Innovision.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bab09872-4c41-4cdc-9b5a-203cb79b489a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from math import sqrt\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.svm import SVR\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c759006e-9bb9-43b6-8b82-b2f9d7f6bfcd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Taking dataset as input\n",
    "input_file = pd.read_csv(\"D:\\Downloads\\engineering colleges in India (1).csv\", low_memory=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e4dbc99f-015d-4da5-9266-6c05878df5aa",
   "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>College Name</th>\n",
       "      <th>Genders Accepted</th>\n",
       "      <th>Campus Size</th>\n",
       "      <th>Total Student Enrollments</th>\n",
       "      <th>Total Faculty</th>\n",
       "      <th>Established Year</th>\n",
       "      <th>Rating</th>\n",
       "      <th>University</th>\n",
       "      <th>Courses</th>\n",
       "      <th>Facilities</th>\n",
       "      <th>...</th>\n",
       "      <th>Unnamed: 210</th>\n",
       "      <th>Unnamed: 211</th>\n",
       "      <th>Unnamed: 212</th>\n",
       "      <th>Unnamed: 213</th>\n",
       "      <th>Unnamed: 214</th>\n",
       "      <th>Unnamed: 215</th>\n",
       "      <th>Unnamed: 216</th>\n",
       "      <th>Unnamed: 217</th>\n",
       "      <th>Unnamed: 218</th>\n",
       "      <th>Unnamed: 219</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>National Institute of Technology Rourkela</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>647 Acres</td>\n",
       "      <td>4811</td>\n",
       "      <td>329</td>\n",
       "      <td>2007</td>\n",
       "      <td>3.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Mechanical Engineering, B.Tech Computer...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Visvesvaraya National Institute of Technology ...</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>215 Acres</td>\n",
       "      <td>1071</td>\n",
       "      <td>192</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Netaji Subhas University of Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>145 Acres</td>\n",
       "      <td>3759</td>\n",
       "      <td>101</td>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Engineering, B.Tech Electronic...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Birla Institute of Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>980 Acres</td>\n",
       "      <td>4506</td>\n",
       "      <td>284</td>\n",
       "      <td>1955</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>International Institute of Information Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>66 Acres</td>\n",
       "      <td>1721</td>\n",
       "      <td>85</td>\n",
       "      <td>2001</td>\n",
       "      <td>3.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science and Engineering, M.Tec...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 220 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        College Name Genders Accepted  \\\n",
       "0         National Institute of Technology Rourkela             Co-Ed   \n",
       "1  Visvesvaraya National Institute of Technology ...            Co-Ed   \n",
       "2             Netaji Subhas University of Technology            Co-Ed   \n",
       "3                      Birla Institute of Technology            Co-Ed   \n",
       "4  International Institute of Information Technology            Co-Ed   \n",
       "\n",
       "  Campus Size Total Student Enrollments Total Faculty Established Year Rating  \\\n",
       "0   647 Acres                      4811           329             2007   3.12   \n",
       "1   215 Acres                      1071           192             2007    NaN   \n",
       "2   145 Acres                      3759           101             2018    NaN   \n",
       "3   980 Acres                      4506           284             1955    NaN   \n",
       "4    66 Acres                      1721            85             2001   3.05   \n",
       "\n",
       "  University                                            Courses  \\\n",
       "0        NaN  B.Tech Mechanical Engineering, B.Tech Computer...   \n",
       "1        NaN  B.Tech Computer Science Engineering, B.Tech El...   \n",
       "2        NaN  B.Tech Computer Engineering, B.Tech Electronic...   \n",
       "3        NaN  B.Tech Computer Science Engineering, B.Tech El...   \n",
       "4        NaN  B.Tech Computer Science and Engineering, M.Tec...   \n",
       "\n",
       "                                          Facilities  ... Unnamed: 210  \\\n",
       "0  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "1  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "2  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "3  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "4  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "\n",
       "  Unnamed: 211 Unnamed: 212 Unnamed: 213 Unnamed: 214 Unnamed: 215  \\\n",
       "0          NaN          NaN          NaN          NaN          NaN   \n",
       "1          NaN          NaN          NaN          NaN          NaN   \n",
       "2          NaN          NaN          NaN          NaN          NaN   \n",
       "3          NaN          NaN          NaN          NaN          NaN   \n",
       "4          NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "  Unnamed: 216 Unnamed: 217 Unnamed: 218 Unnamed: 219  \n",
       "0          NaN          NaN          NaN          NaN  \n",
       "1          NaN          NaN          NaN          NaN  \n",
       "2          NaN          NaN          NaN          NaN  \n",
       "3          NaN          NaN          NaN          NaN  \n",
       "4          NaN          NaN          NaN          NaN  \n",
       "\n",
       "[5 rows x 220 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_file.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0192d325-ab61-4edc-b6f1-6e0e83406cca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5447 entries, 0 to 5446\n",
      "Columns: 220 entries, College Name to Unnamed: 219\n",
      "dtypes: float64(1), object(219)\n",
      "memory usage: 9.1+ MB\n"
     ]
    }
   ],
   "source": [
    "input_file.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8742a222-5e78-4ec6-9be7-84695a639973",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating a new column called student_to_faculty_ratio\n",
    "students=\"Total Student Enrollments\"\n",
    "teachers=\"Total Faculty\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3b034640-a9b0-4653-81f4-72046759fdbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_file[students] = pd.to_numeric(input_file[students], errors='coerce')\n",
    "input_file[teachers] = pd.to_numeric(input_file[teachers], errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "09e0d5ec-d569-4d8a-b6cf-6425ddaf94f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_file[\"student_to_faculty_ratio\"]=input_file[students]/input_file[teachers]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "30177490-71d7-4cfa-9f3f-0ea00656fc38",
   "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>College Name</th>\n",
       "      <th>Genders Accepted</th>\n",
       "      <th>Campus Size</th>\n",
       "      <th>Total Student Enrollments</th>\n",
       "      <th>Total Faculty</th>\n",
       "      <th>Established Year</th>\n",
       "      <th>Rating</th>\n",
       "      <th>University</th>\n",
       "      <th>Courses</th>\n",
       "      <th>Facilities</th>\n",
       "      <th>...</th>\n",
       "      <th>Unnamed: 211</th>\n",
       "      <th>Unnamed: 212</th>\n",
       "      <th>Unnamed: 213</th>\n",
       "      <th>Unnamed: 214</th>\n",
       "      <th>Unnamed: 215</th>\n",
       "      <th>Unnamed: 216</th>\n",
       "      <th>Unnamed: 217</th>\n",
       "      <th>Unnamed: 218</th>\n",
       "      <th>Unnamed: 219</th>\n",
       "      <th>student_to_faculty_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>National Institute of Technology Rourkela</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>647 Acres</td>\n",
       "      <td>4811.0</td>\n",
       "      <td>329.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>3.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Mechanical Engineering, B.Tech Computer...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.623100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Visvesvaraya National Institute of Technology ...</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>215 Acres</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.578125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Netaji Subhas University of Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>145 Acres</td>\n",
       "      <td>3759.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Engineering, B.Tech Electronic...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.217822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Birla Institute of Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>980 Acres</td>\n",
