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aa-gamJain/House Price Prediction.ipynb

Created October 31, 2018 07:43
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House Price Prediction.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### To do\n",
"\n",
"1. Data Cleaning\n",
"2. Data Exploration\n",
"3. Data Preparation for modelling\n",
"4. Model Building and Testing\n",
"\n",
" * Cross Validation on Random Forest\n",
" * Cross Validation on Xgboost\n",
" * Cross Validation on Catboost\n",
" \n",
"5. Selecting best model, Split train and test and predict\n",
"6. Conclusion"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import warnings\n",
"warnings.filterwarnings('ignore')\n",
"from sklearn import preprocessing\n",
"import seaborn as sns\n",
"sns.set()\n",
"\n",
"import time\n",
"from tqdm import tqdm_notebook\n",
"\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn import metrics\n",
"from xgboost import XGBRegressor\n",
"from catboost import CatBoostRegressor, Pool, cv\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from sklearn.cross_validation import cross_val_score\n",
"from sklearn.grid_search import GridSearchCV\n",
"\n",
"pd.set_option('display.max_rows', 500)\n",
"pd.set_option('display.max_columns', 500)\n",
"pd.set_option('display.width', 1000)\n",
"pd.set_option('display.float_format', lambda x: '%.3f' % x)\n",
"\n",
"from geopy.geocoders import Bing\n",
"api_key = 'AuDc6-IRWQ_A3ihk6_kXHmsvgo86fec76XRDx6Gu_BoMje1Fv53_JwgASfThgu8i'\n",
"geolocator = Bing(api_key)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Reading Files"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv('kc_house_data.csv')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"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>id</th>\n",
" <th>date</th>\n",
" <th>price</th>\n",
" <th>bedrooms</th>\n",
" <th>bathrooms</th>\n",
" <th>sqft_living</th>\n",
" <th>sqft_lot</th>\n",
" <th>floors</th>\n",
" <th>waterfront</th>\n",
" <th>view</th>\n",
" <th>condition</th>\n",
" <th>grade</th>\n",
" <th>sqft_above</th>\n",
" <th>sqft_basement</th>\n",
" <th>yr_built</th>\n",
" <th>yr_renovated</th>\n",
" <th>zipcode</th>\n",
" <th>lat</th>\n",
" <th>long</th>\n",
" <th>sqft_living15</th>\n",
" <th>sqft_lot15</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>7129300520</td>\n",
" <td>10/13/2014</td>\n",
" <td>221900.000</td>\n",
" <td>3</td>\n",
" <td>1.000</td>\n",
" <td>1180</td>\n",
" <td>5650</td>\n",
" <td>1.000</td>\n",
" <td>nan</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>7</td>\n",
" <td>1180</td>\n",
" <td>0.0</td>\n",
" <td>1955</td>\n",
" <td>0.000</td>\n",
" <td>98178</td>\n",
" <td>47.511</td>\n",
" <td>-122.257</td>\n",
" <td>1340</td>\n",
" <td>5650</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>6414100192</td>\n",
" <td>12/9/2014</td>\n",
" <td>538000.000</td>\n",
" <td>3</td>\n",
" <td>2.250</td>\n",
" <td>2570</td>\n",
" <td>7242</td>\n",
" <td>2.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>7</td>\n",
" <td>2170</td>\n",
" <td>400.0</td>\n",
" <td>1951</td>\n",
" <td>1991.000</td>\n",
" <td>98125</td>\n",
" <td>47.721</td>\n",
" <td>-122.319</td>\n",
" <td>1690</td>\n",
" <td>7639</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5631500400</td>\n",
" <td>2/25/2015</td>\n",
" <td>180000.000</td>\n",
" <td>2</td>\n",
" <td>1.000</td>\n",
" <td>770</td>\n",
" <td>10000</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>6</td>\n",
" <td>770</td>\n",
" <td>0.0</td>\n",
