house-rent-prediction.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"## House rent prediction model\n\n**Problem statement**: Given the location of a house and it's related details, predict the rent","metadata":{}},{"cell_type":"code","source":"import numpy as np \nimport pandas as pd\nimport matplotlib.pyplot as plt","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-04-11T10:27:39.251915Z","iopub.execute_input":"2023-04-11T10:27:39.252347Z","iopub.status.idle":"2023-04-11T10:27:39.259827Z","shell.execute_reply.started":"2023-04-11T10:27:39.252310Z","shell.execute_reply":"2023-04-11T10:27:39.257977Z"},"trusted":true},"execution_count":11,"outputs":[]},{"cell_type":"markdown","source":"## Exploratory analysis","metadata":{}},{"cell_type":"code","source":"data = pd.read_csv(\"/kaggle/input/house-rent-prices-of-metropolitan-cities-in-india/Delhi_rent.csv\")\ndata.sort_values('price',ascending=False).head()","metadata":{"execution":{"iopub.status.busy":"2023-04-11T10:26:41.509802Z","iopub.execute_input":"2023-04-11T10:26:41.510302Z","iopub.status.idle":"2023-04-11T10:26:41.614295Z","shell.execute_reply.started":"2023-04-11T10:26:41.510259Z","shell.execute_reply":"2023-04-11T10:26:41.612614Z"},"trusted":true},"execution_count":9,"outputs":[{"execution_count":9,"output_type":"execute_result","data":{"text/plain":"      seller_type  bedroom layout_type      property_type         locality  \\\n77          OWNER      4.0         BHK  Independent Floor    Malviya Nagar   \n25735       AGENT      3.0         BHK          Apartment  Greater Kailash   \n32108       OWNER      3.0         BHK          Apartment    Malviya Nagar   \n12226       AGENT      4.0         BHK  Independent Floor        Pitampura   \n27912       OWNER      5.0         BHK  Independent Floor          Kalkaji   \n\n        price    area    furnish_type     bathroom  \n77     99,000  3000.0  Semi-Furnished  4 bathrooms  \n25735  98,000  2116.0       Furnished  3 bathrooms  \n32108  98,000  1800.0       Furnished  3 bathrooms  \n12226  98,000  3200.0  Semi-Furnished  4 bathrooms  \n27912  98,000  2700.0       Furnished  5 bathrooms  ","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>seller_type</th>\n      <th>bedroom</th>\n      <th>layout_type</th>\n      <th>property_type</th>\n      <th>locality</th>\n      <th>price</th>\n      <th>area</th>\n      <th>furnish_type</th>\n      <th>bathroom</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>77</th>\n      <td>OWNER</td>\n      <td>4.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Malviya Nagar</td>\n      <td>99,000</td>\n      <td>3000.0</td>\n      <td>Semi-Furnished</td>\n      <td>4 bathrooms</td>\n    </tr>\n    <tr>\n      <th>25735</th>\n      <td>AGENT</td>\n      <td>3.0</td>\n      <td>BHK</td>\n      <td>Apartment</td>\n      <td>Greater Kailash</td>\n      <td>98,000</td>\n      <td>2116.0</td>\n      <td>Furnished</td>\n      <td>3 bathrooms</td>\n    </tr>\n    <tr>\n      <th>32108</th>\n      <td>OWNER</td>\n      <td>3.0</td>\n      <td>BHK</td>\n      <td>Apartment</td>\n      <td>Malviya Nagar</td>\n      <td>98,000</td>\n      <td>1800.0</td>\n      <td>Furnished</td>\n      <td>3 bathrooms</td>\n    </tr>\n    <tr>\n      <th>12226</th>\n      <td>AGENT</td>\n      <td>4.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Pitampura</td>\n      <td>98,000</td>\n      <td>3200.0</td>\n      <td>Semi-Furnished</td>\n      <td>4 bathrooms</td>\n    </tr>\n    <tr>\n      <th>27912</th>\n      <td>OWNER</td>\n      <td>5.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Kalkaji</td>\n      <td>98,000</td>\n      <td>2700.0</td>\n      <td>Furnished</td>\n      <td>5 bathrooms</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"data.query('area > 2000')","metadata":{"execution":{"iopub.status.busy":"2023-04-11T10:26:43.701974Z","iopub.execute_input":"2023-04-11T10:26:43.702439Z","iopub.status.idle":"2023-04-11T10:26:43.737760Z","shell.execute_reply.started":"2023-04-11T10:26:43.702399Z","shell.execute_reply":"2023-04-11T10:26:43.736235Z"},"trusted":true},"execution_count":10,"outputs":[{"execution_count":10,"output_type":"execute_result","data":{"text/plain":"      seller_type  bedroom layout_type      property_type            locality  \\\n25          AGENT      3.0         BHK          Apartment        Vasant Vihar   \n41          AGENT      3.0         BHK  Independent Floor          Neeti Bagh   \n46          AGENT      3.0         BHK  Independent Floor     Panchsheel Park   \n47          AGENT      2.0         BHK  Independent Floor      Defence Colony   \n77          OWNER      4.0         BHK  Independent Floor       Malviya Nagar   \n...           ...      ...         ...                ...                 ...   \n33403       OWNER      3.0         BHK  Independent Floor         Preet Vihar   \n33431       OWNER      2.0         BHK  Independent Floor     Sector-7 Rohini   \n33433       OWNER      4.0         BHK          Penthouse    Sector 11 Dwarka   \n33439       OWNER      3.0         BHK  Independent Floor         Ashok Vihar   \n33480       OWNER      4.0         BHK  Independent Floor  New Friends Colony   \n\n        price    area    furnish_type     bathroom  \n25       1.25  2500.0       Furnished  3 bathrooms  \n41        1.5  4000.0  Semi-Furnished  3 bathrooms  \n46        1.1  3600.0  Semi-Furnished  3 bathrooms  \n47     72,000  2020.0       Furnished  2 bathrooms  \n77     99,000  3000.0  Semi-Furnished  4 bathrooms  \n...       ...     ...             ...          ...  \n33403  40,000  2070.0  Semi-Furnished  2 bathrooms  \n33431  15,000  2500.0  Semi-Furnished  2 bathrooms  \n33433  45,000  2500.0  Semi-Furnished  3 bathrooms  \n33439  60,000  2700.0     Unfurnished  3 bathrooms  \n33480     1.4  4000.0     Unfurnished  4 bathrooms  \n\n[10116 rows x 9 columns]","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>seller_type</th>\n      <th>bedroom</th>\n      <th>layout_type</th>\n      <th>property_type</th>\n      <th>locality</th>\n      <th>price</th>\n      <th>area</th>\n      <th>furnish_type</th>\n      <th>bathroom</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>25</th>\n      <td>AGENT</td>\n      <td>3.0</td>\n      <td>BHK</td>\n      <td>Apartment</td>\n      <td>Vasant Vihar</td>\n      <td>1.25</td>\n      <td>2500.0</td>\n      <td>Furnished</td>\n      <td>3 bathrooms</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>AGENT</td>\n      <td>3.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Neeti Bagh</td>\n      <td>1.5</td>\n      <td>4000.0</td>\n      <td>Semi-Furnished</td>\n      <td>3 bathrooms</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>AGENT</td>\n      <td>3.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Panchsheel Park</td>\n      <td>1.1</td>\n      <td>3600.0</td>\n      <td>Semi-Furnished</td>\n      <td>3 bathrooms</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>AGENT</td>\n      <td>2.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Defence Colony</td>\n      <td>72,000</td>\n      <td>2020.0</td>\n      <td>Furnished</td>\n      <td>2 bathrooms</td>\n    </tr>\n    <tr>\n      <th>77</th>\n      <td>OWNER</td>\n      <td>4.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Malviya Nagar</td>\n      <td>99,000</td>\n      <td>3000.0</td>\n      <td>Semi-Furnished</td>\n      <td>4 bathrooms</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    </tr>\n    <tr>\n      <th>33403</th>\n      <td>OWNER</td>\n      <td>3.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Preet Vihar</td>\n      <td>40,000</td>\n      <td>2070.0</td>\n      <td>Semi-Furnished</td>\n      <td>2 bathrooms</td>\n    </tr>\n    <tr>\n      <th>33431</th>\n      <td>OWNER</td>\n      <td>2.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Sector-7 Rohini</td>\n      <td>15,000</td>\n      <td>2500.0</td>\n      <td>Semi-Furnished</td>\n      <td>2 bathrooms</td>\n    </tr>\n    <tr>\n      <th>33433</th>\n      <td>OWNER</td>\n      <td>4.0</td>\n      <td>BHK</td>\n      <td>Penthouse</td>\n      <td>Sector 11 Dwarka</td>\n      <td>45,000</td>\n      <td>2500.0</td>\n      <td>Semi-Furnished</td>\n      <td>3 bathrooms</td>\n    </tr>\n    <tr>\n      <th>33439</th>\n      <td>OWNER</td>\n      <td>3.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>Ashok Vihar</td>\n      <td>60,000</td>\n      <td>2700.0</td>\n      <td>Unfurnished</td>\n      <td>3 bathrooms</td>\n    </tr>\n    <tr>\n      <th>33480</th>\n      <td>OWNER</td>\n      <td>4.0</td>\n      <td>BHK</td>\n      <td>Independent Floor</td>\n      <td>New Friends Colony</td>\n      <td>1.4</td>\n      <td>4000.0</td>\n      <td>Unfurnished</td>\n      <td>4 bathrooms</td>\n    </tr>\n  </tbody>\n</table>\n<p>10116 rows × 9 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"data.plot.scatter(x='bedroom',y='area')","metadata":{"execution":{"iopub.status.busy":"2023-04-11T10:29:03.747945Z","iopub.execute_input":"2023-04-11T10:29:03.748481Z","iopub.status.idle":"2023-04-11T10:29:04.210668Z","shell.execute_reply.started":"2023-04-11T10:29:03.748433Z","shell.execute_reply":"2023-04-11T10:29:04.208779Z"},"trusted":true},"execution_count":15,"outputs":[{"execution_count":15,"output_type":"execute_result","data":{"text/plain":"<AxesSubplot:xlabel='bedroom', ylabel='area'>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 1 Axes>","image/png":"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\n"},"metadata":{}}]}]}