       "      <td>4506.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>1955</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.866197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>International Institute of Information Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>66 Acres</td>\n",
       "      <td>1721.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>2001</td>\n",
       "      <td>3.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science and Engineering, M.Tec...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.247059</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 221 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        College Name Genders Accepted  \\\n",
       "0         National Institute of Technology Rourkela             Co-Ed   \n",
       "1  Visvesvaraya National Institute of Technology ...            Co-Ed   \n",
       "2             Netaji Subhas University of Technology            Co-Ed   \n",
       "3                      Birla Institute of Technology            Co-Ed   \n",
       "4  International Institute of Information Technology            Co-Ed   \n",
       "\n",
       "  Campus Size  Total Student Enrollments  Total Faculty Established Year  \\\n",
       "0   647 Acres                     4811.0          329.0             2007   \n",
       "1   215 Acres                     1071.0          192.0             2007   \n",
       "2   145 Acres                     3759.0          101.0             2018   \n",
       "3   980 Acres                     4506.0          284.0             1955   \n",
       "4    66 Acres                     1721.0           85.0             2001   \n",
       "\n",
       "  Rating University                                            Courses  \\\n",
       "0   3.12        NaN  B.Tech Mechanical Engineering, B.Tech Computer...   \n",
       "1    NaN        NaN  B.Tech Computer Science Engineering, B.Tech El...   \n",
       "2    NaN        NaN  B.Tech Computer Engineering, B.Tech Electronic...   \n",
       "3    NaN        NaN  B.Tech Computer Science Engineering, B.Tech El...   \n",
       "4   3.05        NaN  B.Tech Computer Science and Engineering, M.Tec...   \n",
       "\n",
       "                                          Facilities  ... Unnamed: 211  \\\n",
       "0  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "1  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "2  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "3  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "4  Boys Hostel, Girls Hostel, Gym, Library, Sport...  ...          NaN   \n",
       "\n",
       "  Unnamed: 212 Unnamed: 213 Unnamed: 214 Unnamed: 215 Unnamed: 216  \\\n",
       "0          NaN          NaN          NaN          NaN          NaN   \n",
       "1          NaN          NaN          NaN          NaN          NaN   \n",
       "2          NaN          NaN          NaN          NaN          NaN   \n",
       "3          NaN          NaN          NaN          NaN          NaN   \n",
       "4          NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "  Unnamed: 217 Unnamed: 218 Unnamed: 219 student_to_faculty_ratio  \n",
       "0          NaN          NaN          NaN                14.623100  \n",
       "1          NaN          NaN          NaN                 5.578125  \n",
       "2          NaN          NaN          NaN                37.217822  \n",
       "3          NaN          NaN          NaN                15.866197  \n",
       "4          NaN          NaN          NaN                20.247059  \n",
       "\n",
       "[5 rows x 221 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_file.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0a9790a4-b72a-47f9-9dd2-6a206866ca6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       14.623100\n",
       "1        5.578125\n",
       "2       37.217822\n",
       "3       15.866197\n",
       "4       20.247059\n",
       "          ...    \n",
       "5442          NaN\n",
       "5443          NaN\n",
       "5444     0.400000\n",
       "5445     3.800000\n",
       "5446          NaN\n",
       "Name: student_to_faculty_ratio, Length: 5447, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_file[\"student_to_faculty_ratio\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5eb62a2a-2fc2-49fe-961d-30dca70815de",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5447 entries, 0 to 5446\n",
      "Columns: 221 entries, College Name to student_to_faculty_ratio\n",
      "dtypes: float64(4), object(217)\n",
      "memory usage: 9.2+ MB\n"
     ]
    }
   ],
   "source": [
    "input_file.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ba67adca-b5a4-45ab-b73a-41a5e1b14e0e",
   "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>Total Student Enrollments</th>\n",
       "      <th>Total Faculty</th>\n",
       "      <th>Unnamed: 219</th>\n",
       "      <th>student_to_faculty_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4.437000e+03</td>\n",
       "      <td>5279.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4378.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.915446e+03</td>\n",
       "      <td>96.739345</td>\n",
       "      <td>731392.857143</td>\n",
       "      <td>25.356753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.841858e+04</td>\n",
       "      <td>113.869962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>290.661584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>731392.857143</td>\n",
       "      <td>0.024390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.090000e+02</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>731392.857143</td>\n",
       "      <td>7.402890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.120000e+02</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>731392.857143</td>\n",
       "      <td>12.730797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.551000e+03</td>\n",
       "      <td>124.000000</td>\n",
       "      <td>731392.857143</td>\n",
       "      <td>19.547078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.035081e+06</td>\n",
       "      <td>2453.000000</td>\n",
       "      <td>731392.857143</td>\n",
       "      <td>18532.387097</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Total Student Enrollments  Total Faculty   Unnamed: 219  \\\n",
       "count               4.437000e+03    5279.000000       1.000000   \n",
       "mean                1.915446e+03      96.739345  731392.857143   \n",
       "std                 1.841858e+04     113.869962            NaN   \n",
       "min                 1.000000e+00       1.000000  731392.857143   \n",
       "25%                 4.090000e+02      37.000000  731392.857143   \n",
       "50%                 8.120000e+02      69.000000  731392.857143   \n",
       "75%                 1.551000e+03     124.000000  731392.857143   \n",
       "max                 1.035081e+06    2453.000000  731392.857143   \n",
       "\n",
       "       student_to_faculty_ratio  \n",
       "count               4378.000000  \n",
       "mean                  25.356753  \n",
       "std                  290.661584  \n",
       "min                    0.024390  \n",
       "25%                    7.402890  \n",
       "50%                   12.730797  \n",
       "75%                   19.547078  \n",
       "max                18532.387097  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_file.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ade33f05-21cd-4e2b-8e97-a167feaae759",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check the columns that contain 'Unnamed'\n",
    "cols_to_drop = input_file.columns[input_file.columns.str.contains('^Unnamed')]\n",
    "\n",
    "# Drop the columns from the DataFrame\n",
    "input_file.drop(columns=cols_to_drop, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "68d929bc-7392-4f37-835d-ec76f77f9e82",
   "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>College Name</th>\n",
       "      <th>Genders Accepted</th>\n",
       "      <th>Campus Size</th>\n",
       "      <th>Total Student Enrollments</th>\n",
       "      <th>Total Faculty</th>\n",
       "      <th>Established Year</th>\n",
       "      <th>Rating</th>\n",
       "      <th>University</th>\n",
       "      <th>Courses</th>\n",
       "      <th>Facilities</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>College Type</th>\n",
       "      <th>Average Fees</th>\n",
       "      <th>student_to_faculty_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>National Institute of Technology Rourkela</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>647 Acres</td>\n",
       "      <td>4811.0</td>\n",
       "      <td>329.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>3.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Mechanical Engineering, B.Tech Computer...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Rourkela</td>\n",
       "      <td>Odisha</td>\n",
       "      <td>India</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>350600</td>\n",