" <td>1933</td>\n",
" <td>nan</td>\n",
" <td>98028</td>\n",
" <td>47.738</td>\n",
" <td>-122.233</td>\n",
" <td>2720</td>\n",
" <td>8062</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2487200875</td>\n",
" <td>12/9/2014</td>\n",
" <td>604000.000</td>\n",
" <td>4</td>\n",
" <td>3.000</td>\n",
" <td>1960</td>\n",
" <td>5000</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>5</td>\n",
" <td>7</td>\n",
" <td>1050</td>\n",
" <td>910.0</td>\n",
" <td>1965</td>\n",
" <td>0.000</td>\n",
" <td>98136</td>\n",
" <td>47.521</td>\n",
" <td>-122.393</td>\n",
" <td>1360</td>\n",
" <td>5000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1954400510</td>\n",
" <td>2/18/2015</td>\n",
" <td>510000.000</td>\n",
" <td>3</td>\n",
" <td>2.000</td>\n",
" <td>1680</td>\n",
" <td>8080</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>8</td>\n",
" <td>1680</td>\n",
" <td>0.0</td>\n",
" <td>1987</td>\n",
" <td>0.000</td>\n",
" <td>98074</td>\n",
" <td>47.617</td>\n",
" <td>-122.045</td>\n",
" <td>1800</td>\n",
" <td>7503</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id date price bedrooms bathrooms sqft_living sqft_lot floors waterfront view condition grade sqft_above sqft_basement yr_built yr_renovated zipcode lat long sqft_living15 sqft_lot15\n",
"0 7129300520 10/13/2014 221900.000 3 1.000 1180 5650 1.000 nan 0.000 3 7 1180 0.0 1955 0.000 98178 47.511 -122.257 1340 5650\n",
"1 6414100192 12/9/2014 538000.000 3 2.250 2570 7242 2.000 0.000 0.000 3 7 2170 400.0 1951 1991.000 98125 47.721 -122.319 1690 7639\n",
"2 5631500400 2/25/2015 180000.000 2 1.000 770 10000 1.000 0.000 0.000 3 6 770 0.0 1933 nan 98028 47.738 -122.233 2720 8062\n",
"3 2487200875 12/9/2014 604000.000 4 3.000 1960 5000 1.000 0.000 0.000 5 7 1050 910.0 1965 0.000 98136 47.521 -122.393 1360 5000\n",
"4 1954400510 2/18/2015 510000.000 3 2.000 1680 8080 1.000 0.000 0.000 3 8 1680 0.0 1987 0.000 98074 47.617 -122.045 1800 7503"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Data Cleaning"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"id 0\n",
"date 0\n",
"price 0\n",
"bedrooms 0\n",
"bathrooms 0\n",
"sqft_living 0\n",
"sqft_lot 0\n",
"floors 0\n",
"waterfront 2376\n",
"view 63\n",
"condition 0\n",
"grade 0\n",
"sqft_above 0\n",
"sqft_basement 0\n",
"yr_built 0\n",
"yr_renovated 3842\n",
"zipcode 0\n",
"lat 0\n",
"long 0\n",
"sqft_living15 0\n",
"sqft_lot15 0\n",
"dtype: int64"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[df.columns].isnull().sum() # Count of Null Values in each column"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 2 ways to fill missing values in `view` column.\n",
"\n",
"1. Fill by mode as you can see `type 0` comes 19422 times.\n",
"2. `View` has highly correlation with `Price and waterfront`. But `waterfront` itself has large number of missing values. So using `Price` to fill the missing values."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 1. By mode"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.000 19422\n",
"2.000 957\n",
"3.000 508\n",
"1.000 330\n",
"4.000 317\n",
"Name: view, dtype: int64"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['view'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"#df['view'].fillna(df['view'].mode().values[0],inplace=True) \n",
"\n",
"# Uncomment it to fill by mode."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 2. By Price"
]
},
{
"cell_type": "code",
"execution_count": 7,
"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>id</th>\n",
" <th>price</th>\n",
" <th>bedrooms</th>\n",
