Name Employee Department  Employee Job Level\n",
       "0   1001           ABC                  HR                   1\n",
       "1   1002           XYZ             Finance                   1\n",
       "2   1003           PQR                  HR                   1\n",
       "3   1004        Ramesh               Sales                   3\n",
       "4   1005        Suresh             Finance                   2\n",
       "5   1006           DEF                  HR                   2"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "t2.rename(columns = {'Employee Job Level':'JL'}, inplace = True)\n",
    "df_final2.rename(columns = {'Employee Job Level':'JL'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['JL', 'Employee Salary'], dtype='object')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Empid', 'Employee Name', 'Employee Department', 'JL'], dtype='object')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = [df_final2,t2]\n",
    "from functools import reduce\n",
    "df_final = reduce(lambda left,right: pd.merge(left,right,on='JL'), df3)\n",
    "EmpID = df_final['JL']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Empid</th>\n",
       "      <th>Employee Name</th>\n",
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       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>ABC</td>\n",
       "      <td>HR</td>\n",
       "      <td>1</td>\n",
       "      <td>50000</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>XYZ</td>\n",
       "      <td>Finance</td>\n",
       "      <td>1</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>PQR</td>\n",
       "      <td>HR</td>\n",
       "      <td>1</td>\n",
       "      <td>50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>Ramesh</td>\n",
       "      <td>Sales</td>\n",
       "      <td>3</td>\n",
       "      <td>125000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>Suresh</td>\n",
       "      <td>Finance</td>\n",
       "      <td>2</td>\n",
       "      <td>80000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>DEF</td>\n",
       "      <td>HR</td>\n",
       "      <td>2</td>\n",
       "      <td>80000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Empid Employee Name Employee Department  JL  Employee Salary\n",
       "0   1001           ABC                  HR   1            50000\n",
       "1   1002           XYZ             Finance   1            50000\n",
       "2   1003           PQR                  HR   1            50000\n",
       "3   1004        Ramesh               Sales   3           125000\n",
       "4   1005        Suresh             Finance   2            80000\n",
       "5   1006           DEF                  HR   2            80000"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_final"
   ]
  }
 ],
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