       "      <td>14.623100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Visvesvaraya National Institute of Technology ...</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>215 Acres</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Nagpur</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>India</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>273596.666666666</td>\n",
       "      <td>5.578125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Netaji Subhas University of Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>145 Acres</td>\n",
       "      <td>3759.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Engineering, B.Tech Electronic...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>India</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>352320</td>\n",
       "      <td>37.217822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Birla Institute of Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>980 Acres</td>\n",
       "      <td>4506.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>1955</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Ranchi</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>596686.046511627</td>\n",
       "      <td>15.866197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>International Institute of Information Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>66 Acres</td>\n",
       "      <td>1721.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>2001</td>\n",
       "      <td>3.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science and Engineering, M.Tec...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Telangana</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>756666.666666666</td>\n",
       "      <td>20.247059</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        College Name Genders Accepted  \\\n",
       "0         National Institute of Technology Rourkela             Co-Ed   \n",
       "1  Visvesvaraya National Institute of Technology ...            Co-Ed   \n",
       "2             Netaji Subhas University of Technology            Co-Ed   \n",
       "3                      Birla Institute of Technology            Co-Ed   \n",
       "4  International Institute of Information Technology            Co-Ed   \n",
       "\n",
       "  Campus Size  Total Student Enrollments  Total Faculty Established Year  \\\n",
       "0   647 Acres                     4811.0          329.0             2007   \n",
       "1   215 Acres                     1071.0          192.0             2007   \n",
       "2   145 Acres                     3759.0          101.0             2018   \n",
       "3   980 Acres                     4506.0          284.0             1955   \n",
       "4    66 Acres                     1721.0           85.0             2001   \n",
       "\n",
       "  Rating University                                            Courses  \\\n",
       "0   3.12        NaN  B.Tech Mechanical Engineering, B.Tech Computer...   \n",
       "1    NaN        NaN  B.Tech Computer Science Engineering, B.Tech El...   \n",
       "2    NaN        NaN  B.Tech Computer Engineering, B.Tech Electronic...   \n",
       "3    NaN        NaN  B.Tech Computer Science Engineering, B.Tech El...   \n",
       "4   3.05        NaN  B.Tech Computer Science and Engineering, M.Tec...   \n",
       "\n",
       "                                          Facilities       City        State  \\\n",
       "0  Boys Hostel, Girls Hostel, Gym, Library, Sport...   Rourkela       Odisha   \n",
       "1  Boys Hostel, Girls Hostel, Gym, Library, Sport...     Nagpur  Maharashtra   \n",
       "2  Boys Hostel, Girls Hostel, Gym, Library, Sport...  New Delhi        Delhi   \n",
       "3  Boys Hostel, Girls Hostel, Gym, Library, Sport...     Ranchi    Jharkhand   \n",
       "4  Boys Hostel, Girls Hostel, Gym, Library, Sport...  Hyderabad    Telangana   \n",
       "\n",
       "  Country       College Type      Average Fees  student_to_faculty_ratio  \n",
       "0   India  Public/Government            350600                 14.623100  \n",
       "1   India  Public/Government  273596.666666666                  5.578125  \n",
       "2   India  Public/Government            352320                 37.217822  \n",
       "3   India            Private  596686.046511627                 15.866197  \n",
       "4   India            Private  756666.666666666                 20.247059  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_file.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5bd8928e-fdaa-43cc-be63-7ce50bedb47d",
   "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>Total Student Enrollments</th>\n",
       "      <th>Total Faculty</th>\n",
       "      <th>student_to_faculty_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4.437000e+03</td>\n",
       "      <td>5279.000000</td>\n",
       "      <td>4378.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.915446e+03</td>\n",
       "      <td>96.739345</td>\n",
       "      <td>25.356753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.841858e+04</td>\n",
       "      <td>113.869962</td>\n",
       "      <td>290.661584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.024390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.090000e+02</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>7.402890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.120000e+02</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>12.730797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.551000e+03</td>\n",
       "      <td>124.000000</td>\n",
       "      <td>19.547078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.035081e+06</td>\n",
       "      <td>2453.000000</td>\n",
       "      <td>18532.387097</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Total Student Enrollments  Total Faculty  student_to_faculty_ratio\n",
       "count               4.437000e+03    5279.000000               4378.000000\n",
       "mean                1.915446e+03      96.739345                 25.356753\n",
       "std                 1.841858e+04     113.869962                290.661584\n",
       "min                 1.000000e+00       1.000000                  0.024390\n",
       "25%                 4.090000e+02      37.000000                  7.402890\n",
       "50%                 8.120000e+02      69.000000                 12.730797\n",
       "75%                 1.551000e+03     124.000000                 19.547078\n",
       "max                 1.035081e+06    2453.000000              18532.387097"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_file.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4d0d9b42-5c6b-42ad-b5b2-39db4f741be8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5447 entries, 0 to 5446\n",
      "Data columns (total 16 columns):\n",
      " #   Column                     Non-Null Count  Dtype  \n",
      "---  ------                     --------------  -----  \n",
      " 0   College Name               5447 non-null   object \n",
      " 1   Genders Accepted           5429 non-null   object \n",
      " 2   Campus Size                2696 non-null   object \n",
      " 3   Total Student Enrollments  4437 non-null   float64\n",
      " 4   Total Faculty              5279 non-null   float64\n",
      " 5   Established Year           5346 non-null   object \n",
      " 6   Rating                     334 non-null    object \n",
      " 7   University                 3511 non-null   object \n",
      " 8   Courses                    5447 non-null   object \n",
      " 9   Facilities                 5434 non-null   object \n",
      " 10  City                       5446 non-null   object \n",
      " 11  State                      5446 non-null   object \n",
      " 12  Country                    5446 non-null   object \n",
      " 13  College Type               5445 non-null   object \n",
      " 14  Average Fees               5446 non-null   object \n",
      " 15  student_to_faculty_ratio   4378 non-null   float64\n",
      "dtypes: float64(3), object(13)\n",
      "memory usage: 681.0+ KB\n"
     ]
    }
   ],
   "source": [
    "input_file.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "918c8b54-83ca-4d65-b8c4-f8c142fa0ba2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating a copy of the input_file dataset with necessary features \n",
    "features=[\"College Name\",\"student_to_faculty_ratio\",\"University\",\"Facilities\",\"City\",\"College Type\",\"Rating\"]\n",
    "data_set=input_file[features].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "032266f7-cabe-46b7-836a-f95f75e33bdc",
   "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>College Name</th>\n",
       "      <th>student_to_faculty_ratio</th>\n",
       "      <th>University</th>\n",
       "      <th>Facilities</th>\n",
       "      <th>City</th>\n",
       "      <th>College Type</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>National Institute of Technology Rourkela</td>\n",
       "      <td>14.623100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Rourkela</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>3.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Visvesvaraya National Institute of Technology ...</td>\n",