" <th>bathrooms</th>\n",
" <th>sqft_living</th>\n",
" <th>sqft_lot</th>\n",
" <th>floors</th>\n",
" <th>waterfront</th>\n",
" <th>view</th>\n",
" <th>condition</th>\n",
" <th>grade</th>\n",
" <th>sqft_above</th>\n",
" <th>yr_built</th>\n",
" <th>yr_renovated</th>\n",
" <th>zipcode</th>\n",
" <th>lat</th>\n",
" <th>long</th>\n",
" <th>sqft_living15</th>\n",
" <th>sqft_lot15</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>id</th>\n",
" <td>1.000</td>\n",
" <td>-0.017</td>\n",
" <td>0.001</td>\n",
" <td>0.005</td>\n",
" <td>-0.012</td>\n",
" <td>-0.132</td>\n",
" <td>0.019</td>\n",
" <td>-0.004</td>\n",
" <td>0.012</td>\n",
" <td>-0.024</td>\n",
" <td>0.008</td>\n",
" <td>-0.011</td>\n",
" <td>0.022</td>\n",
" <td>-0.012</td>\n",
" <td>-0.008</td>\n",
" <td>-0.002</td>\n",
" <td>0.021</td>\n",
" <td>-0.003</td>\n",
" <td>-0.139</td>\n",
" </tr>\n",
" <tr>\n",
" <th>price</th>\n",
" <td>-0.017</td>\n",
" <td>1.000</td>\n",
" <td>0.309</td>\n",
" <td>0.526</td>\n",
" <td>0.702</td>\n",
" <td>0.090</td>\n",
" <td>0.257</td>\n",
" <td>0.276</td>\n",
" <td>0.396</td>\n",
" <td>0.036</td>\n",
" <td>0.668</td>\n",
" <td>0.605</td>\n",
" <td>0.054</td>\n",
" <td>0.130</td>\n",
" <td>-0.053</td>\n",
" <td>0.307</td>\n",
" <td>0.022</td>\n",
" <td>0.585</td>\n",
" <td>0.083</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bedrooms</th>\n",
" <td>0.001</td>\n",
" <td>0.309</td>\n",
" <td>1.000</td>\n",
" <td>0.515</td>\n",
" <td>0.578</td>\n",
" <td>0.032</td>\n",
" <td>0.178</td>\n",
" <td>-0.002</td>\n",
" <td>0.079</td>\n",
" <td>0.026</td>\n",
" <td>0.357</td>\n",
" <td>0.479</td>\n",
" <td>0.156</td>\n",
" <td>0.018</td>\n",
" <td>-0.154</td>\n",
" <td>-0.010</td>\n",
" <td>0.132</td>\n",
" <td>0.393</td>\n",
" <td>0.031</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bathrooms</th>\n",
" <td>0.005</td>\n",
" <td>0.526</td>\n",
" <td>0.515</td>\n",
" <td>1.000</td>\n",
" <td>0.756</td>\n",
" <td>0.088</td>\n",
" <td>0.503</td>\n",
" <td>0.067</td>\n",
" <td>0.186</td>\n",
" <td>-0.126</td>\n",
" <td>0.666</td>\n",
" <td>0.687</td>\n",
" <td>0.507</td>\n",
" <td>0.051</td>\n",
" <td>-0.205</td>\n",
" <td>0.024</td>\n",
" <td>0.225</td>\n",
" <td>0.570</td>\n",
" <td>0.088</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sqft_living</th>\n",
" <td>-0.012</td>\n",
" <td>0.702</td>\n",
" <td>0.578</td>\n",
" <td>0.756</td>\n",
" <td>1.000</td>\n",
" <td>0.173</td>\n",
" <td>0.354</td>\n",
" <td>0.110</td>\n",
" <td>0.283</td>\n",
" <td>-0.059</td>\n",
" <td>0.763</td>\n",
" <td>0.876</td>\n",
" <td>0.318</td>\n",
" <td>0.056</td>\n",
" <td>-0.200</td>\n",
" <td>0.052</td>\n",
" <td>0.241</td>\n",
" <td>0.756</td>\n",
" <td>0.184</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sqft_lot</th>\n",
" <td>-0.132</td>\n",
" <td>0.090</td>\n",
" <td>0.032</td>\n",
" <td>0.088</td>\n",
" <td>0.173</td>\n",
" <td>1.000</td>\n",
" <td>-0.005</td>\n",
" <td>0.023</td>\n",
" <td>0.075</td>\n",
" <td>-0.009</td>\n",
" <td>0.115</td>\n",
" <td>0.184</td>\n",
" <td>0.053</td>\n",
" <td>0.005</td>\n",
" <td>-0.130</td>\n",
" <td>-0.086</td>\n",
" <td>0.230</td>\n",
" <td>0.145</td>\n",
" <td>0.718</td>\n",
" </tr>\n",
" <tr>\n",
" <th>floors</th>\n",
" <td>0.019</td>\n",
" <td>0.257</td>\n",
" <td>0.178</td>\n",
" <td>0.503</td>\n",
" <td>0.354</td>\n",
" <td>-0.005</td>\n",
" <td>1.000</td>\n",
" <td>0.022</td>\n",
" <td>0.028</td>\n",
" <td>-0.264</td>\n",
" <td>0.459</td>\n",
" <td>0.524</td>\n",
" <td>0.489</td>\n",
" <td>0.004</td>\n",