       "      <td>5.578125</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Nagpur</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Netaji Subhas University of Technology</td>\n",
       "      <td>37.217822</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Birla Institute of Technology</td>\n",
       "      <td>15.866197</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Ranchi</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>International Institute of Information Technology</td>\n",
       "      <td>20.247059</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Private</td>\n",
       "      <td>3.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        College Name  \\\n",
       "0         National Institute of Technology Rourkela    \n",
       "1  Visvesvaraya National Institute of Technology ...   \n",
       "2             Netaji Subhas University of Technology   \n",
       "3                      Birla Institute of Technology   \n",
       "4  International Institute of Information Technology   \n",
       "\n",
       "   student_to_faculty_ratio University  \\\n",
       "0                 14.623100        NaN   \n",
       "1                  5.578125        NaN   \n",
       "2                 37.217822        NaN   \n",
       "3                 15.866197        NaN   \n",
       "4                 20.247059        NaN   \n",
       "\n",
       "                                          Facilities       City  \\\n",
       "0  Boys Hostel, Girls Hostel, Gym, Library, Sport...   Rourkela   \n",
       "1  Boys Hostel, Girls Hostel, Gym, Library, Sport...     Nagpur   \n",
       "2  Boys Hostel, Girls Hostel, Gym, Library, Sport...  New Delhi   \n",
       "3  Boys Hostel, Girls Hostel, Gym, Library, Sport...     Ranchi   \n",
       "4  Boys Hostel, Girls Hostel, Gym, Library, Sport...  Hyderabad   \n",
       "\n",
       "        College Type Rating  \n",
       "0  Public/Government   3.12  \n",
       "1  Public/Government    NaN  \n",
       "2  Public/Government    NaN  \n",
       "3            Private    NaN  \n",
       "4            Private   3.05  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5a00648f-a671-4c8b-90ea-0e482280917a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5447 entries, 0 to 5446\n",
      "Data columns (total 7 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   College Name              5447 non-null   object \n",
      " 1   student_to_faculty_ratio  4378 non-null   float64\n",
      " 2   University                3511 non-null   object \n",
      " 3   Facilities                5434 non-null   object \n",
      " 4   City                      5446 non-null   object \n",
      " 5   College Type              5445 non-null   object \n",
      " 6   Rating                    334 non-null    object \n",
      "dtypes: float64(1), object(6)\n",
      "memory usage: 298.0+ KB\n"
     ]
    }
   ],
   "source": [
    "data_set.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ccf7cca0-23d5-41c7-b639-8b83bd293d75",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>Facilities</th>\n",
       "      <th>City</th>\n",
       "      <th>College Type</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14.623100</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Rourkela</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>3.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Nagpur</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.217822</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.866197</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Ranchi</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.247059</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>Private</td>\n",
       "      <td>3.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   student_to_faculty_ratio  \\\n",
       "0                 14.623100   \n",
       "1                  5.578125   \n",
       "2                 37.217822   \n",
       "3                 15.866197   \n",
       "4                 20.247059   \n",
       "\n",
       "                                          Facilities       City  \\\n",
       "0  Boys Hostel, Girls Hostel, Gym, Library, Sport...   Rourkela   \n",
       "1  Boys Hostel, Girls Hostel, Gym, Library, Sport...     Nagpur   \n",
       "2  Boys Hostel, Girls Hostel, Gym, Library, Sport...  New Delhi   \n",
       "3  Boys Hostel, Girls Hostel, Gym, Library, Sport...     Ranchi   \n",
       "4  Boys Hostel, Girls Hostel, Gym, Library, Sport...  Hyderabad   \n",
       "\n",
       "        College Type Rating  \n",
       "0  Public/Government   3.12  \n",
       "1  Public/Government    NaN  \n",
       "2  Public/Government    NaN  \n",
       "3            Private    NaN  \n",
       "4            Private   3.05  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Dropping the unnecessary columns\n",
    "feature_drop=[\"University\",\"College Name\"]\n",
    "data_set.drop(columns=[\"University\"], inplace=True)\n",
    "data_set.drop(columns=[\"College Name\"], inplace=True)\n",
    "data_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1bfe7d8b-55dd-4b82-81a6-0a52dc54c707",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Encoding the categorical column - College Type\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "one_hot_encoded = pd.get_dummies(data_set, columns=['College Type'])\n",
    "\n",
    "# Label Encoding\n",
    "dataset = data_set.copy()  # Make a copy of the DataFrame\n",
    "label_encoder = LabelEncoder()\n",
    "dataset['College Type'] = label_encoder.fit_transform(dataset['College Type'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "1db16382-8a5f-41e2-8b29-4b39972c15f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create a separate train dataset that contains the rows in which rating is present\n",
    "dataset = dataset.dropna(subset=['Rating'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "b4a8e666-d403-4fc9-95aa-c9d3ea26317e",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>Facilities</th>\n",
       "      <th>City</th>\n",
       "      <th>College Type</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14.623100</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Rourkela</td>\n",
       "      <td>3</td>\n",
       "      <td>3.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.247059</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2</td>\n",
       "      <td>3.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>18.825503</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Bengaluru</td>\n",
       "      <td>2</td>\n",
       "      <td>3.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>15.112069</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>3</td>\n",
       "      <td>3.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>17.071472</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Varanasi</td>\n",
       "      <td>3</td>\n",
       "      <td>3.41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   student_to_faculty_ratio  \\\n",
       "0                 14.623100   \n",
       "4                 20.247059   \n",
       "5                 18.825503   \n",
       "6                 15.112069   \n",
       "7                 17.071472   \n",
       "\n",
       "                                          Facilities       City  College Type  \\\n",
       "0  Boys Hostel, Girls Hostel, Gym, Library, Sport...   Rourkela             3   \n",
       "4  Boys Hostel, Girls Hostel, Gym, Library, Sport...  Hyderabad             2   \n",
       "5  Boys Hostel, Girls Hostel, Gym, Library, Sport...  Bengaluru             2   \n",
       "6  Boys Hostel, Girls Hostel, Gym, Library, Sport...     Mumbai             3   \n",
       "7  Boys Hostel, Girls Hostel, Gym, Library, Sport...   Varanasi             3   \n",
       "\n",
       "  Rating  \n",
       "0   3.12  \n",
       "4   3.05  \n",
       "5   3.83  \n",
       "6   3.77  \n",
       "7   3.41  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "4ebba57c-fb24-4299-8480-aa6556468785",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 334 entries, 0 to 4791\n",
      "Data columns (total 3 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   student_to_faculty_ratio  320 non-null    float64\n",
      " 1   College Type              334 non-null    int32  \n",
      " 2   Rating                    334 non-null    object \n",
      "dtypes: float64(1), int32(1), object(1)\n",
      "memory usage: 9.1+ KB\n"
     ]
    }
   ],
   "source": [
    "# Make a copy of the dataset\n",
    "dataset_t = dataset.copy()\n",
    "# Drop unnecessary columns\n",
    "dataset_t=dataset_t.drop(columns=['Facilities','City'])\n",
    "# Drop rows with missing values in the 'rating' column\n",
    "dataset_t.dropna(subset=['Rating'])\n",