" <td>-0.060</td>\n",
" <td>0.049</td>\n",
" <td>0.126</td>\n",
" <td>0.280</td>\n",
" <td>-0.011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>waterfront</th>\n",
" <td>-0.004</td>\n",
" <td>0.276</td>\n",
" <td>-0.002</td>\n",
" <td>0.067</td>\n",
" <td>0.110</td>\n",
" <td>0.023</td>\n",
" <td>0.022</td>\n",
" <td>1.000</td>\n",
" <td>0.407</td>\n",
" <td>0.018</td>\n",
" <td>0.087</td>\n",
" <td>0.075</td>\n",
" <td>-0.026</td>\n",
" <td>0.087</td>\n",
" <td>0.031</td>\n",
" <td>-0.013</td>\n",
" <td>-0.040</td>\n",
" <td>0.089</td>\n",
" <td>0.032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>view</th>\n",
" <td>0.012</td>\n",
" <td>0.396</td>\n",
" <td>0.079</td>\n",
" <td>0.186</td>\n",
" <td>0.283</td>\n",
" <td>0.075</td>\n",
" <td>0.028</td>\n",
" <td>0.407</td>\n",
" <td>1.000</td>\n",
" <td>0.046</td>\n",
" <td>0.250</td>\n",
" <td>0.166</td>\n",
" <td>-0.055</td>\n",
" <td>0.101</td>\n",
" <td>0.085</td>\n",
" <td>0.006</td>\n",
" <td>-0.078</td>\n",
" <td>0.280</td>\n",
" <td>0.073</td>\n",
" </tr>\n",
" <tr>\n",
" <th>condition</th>\n",
" <td>-0.024</td>\n",
" <td>0.036</td>\n",
" <td>0.026</td>\n",
" <td>-0.126</td>\n",
" <td>-0.059</td>\n",
" <td>-0.009</td>\n",
" <td>-0.264</td>\n",
" <td>0.018</td>\n",
" <td>0.046</td>\n",
" <td>1.000</td>\n",
" <td>-0.147</td>\n",
" <td>-0.159</td>\n",
" <td>-0.362</td>\n",
" <td>-0.062</td>\n",
" <td>0.003</td>\n",
" <td>-0.015</td>\n",
" <td>-0.106</td>\n",
" <td>-0.093</td>\n",
" <td>-0.003</td>\n",
" </tr>\n",
" <tr>\n",
" <th>grade</th>\n",
" <td>0.008</td>\n",
" <td>0.668</td>\n",
" <td>0.357</td>\n",
" <td>0.666</td>\n",
" <td>0.763</td>\n",
" <td>0.115</td>\n",
" <td>0.459</td>\n",
" <td>0.087</td>\n",
" <td>0.250</td>\n",
" <td>-0.147</td>\n",
" <td>1.000</td>\n",
" <td>0.756</td>\n",
" <td>0.448</td>\n",
" <td>0.017</td>\n",
" <td>-0.186</td>\n",
" <td>0.114</td>\n",
" <td>0.200</td>\n",
" <td>0.714</td>\n",
" <td>0.121</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sqft_above</th>\n",
" <td>-0.011</td>\n",
" <td>0.605</td>\n",
" <td>0.479</td>\n",
" <td>0.687</td>\n",
" <td>0.876</td>\n",
" <td>0.184</td>\n",
" <td>0.524</td>\n",
" <td>0.075</td>\n",
" <td>0.166</td>\n",
" <td>-0.159</td>\n",
" <td>0.756</td>\n",
" <td>1.000</td>\n",
" <td>0.424</td>\n",
" <td>0.022</td>\n",
" <td>-0.262</td>\n",
" <td>-0.001</td>\n",
" <td>0.345</td>\n",
" <td>0.732</td>\n",
" <td>0.195</td>\n",
" </tr>\n",
" <tr>\n",
" <th>yr_built</th>\n",
" <td>0.022</td>\n",
" <td>0.054</td>\n",
" <td>0.156</td>\n",
" <td>0.507</td>\n",
" <td>0.318</td>\n",
" <td>0.053</td>\n",
" <td>0.489</td>\n",
" <td>-0.026</td>\n",
" <td>-0.055</td>\n",
" <td>-0.362</td>\n",
" <td>0.448</td>\n",
" <td>0.424</td>\n",
" <td>1.000</td>\n",
" <td>-0.225</td>\n",
" <td>-0.347</td>\n",
" <td>-0.148</td>\n",
" <td>0.410</td>\n",
" <td>0.326</td>\n",
" <td>0.071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>yr_renovated</th>\n",
" <td>-0.012</td>\n",
" <td>0.130</td>\n",
" <td>0.018</td>\n",
" <td>0.051</td>\n",
" <td>0.056</td>\n",
" <td>0.005</td>\n",
" <td>0.004</td>\n",
" <td>0.087</td>\n",
" <td>0.101</td>\n",
" <td>-0.062</td>\n",
" <td>0.017</td>\n",
" <td>0.022</td>\n",
" <td>-0.225</td>\n",
" <td>1.000</td>\n",
" <td>0.070</td>\n",
" <td>0.032</td>\n",
" <td>-0.072</td>\n",
" <td>-0.000</td>\n",
" <td>0.004</td>\n",
" </tr>\n",
" <tr>\n",
" <th>zipcode</th>\n",
" <td>-0.008</td>\n",
" <td>-0.053</td>\n",
" <td>-0.154</td>\n",
" <td>-0.205</td>\n",
" <td>-0.200</td>\n",
" <td>-0.130</td>\n",