    "dataset_t.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "9fef7158-480f-44bd-9515-0008776f67cc",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>College Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14.623100</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.247059</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>18.825503</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>15.112069</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>17.071472</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2871</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3623</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4278</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4495</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4791</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>334 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio  College Type\n",
       "0                    14.623100             3\n",
       "4                    20.247059             2\n",
       "5                    18.825503             2\n",
       "6                    15.112069             3\n",
       "7                    17.071472             3\n",
       "...                        ...           ...\n",
       "2871                       NaN             0\n",
       "3623                       NaN             1\n",
       "4278                       NaN             1\n",
       "4495                       NaN             1\n",
       "4791                       NaN             1\n",
       "\n",
       "[334 rows x 2 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = dataset_t.drop(columns=['Rating'])\n",
    "y = dataset_t['Rating']\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "7965b029-2530-49aa-b789-e7e3415fdfe8",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_valid, y_train, y_valid = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Drop samples with missing values\n",
    "X_train_cleaned = X_train.dropna()\n",
    "\n",
    "# Drop corresponding labels in y_train as well if there are missing values\n",
    "y_train_cleaned = y_train.drop(y_train.index.difference(X_train_cleaned.index))\n",
    "\n",
    "X_valid_cleaned = X_valid.dropna()\n",
    "\n",
    "# Drop corresponding labels in y_train as well if there are missing values\n",
    "y_valid_cleaned = y_valid.drop(y_valid.index.difference(X_valid_cleaned.index))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "05fe873d-d2a9-4d0c-800f-f47da870fa81",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training dataset feature names: Index(['student_to_faculty_ratio', 'College Type'], dtype='object')\n"
     ]
    },
    {
     "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>student_to_faculty_ratio</th>\n",
       "      <th>College Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>615</th>\n",
       "      <td>23.884848</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>60.677326</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1099</th>\n",
       "      <td>15.902597</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>11.931487</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>25.157895</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>38.090909</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>36.077778</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>29.703297</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>904</th>\n",
       "      <td>110.552189</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>18.695853</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>255 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio  College Type\n",
       "615                  23.884848             3\n",
       "172                  60.677326             3\n",
       "1099                 15.902597             2\n",
       "47                   11.931487             3\n",
       "57                   25.157895             3\n",
       "...                        ...           ...\n",
       "454                  38.090909             3\n",
       "161                  36.077778             3\n",
       "236                  29.703297             2\n",
       "904                 110.552189             3\n",
       "226                  18.695853             2\n",
       "\n",
       "[255 rows x 2 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Training dataset feature names:\", X_train_cleaned.columns)\n",
    "X_train_cleaned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "09ed3d9d-7a9a-49ba-b782-7bff51c9b677",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 0.37234927647614396\n"
     ]
    }
   ],
   "source": [
    "#Using RandomForestRegressor to predict rating\n",
    "model = RandomForestRegressor(random_state=42)\n",
    "model.fit(X_train_cleaned, y_train_cleaned)\n",
    "X_valid_cleaned = X_valid.dropna()\n",
    "y_valid_cleaned = y_valid.drop(y_valid.index.difference(X_valid_cleaned.index))\n",
    "\n",
    "# making predictions on the cleaned validation set\n",
    "y_pred = model.predict(X_valid_cleaned)\n",
    "\n",
    "# Calculate RMSE (Root Mean Squared Error) to evaluate the model performance\n",
    "rmse = sqrt(mean_squared_error(y_valid_cleaned, y_pred))\n",
    "print(f\"RMSE: {rmse}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "e08dcc6b-6c99-4b60-83f3-f17ad9624d23",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating a output dataset with rows that doesn't have rating to predict the rating\n",
    "dataset_main_subtracted = data_set.drop(dataset.index, errors='ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "69a14fbe-94f4-4150-9685-ca8d4ce1a923",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_main=dataset_main_subtracted.drop(columns=['Facilities','City'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "90464839-6483-4399-940b-ef5b5f20ad72",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>College Type</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.217822</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.866197</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21.626818</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5442</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5443</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5444</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5445</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5446</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Private</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5113 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio       College Type Rating\n",
       "1                     5.578125  Public/Government    NaN\n",
       "2                    37.217822  Public/Government    NaN\n",
       "3                    15.866197            Private    NaN\n",
       "10                         NaN  Public/Government    NaN\n",
       "13                   21.626818            Private    NaN\n",
       "...                        ...                ...    ...\n",
       "5442                       NaN            Private    NaN\n",
       "5443                       NaN            Private    NaN\n",
       "5444                  0.400000            Private    NaN\n",
       "5445                  3.800000            Private    NaN\n",
       "5446                       NaN            Private    NaN\n",
       "\n",
       "[5113 rows x 3 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_main"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "dbbd823c-efbd-4882-a153-719f55ddf1cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test=dataset_main.drop(columns='Rating')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "d3a86bf1-3bca-465a-8ea9-ef3fd25d096b",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>College Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>Public/Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.217822</td>\n",
       "      <td>Public/Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.866197</td>\n",
       "      <td>Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Public/Government</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21.626818</td>\n",
       "      <td>Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5442</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5443</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5444</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5445</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5446</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Private</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5113 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio       College Type\n",
       "1                     5.578125  Public/Government\n",
       "2                    37.217822  Public/Government\n",
       "3                    15.866197            Private\n",
       "10                         NaN  Public/Government\n",
       "13                   21.626818            Private\n",
       "...                        ...                ...\n",
       "5442                       NaN            Private\n",
       "5443                       NaN            Private\n",
       "5444                  0.400000            Private\n",
       "5445                  3.800000            Private\n",
       "5446                       NaN            Private\n",
       "\n",