" <td>-0.060</td>\n",
" <td>0.031</td>\n",
" <td>0.085</td>\n",
" <td>0.003</td>\n",
" <td>-0.186</td>\n",
" <td>-0.262</td>\n",
" <td>-0.347</td>\n",
" <td>0.070</td>\n",
" <td>1.000</td>\n",
" <td>0.267</td>\n",
" <td>-0.564</td>\n",
" <td>-0.279</td>\n",
" <td>-0.147</td>\n",
" </tr>\n",
" <tr>\n",
" <th>lat</th>\n",
" <td>-0.002</td>\n",
" <td>0.307</td>\n",
" <td>-0.010</td>\n",
" <td>0.024</td>\n",
" <td>0.052</td>\n",
" <td>-0.086</td>\n",
" <td>0.049</td>\n",
" <td>-0.013</td>\n",
" <td>0.006</td>\n",
" <td>-0.015</td>\n",
" <td>0.114</td>\n",
" <td>-0.001</td>\n",
" <td>-0.148</td>\n",
" <td>0.032</td>\n",
" <td>0.267</td>\n",
" <td>1.000</td>\n",
" <td>-0.135</td>\n",
" <td>0.049</td>\n",
" <td>-0.086</td>\n",
" </tr>\n",
" <tr>\n",
" <th>long</th>\n",
" <td>0.021</td>\n",
" <td>0.022</td>\n",
" <td>0.132</td>\n",
" <td>0.225</td>\n",
" <td>0.241</td>\n",
" <td>0.230</td>\n",
" <td>0.126</td>\n",
" <td>-0.040</td>\n",
" <td>-0.078</td>\n",
" <td>-0.106</td>\n",
" <td>0.200</td>\n",
" <td>0.345</td>\n",
" <td>0.410</td>\n",
" <td>-0.072</td>\n",
" <td>-0.564</td>\n",
" <td>-0.135</td>\n",
" <td>1.000</td>\n",
" <td>0.336</td>\n",
" <td>0.256</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sqft_living15</th>\n",
" <td>-0.003</td>\n",
" <td>0.585</td>\n",
" <td>0.393</td>\n",
" <td>0.570</td>\n",
" <td>0.756</td>\n",
" <td>0.145</td>\n",
" <td>0.280</td>\n",
" <td>0.089</td>\n",
" <td>0.280</td>\n",
" <td>-0.093</td>\n",
" <td>0.714</td>\n",
" <td>0.732</td>\n",
" <td>0.326</td>\n",
" <td>-0.000</td>\n",
" <td>-0.279</td>\n",
" <td>0.049</td>\n",
" <td>0.336</td>\n",
" <td>1.000</td>\n",
" <td>0.184</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sqft_lot15</th>\n",
" <td>-0.139</td>\n",
" <td>0.083</td>\n",
" <td>0.031</td>\n",
" <td>0.088</td>\n",
" <td>0.184</td>\n",
" <td>0.718</td>\n",
" <td>-0.011</td>\n",
" <td>0.032</td>\n",
" <td>0.073</td>\n",
" <td>-0.003</td>\n",
" <td>0.121</td>\n",
" <td>0.195</td>\n",
" <td>0.071</td>\n",
" <td>0.004</td>\n",
" <td>-0.147</td>\n",
" <td>-0.086</td>\n",
" <td>0.256</td>\n",
" <td>0.184</td>\n",
" <td>1.000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id price bedrooms bathrooms sqft_living sqft_lot floors waterfront view condition grade sqft_above yr_built yr_renovated zipcode lat long sqft_living15 sqft_lot15\n",
"id 1.000 -0.017 0.001 0.005 -0.012 -0.132 0.019 -0.004 0.012 -0.024 0.008 -0.011 0.022 -0.012 -0.008 -0.002 0.021 -0.003 -0.139\n",
"price -0.017 1.000 0.309 0.526 0.702 0.090 0.257 0.276 0.396 0.036 0.668 0.605 0.054 0.130 -0.053 0.307 0.022 0.585 0.083\n",
"bedrooms 0.001 0.309 1.000 0.515 0.578 0.032 0.178 -0.002 0.079 0.026 0.357 0.479 0.156 0.018 -0.154 -0.010 0.132 0.393 0.031\n",
"bathrooms 0.005 0.526 0.515 1.000 0.756 0.088 0.503 0.067 0.186 -0.126 0.666 0.687 0.507 0.051 -0.205 0.024 0.225 0.570 0.088\n",
"sqft_living -0.012 0.702 0.578 0.756 1.000 0.173 0.354 0.110 0.283 -0.059 0.763 0.876 0.318 0.056 -0.200 0.052 0.241 0.756 0.184\n",
"sqft_lot -0.132 0.090 0.032 0.088 0.173 1.000 -0.005 0.023 0.075 -0.009 0.115 0.184 0.053 0.005 -0.130 -0.086 0.230 0.145 0.718\n",
"floors 0.019 0.257 0.178 0.503 0.354 -0.005 1.000 0.022 0.028 -0.264 0.459 0.524 0.489 0.004 -0.060 0.049 0.126 0.280 -0.011\n",
"waterfront -0.004 0.276 -0.002 0.067 0.110 0.023 0.022 1.000 0.407 0.018 0.087 0.075 -0.026 0.087 0.031 -0.013 -0.040 0.089 0.032\n",
"view 0.012 0.396 0.079 0.186 0.283 0.075 0.028 0.407 1.000 0.046 0.250 0.166 -0.055 0.101 0.085 0.006 -0.078 0.280 0.073\n",
"condition -0.024 0.036 0.026 -0.126 -0.059 -0.009 -0.264 0.018 0.046 1.000 -0.147 -0.159 -0.362 -0.062 0.003 -0.015 -0.106 -0.093 -0.003\n",
"grade 0.008 0.668 0.357 0.666 0.763 0.115 0.459 0.087 0.250 -0.147 1.000 0.756 0.448 0.017 -0.186 0.114 0.200 0.714 0.121\n",
"sqft_above -0.011 0.605 0.479 0.687 0.876 0.184 0.524 0.075 0.166 -0.159 0.756 1.000 0.424 0.022 -0.262 -0.001 0.345 0.732 0.195\n",
"yr_built 0.022 0.054 0.156 0.507 0.318 0.053 0.489 -0.026 -0.055 -0.362 0.448 0.424 1.000 -0.225 -0.347 -0.148 0.410 0.326 0.071\n",
"yr_renovated -0.012 0.130 0.018 0.051 0.056 0.005 0.004 0.087 0.101 -0.062 0.017 0.022 -0.225 1.000 0.070 0.032 -0.072 -0.000 0.004\n",
"zipcode -0.008 -0.053 -0.154 -0.205 -0.200 -0.130 -0.060 0.031 0.085 0.003 -0.186 -0.262 -0.347 0.070 1.000 0.267 -0.564 -0.279 -0.147\n",
"lat -0.002 0.307 -0.010 0.024 0.052 -0.086 0.049 -0.013 0.006 -0.015 0.114 -0.001 -0.148 0.032 0.267 1.000 -0.135 0.049 -0.086\n",
"long 0.021 0.022 0.132 0.225 0.241 0.230 0.126 -0.040 -0.078 -0.106 0.200 0.345 0.410 -0.072 -0.564 -0.135 1.000 0.336 0.256\n",
"sqft_living15 -0.003 0.585 0.393 0.570 0.756 0.145 0.280 0.089 0.280 -0.093 0.714 0.732 0.326 -0.000 -0.279 0.049 0.336 1.000 0.184\n",
"sqft_lot15 -0.139 0.083 0.031 0.088 0.184 0.718 -0.011 0.032 0.073 -0.003 0.121 0.195 0.071 0.004 -0.147 -0.086 0.256 0.184 1.000"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.corr() # Correlation"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"view\n",
"0.000 496806.066\n",
"1.000 813373.267\n",
"2.000 791390.371\n",
"3.000 973285.197\n",
"4.000 1452465.883\n",
"Name: price, dtype: float64"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['price'].groupby([df['view']]).mean() # Mean values for different views"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"def fun_fill(price):\n",
" '''Return type based on price'''\n",
" if price < 496806:\n",
" return 0\n",
" elif price < 791390 and price >= 496806:\n",
" return 2\n",
" elif price < 813373 and price >= 791390:\n",
" return 1\n",
" elif price < 973285 and price >= 813373:\n",
" return 2\n",
" elif price > 973285:\n",
" return 4"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"df['view'].loc[df['view'].isnull()] = df['price'][df['view'].isnull()].apply(fun_fill) # Filling missing values"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Fill missing values in `waterfront` column by mode"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.000 19075\n",
"1.000 146\n",
"Name: waterfront, dtype: int64"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['waterfront'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"df['waterfront'].fillna(df['waterfront'].mode()[0],inplace=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Fill missing values in `yr_renovated` by 0\n",
"as when the renovation not done value is 0 and if the renovation is done we don't know the exact year."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.000 17011\n",
"2014.000 73\n",
"2003.000 31\n",
"2013.000 31\n",
"2007.000 30\n",
"2000.000 29\n",
"2005.000 29\n",
"1990.000 22\n",
"2004.000 22\n",
"2009.000 21\n",
"Name: yr_renovated, dtype: int64"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['yr_renovated'].value_counts().iloc[:10] # Showing value counts for first 10"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"df['yr_renovated'].fillna(0,inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"id 0\n",
"date 0\n",
"price 0\n",
"bedrooms 0\n",
"bathrooms 0\n",
"sqft_living 0\n",
"sqft_lot 0\n",