       "[5113 rows x 2 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "e30bef12-f476-4845-b311-a68853558e7d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original Categories: ['Private' 'Public/Government' nan]\n"
     ]
    }
   ],
   "source": [
    "#Encoding College_type\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "one_hot_encoded = pd.get_dummies(X_test, columns=['College Type'])\n",
    "\n",
    "# Label Encoding\n",
    "xtest = X_test.copy()  # Make a copy of the DataFrame\n",
    "label_encoder = LabelEncoder()\n",
    "\n",
    "xtest['College Type'] = label_encoder.fit_transform(X_test['College Type'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c047533d-9feb-41ce-ad0c-978830b1e238",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>College Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.217822</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.866197</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21.626818</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>28.147059</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5435</th>\n",
       "      <td>16.453125</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5438</th>\n",
       "      <td>7.114583</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5440</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5444</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5445</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4058 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio  College Type\n",
       "1                     5.578125             1\n",
       "2                    37.217822             1\n",
       "3                    15.866197             0\n",
       "13                   21.626818             0\n",
       "16                   28.147059             1\n",
       "...                        ...           ...\n",
       "5435                 16.453125             0\n",
       "5438                  7.114583             0\n",
       "5440                  3.000000             0\n",
       "5444                  0.400000             0\n",
       "5445                  3.800000             0\n",
       "\n",
       "[4058 rows x 2 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xtest.dropna(subset=['student_to_faculty_ratio'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "ff7322f5-3710-4cc2-80fe-9dcd062e0e8d",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>College Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.217822</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.866197</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21.626818</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5442</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5443</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5444</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5445</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5446</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5113 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio  College Type\n",
       "1                     5.578125             1\n",
       "2                    37.217822             1\n",
       "3                    15.866197             0\n",
       "10                         NaN             1\n",
       "13                   21.626818             0\n",
       "...                        ...           ...\n",
       "5442                       NaN             0\n",
       "5443                       NaN             0\n",
       "5444                  0.400000             0\n",
       "5445                  3.800000             0\n",
       "5446                       NaN             0\n",
       "\n",
       "[5113 rows x 2 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xtest.dropna(subset=['College Type'])\n",
    "xtest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "52d035fe-5d67-4ab1-ab88-f05c25617799",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>College Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.217822</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.866197</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21.626818</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>28.147059</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5435</th>\n",
       "      <td>16.453125</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5438</th>\n",
       "      <td>7.114583</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5440</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5444</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5445</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4058 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio  College Type\n",
       "1                     5.578125             1\n",
       "2                    37.217822             1\n",
       "3                    15.866197             0\n",
       "13                   21.626818             0\n",
       "16                   28.147059             1\n",
       "...                        ...           ...\n",
       "5435                 16.453125             0\n",
       "5438                  7.114583             0\n",
       "5440                  3.000000             0\n",
       "5444                  0.400000             0\n",
       "5445                  3.800000             0\n",
       "\n",
       "[4058 rows x 2 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xtest=xtest.dropna(subset=['student_to_faculty_ratio'])\n",
    "xtest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "864a2083-9103-4209-a2c2-7fa0f210b7f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "student_to_faculty_ratio    0\n",
      "College Type                0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "missing_values = xtest.isnull().sum()\n",
    "print(missing_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "777e44b2-e2ad-4151-96b4-65b558c45d0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# making predictions for rating\n",
    "predictions=model.predict(xtest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "a91fdf3e-466c-4c28-8699-43a2cf0dc4e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3.0084, 3.333 , 3.3317, ..., 3.2061, 3.2429, 3.11  ])"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "2dbc54d5-caa1-436f-b3aa-78ed1b7e441e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#adding the predictions to the test dataset as a column\n",
    "xtest.loc[:, \"Rating\"] = predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "730d4b92-ff88-451d-a70a-9617f9e3e46b",
   "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>student_to_faculty_ratio</th>\n",
       "      <th>College Type</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.217822</td>\n",
       "      <td>1</td>\n",
       "      <td>3.3330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.866197</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21.626818</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>28.147059</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5435</th>\n",
       "      <td>16.453125</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5438</th>\n",
       "      <td>7.114583</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5440</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5444</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5445</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4058 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio  College Type  Rating\n",
       "1                     5.578125             1  3.0084\n",
       "2                    37.217822             1  3.3330\n",
       "3                    15.866197             0  3.3317\n",
       "13                   21.626818             0  3.1869\n",
       "16                   28.147059             1  2.7736\n",
       "...                        ...           ...     ...\n",
       "5435                 16.453125             0  3.0870\n",
       "5438                  7.114583             0  2.8146\n",
       "5440                  3.000000             0  3.2061\n",
       "5444                  0.400000             0  3.2429\n",
       "5445                  3.800000             0  3.1100\n",
       "\n",
       "[4058 rows x 3 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xtest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "5eba62ba-b099-41ec-a3b8-ce816c5aeb66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "College Name                    0\n",
      "Genders Accepted               18\n",
      "Campus Size                  2751\n",
      "Total Student Enrollments    1010\n",
      "Total Faculty                 168\n",
      "Established Year              101\n",
      "Rating                       5113\n",
      "University                   1936\n",
      "Courses                         0\n",
      "Facilities                     13\n",
      "City                            1\n",
      "State                           1\n",
      "Country                         1\n",
      "College Type                    2\n",
      "Average Fees                    1\n",
      "student_to_faculty_ratio     1069\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "missing_values = input_file.isnull().sum()\n",