"floors 0\n",
"waterfront 0\n",
"view 0\n",
"condition 0\n",
"grade 0\n",
"sqft_above 0\n",
"sqft_basement 0\n",
"yr_built 0\n",
"yr_renovated 0\n",
"zipcode 0\n",
"lat 0\n",
"long 0\n",
"sqft_living15 0\n",
"sqft_lot15 0\n",
"dtype: int64"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[df.columns].isnull().sum() # Count of Null Values in each column"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Checking Outliers in `price`"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 720x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig1, ax1 = plt.subplots(figsize=(10,6))\n",
"green_diamond = dict(markerfacecolor='g', marker='D')\n",
"ax1.set_title('Basic Plot')\n",
"ax1.boxplot(df['price'], notch=True, flierprops=green_diamond, vert=False)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### We shouldn't remove these outliers.\n",
"As price of house could increase drastically based on locality, sqft, condition. So, we shouldn't drop or impute these outlier values."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get address using bing api from latitude and longitude\n",
"\n",
"`Note:` Don't run these 8 cells again if you already have the Locations.csv"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"def get_address(string):\n",
" try:\n",
" location = geolocator.reverse(string,timeout=10)\n",
" return location.address\n",
" except:\n",
" time.sleep(10)\n",
" try:\n",
" location = geolocator.reverse(string,timeout=10)\n",
" return location.address\n",
" except:\n",
" return 'Not available'"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"df['lat'] = df['lat'].round(2) # rounding Off\n",
"df['long'] = df['long'].round(2)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"temp = df['lat'].astype('str') + ', ' + df['long'].astype('str')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"temp.drop_duplicates(inplace=True) # Remove duplicate values"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"temp.reset_index(drop=True,inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d4bb393a11174dc789a8d20b7b78f88c",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(IntProgress(value=0, max=1974), HTML(value='')))"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"result = [] #666\n",
"for i in tqdm_notebook(range(len(result),len(temp))):\n",
" res = get_address(temp[i])\n",
" result.append(res)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"loc = pd.DataFrame()\n",
"loc['lat_long'] = temp\n",
"loc['address'] = result"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"loc.to_csv('Locations.csv',index=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Read address and map with coordinates"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"loc = pd.read_csv('Locations.csv')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"df['lat'] = df['lat'].round(2) # rounding Off\n",
"df['long'] = df['long'].round(2)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"temp = loc['lat_long'].str.split(',')\n",
"loc['lat'] = temp.str.get(0)\n",
"loc['long'] = temp.str.get(1)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"df['lat'] = df['lat'].astype('str') \n",
"df['long'] = df['long'].astype('str')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"loc = loc[loc.columns[1:]]"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"loc['long'] = loc['long'].str.strip()"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"df = pd.merge(df,loc,on=['lat','long'],how='left')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### sqft_basement have some `?`"