    "print(missing_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "37b3e586-4545-4c5a-94a5-41a3ace53bda",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Combining the input_file dataset with the dataset that has the predictions \n",
    "combined_df = xtest.merge(input_file, left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "8e74cf04-18d0-4e09-a818-0bd8a0a28dbe",
   "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>student_to_faculty_ratio_x</th>\n",
       "      <th>College Type_x</th>\n",
       "      <th>Rating_x</th>\n",
       "      <th>College Name</th>\n",
       "      <th>Genders Accepted</th>\n",
       "      <th>Campus Size</th>\n",
       "      <th>Total Student Enrollments</th>\n",
       "      <th>Total Faculty</th>\n",
       "      <th>Established Year</th>\n",
       "      <th>Rating_y</th>\n",
       "      <th>University</th>\n",
       "      <th>Courses</th>\n",
       "      <th>Facilities</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>College Type_y</th>\n",
       "      <th>Average Fees</th>\n",
       "      <th>student_to_faculty_ratio_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0084</td>\n",
       "      <td>Visvesvaraya National Institute of Technology ...</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>215 Acres</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Nagpur</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>India</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>273596.666666666</td>\n",
       "      <td>5.578125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37.217822</td>\n",
       "      <td>1</td>\n",
       "      <td>3.3330</td>\n",
       "      <td>Netaji Subhas University of Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>145 Acres</td>\n",
       "      <td>3759.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Engineering, B.Tech Electronic...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>India</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>352320</td>\n",
       "      <td>37.217822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.866197</td>\n",
       "      <td>0</td>\n",
       "      <td>3.3317</td>\n",
       "      <td>Birla Institute of Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>980 Acres</td>\n",
       "      <td>4506.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>1955</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Ranchi</td>\n",
       "      <td>Jharkhand</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>596686.046511627</td>\n",
       "      <td>15.866197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>21.626818</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1869</td>\n",
       "      <td>Lovely Professional University</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>600 Acres</td>\n",
       "      <td>47579.0</td>\n",
       "      <td>2200.0</td>\n",
       "      <td>2005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Arch, B.Com LLB Hons, BA LLB Hons, BBA LLB H...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Phagwara</td>\n",
       "      <td>Punjab</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>423667.176870748</td>\n",
       "      <td>21.626818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>28.147059</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7736</td>\n",
       "      <td>Sardar Vallabhbhai National Institute of Techn...</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>251 Acres</td>\n",
       "      <td>4785.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>1961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Mechanical Engineering, B.Tech Electron...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Surat</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>India</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>224208.333333333</td>\n",
       "      <td>28.147059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5435</th>\n",
       "      <td>16.453125</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0870</td>\n",
       "      <td>Atmiya Institute of Technology and Science for...</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>23 Acres</td>\n",
       "      <td>1053.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>2005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gujarat Technological University, Ahmedabad</td>\n",
       "      <td>Diploma in Computer Engineering, Diploma in Me...</td>\n",
       "      <td>Boys Hostel, Gym, Library, Sports, Cafeteria, ...</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>Gujarat</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>126000</td>\n",
       "      <td>16.453125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5438</th>\n",
       "      <td>7.114583</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8146</td>\n",
       "      <td>Rajasthan Institute of Engineering and Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>683.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>2009</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rajasthan Technical University, Kota</td>\n",
       "      <td>B.Tech Electrical Engineering, Diploma in Civi...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Semalpura</td>\n",
       "      <td>Rajasthan</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>206500</td>\n",
       "      <td>7.114583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5440</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2061</td>\n",
       "      <td>IBT College of Diploma Engineering</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>20 Acres</td>\n",
       "      <td>117.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chhattisgarh Swami Vivekanand Technical Univer...</td>\n",
       "      <td>Diploma in Civil Engineering, Diploma in Mecha...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Library, Sports, Ca...</td>\n",
       "      <td>Janjgiri</td>\n",
       "      <td>Chhattisgarh</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>39600</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5444</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2429</td>\n",
       "      <td>Trimurti Institute of Technology Polytechnic</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>2009</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Diploma in Electrical Engineering, Diploma in ...</td>\n",
       "      <td>Library, Sports, IT Infrastructure, Laboratories</td>\n",
       "      <td>Paldhi</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>157000</td>\n",
       "      <td>0.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5445</th>\n",
       "      <td>3.800000</td>\n",
       "      <td>0</td>\n",
       "      <td>3.1100</td>\n",
       "      <td>RV Parankar College of Engineering and Technology</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2015</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rashtrasant Tukadoji Maharaj Nagpur University...</td>\n",
       "      <td>BE Civil Engineering, BE Electrical Engineerin...</td>\n",
       "      <td>Library, Sports, Cafeteria, Auditorium, IT Inf...</td>\n",
       "      <td>Arvi</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>India</td>\n",
       "      <td>Private</td>\n",
       "      <td>272000</td>\n",
       "      <td>3.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4058 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      student_to_faculty_ratio_x  College Type_x  Rating_x  \\\n",
       "1                       5.578125               1    3.0084   \n",
       "2                      37.217822               1    3.3330   \n",
       "3                      15.866197               0    3.3317   \n",
       "13                     21.626818               0    3.1869   \n",
       "16                     28.147059               1    2.7736   \n",
       "...                          ...             ...       ...   \n",
       "5435                   16.453125               0    3.0870   \n",
       "5438                    7.114583               0    2.8146   \n",
       "5440                    3.000000               0    3.2061   \n",
       "5444                    0.400000               0    3.2429   \n",
       "5445                    3.800000               0    3.1100   \n",
       "\n",
       "                                           College Name Genders Accepted  \\\n",
       "1     Visvesvaraya National Institute of Technology ...            Co-Ed   \n",
       "2                Netaji Subhas University of Technology            Co-Ed   \n",
       "3                         Birla Institute of Technology            Co-Ed   \n",
       "13                       Lovely Professional University            Co-Ed   \n",
       "16    Sardar Vallabhbhai National Institute of Techn...            Co-Ed   \n",
       "...                                                 ...              ...   \n",
       "5435  Atmiya Institute of Technology and Science for...            Co-Ed   \n",
       "5438  Rajasthan Institute of Engineering and Technology            Co-Ed   \n",
       "5440                 IBT College of Diploma Engineering            Co-Ed   \n",
       "5444       Trimurti Institute of Technology Polytechnic            Co-Ed   \n",
       "5445  RV Parankar College of Engineering and Technology            Co-Ed   \n",
       "\n",
       "     Campus Size  Total Student Enrollments  Total Faculty Established Year  \\\n",
       "1      215 Acres                     1071.0          192.0             2007   \n",
       "2      145 Acres                     3759.0          101.0             2018   \n",
       "3      980 Acres                     4506.0          284.0             1955   \n",
       "13     600 Acres                    47579.0         2200.0             2005   \n",
       "16     251 Acres                     4785.0          170.0             1961   \n",
       "...          ...                        ...            ...              ...   \n",
       "5435    23 Acres                     1053.0           64.0             2005   \n",
       "5438         NaN                      683.0           96.0             2009   \n",
       "5440    20 Acres                      117.0           39.0             2008   \n",
       "5444         NaN                       22.0           55.0             2009   \n",
       "5445         NaN                       38.0           10.0             2015   \n",
       "\n",
       "     Rating_y                                         University  \\\n",
       "1         NaN                                                NaN   \n",
       "2         NaN                                                NaN   \n",
       "3         NaN                                                NaN   \n",
       "13        NaN                                                NaN   \n",
       "16        NaN                                                NaN   \n",
       "...       ...                                                ...   \n",
       "5435      NaN        Gujarat Technological University, Ahmedabad   \n",
       "5438      NaN               Rajasthan Technical University, Kota   \n",
       "5440      NaN  Chhattisgarh Swami Vivekanand Technical Univer...   \n",
       "5444      NaN                                                NaN   \n",
       "5445      NaN  Rashtrasant Tukadoji Maharaj Nagpur University...   \n",
       "\n",
       "                                                Courses  \\\n",
       "1     B.Tech Computer Science Engineering, B.Tech El...   \n",
       "2     B.Tech Computer Engineering, B.Tech Electronic...   \n",
       "3     B.Tech Computer Science Engineering, B.Tech El...   \n",
       "13    B.Arch, B.Com LLB Hons, BA LLB Hons, BBA LLB H...   \n",
       "16    B.Tech Mechanical Engineering, B.Tech Electron...   \n",
       "...                                                 ...   \n",
       "5435  Diploma in Computer Engineering, Diploma in Me...   \n",
       "5438  B.Tech Electrical Engineering, Diploma in Civi...   \n",
       "5440  Diploma in Civil Engineering, Diploma in Mecha...   \n",
       "5444  Diploma in Electrical Engineering, Diploma in ...   \n",
       "5445  BE Civil Engineering, BE Electrical Engineerin...   \n",
       "\n",
       "                                             Facilities       City  \\\n",
       "1     Boys Hostel, Girls Hostel, Gym, Library, Sport...     Nagpur   \n",
       "2     Boys Hostel, Girls Hostel, Gym, Library, Sport...  New Delhi   \n",
       "3     Boys Hostel, Girls Hostel, Gym, Library, Sport...     Ranchi   \n",
       "13    Boys Hostel, Girls Hostel, Gym, Library, Sport...   Phagwara   \n",
       "16    Boys Hostel, Girls Hostel, Gym, Library, Sport...      Surat   \n",
       "...                                                 ...        ...   \n",
       "5435  Boys Hostel, Gym, Library, Sports, Cafeteria, ...     Rajkot   \n",
       "5438  Boys Hostel, Girls Hostel, Gym, Library, Sport...  Semalpura   \n",
       "5440  Boys Hostel, Girls Hostel, Library, Sports, Ca...   Janjgiri   \n",
       "5444   Library, Sports, IT Infrastructure, Laboratories     Paldhi   \n",
       "5445  Library, Sports, Cafeteria, Auditorium, IT Inf...       Arvi   \n",
       "\n",
       "             State Country     College Type_y      Average Fees  \\\n",
       "1      Maharashtra   India  Public/Government  273596.666666666   \n",
       "2            Delhi   India  Public/Government            352320   \n",
       "3        Jharkhand   India            Private  596686.046511627   \n",
       "13          Punjab   India            Private  423667.176870748   \n",
       "16         Gujarat   India  Public/Government  224208.333333333   \n",
       "...            ...     ...                ...               ...   \n",
       "5435       Gujarat   India            Private            126000   \n",
       "5438     Rajasthan   India            Private            206500   \n",
       "5440  Chhattisgarh   India            Private             39600   \n",
       "5444   Maharashtra   India            Private            157000   \n",
       "5445   Maharashtra   India            Private            272000   \n",
       "\n",
       "      student_to_faculty_ratio_y  \n",
       "1                       5.578125  \n",
       "2                      37.217822  \n",
       "3                      15.866197  \n",
       "13                     21.626818  \n",
       "16                     28.147059  \n",
       "...                          ...  \n",
       "5435                   16.453125  \n",
       "5438                    7.114583  \n",
       "5440                    3.000000  \n",
       "5444                    0.400000  \n",
       "5445                    3.800000  \n",
       "\n",
       "[4058 rows x 19 columns]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "3e314404-d5be-4858-9940-5f6b9829d607",
   "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>student_to_faculty_ratio_x</th>\n",
       "      <th>College Type_x</th>\n",
       "      <th>Rating_x</th>\n",
       "      <th>College Name</th>\n",
       "      <th>Genders Accepted</th>\n",
       "      <th>Campus Size</th>\n",
       "      <th>Total Student Enrollments</th>\n",
       "      <th>Total Faculty</th>\n",
       "      <th>Established Year</th>\n",
       "      <th>Rating_y</th>\n",
       "      <th>University</th>\n",
       "      <th>Courses</th>\n",
       "      <th>Facilities</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Country</th>\n",
       "      <th>College Type_y</th>\n",
       "      <th>Average Fees</th>\n",
       "      <th>student_to_faculty_ratio_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.578125</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0084</td>\n",
       "      <td>Visvesvaraya National Institute of Technology ...</td>\n",
       "      <td>Co-Ed</td>\n",
       "      <td>215 Acres</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B.Tech Computer Science Engineering, B.Tech El...</td>\n",
       "      <td>Boys Hostel, Girls Hostel, Gym, Library, Sport...</td>\n",
       "      <td>Nagpur</td>\n",
       "      <td>Maharashtra</td>\n",
       "      <td>India</td>\n",
       "      <td>Public/Government</td>\n",
       "      <td>273596.666666666</td>\n",
       "      <td>5.578125</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   student_to_faculty_ratio_x  College Type_x  Rating_x  \\\n",
       "1                    5.578125               1    3.0084   \n",
       "\n",
       "                                        College Name Genders Accepted  \\\n",
       "1  Visvesvaraya National Institute of Technology ...            Co-Ed   \n",
       "\n",
       "  Campus Size  Total Student Enrollments  Total Faculty Established Year  \\\n",
       "1   215 Acres                     1071.0          192.0             2007   \n",
       "\n",
       "  Rating_y University                                            Courses  \\\n",
       "1      NaN        NaN  B.Tech Computer Science Engineering, B.Tech El...   \n",
       "\n",
       "                                          Facilities    City        State  \\\n",
       "1  Boys Hostel, Girls Hostel, Gym, Library, Sport...  Nagpur  Maharashtra   \n",
       "\n",
       "  Country     College Type_y      Average Fees  student_to_faculty_ratio_y  \n",
       "1   India  Public/Government  273596.666666666                    5.578125  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "1cbfabac-cff4-4121-9791-ee4a2d4ddb77",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting the final output file to a csv file\n",
    "combined_df.to_csv('output_file.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "5c07eb9b-4625-4b13-8048-e2d40901ea51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<a href='output_file.csv' target='_blank'>output_file.csv</a><br>"
      ],
      "text/plain": [
       "C:\\Users\\Harini N\\output_file.csv"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Creating a link to the output file\n",
    "from IPython.display import FileLink\n",
    "\n",
    "FileLink('output_file.csv')"
   ]
  }
 ],
 "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}