]
},
{
"cell_type": "code",
"execution_count": 29,
"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>id</th>\n",
" <th>date</th>\n",
" <th>price</th>\n",
" <th>bedrooms</th>\n",
" <th>bathrooms</th>\n",
" <th>sqft_living</th>\n",
" <th>sqft_lot</th>\n",
" <th>floors</th>\n",
" <th>waterfront</th>\n",
" <th>view</th>\n",
" <th>condition</th>\n",
" <th>grade</th>\n",
" <th>sqft_above</th>\n",
" <th>sqft_basement</th>\n",
" <th>yr_built</th>\n",
" <th>yr_renovated</th>\n",
" <th>zipcode</th>\n",
" <th>lat</th>\n",
" <th>long</th>\n",
" <th>sqft_living15</th>\n",
" <th>sqft_lot15</th>\n",
" <th>address</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>1321400060</td>\n",
" <td>6/27/2014</td>\n",
" <td>257500.000</td>\n",
" <td>3</td>\n",
" <td>2.250</td>\n",
" <td>1715</td>\n",
" <td>6819</td>\n",
" <td>2.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>7</td>\n",
" <td>1715</td>\n",
" <td>?</td>\n",
" <td>1995</td>\n",
" <td>0.000</td>\n",
" <td>98003</td>\n",
" <td>47.31</td>\n",
" <td>-122.33</td>\n",
" <td>2238</td>\n",
" <td>6819</td>\n",
" <td>330 S 327th Ln, Federal Way, WA 98003, United ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>16000397</td>\n",
" <td>12/5/2014</td>\n",
" <td>189000.000</td>\n",
" <td>2</td>\n",
" <td>1.000</td>\n",
" <td>1200</td>\n",
" <td>9850</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>4</td>\n",
" <td>7</td>\n",
" <td>1200</td>\n",
" <td>?</td>\n",
" <td>1921</td>\n",
" <td>0.000</td>\n",
" <td>98002</td>\n",
" <td>47.31</td>\n",
" <td>-122.21</td>\n",
" <td>1060</td>\n",
" <td>5095</td>\n",
" <td>201 Pike St NE, Auburn, WA 98002, United States</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>7203220400</td>\n",
" <td>7/7/2014</td>\n",
" <td>861990.000</td>\n",
" <td>5</td>\n",
" <td>2.750</td>\n",
" <td>3595</td>\n",
" <td>5639</td>\n",
" <td>2.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>9</td>\n",
" <td>3595</td>\n",
" <td>?</td>\n",
" <td>2014</td>\n",
" <td>0.000</td>\n",
" <td>98053</td>\n",
" <td>47.68</td>\n",
" <td>-122.02</td>\n",
" <td>3625</td>\n",
" <td>5639</td>\n",
" <td>8824 237th Pl NE, Union Hill-Novelty Hill, WA ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>79</th>\n",
" <td>1531000030</td>\n",
" <td>3/23/2015</td>\n",
" <td>720000.000</td>\n",
" <td>4</td>\n",
" <td>2.500</td>\n",
" <td>3450</td>\n",
" <td>39683</td>\n",
" <td>2.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>10</td>\n",
" <td>3450</td>\n",
" <td>?</td>\n",
" <td>2002</td>\n",
" <td>0.000</td>\n",
" <td>98010</td>\n",
" <td>47.34</td>\n",
" <td>-122.02</td>\n",
" <td>3350</td>\n",
" <td>39750</td>\n",
" <td>Green River To Cedar River Trail, Maple Valley...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>112</th>\n",
" <td>2525310310</td>\n",
" <td>9/16/2014</td>\n",
" <td>272500.000</td>\n",
" <td>3</td>\n",
" <td>1.750</td>\n",
" <td>1540</td>\n",
" <td>12600</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>4</td>\n",
" <td>7</td>\n",
" <td>1160</td>\n",
" <td>?</td>\n",
" <td>1980</td>\n",
" <td>0.000</td>\n",
" <td>98038</td>\n",
" <td>47.36</td>\n",
" <td>-122.03</td>\n",
" <td>1540</td>\n",
" <td>11656</td>\n",
" <td>26914 233rd Pl SE, Maple Valley, WA 98038, Uni...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id date price bedrooms bathrooms sqft_living sqft_lot floors waterfront view condition grade sqft_above sqft_basement yr_built yr_renovated zipcode lat long sqft_living15 sqft_lot15 address\n",
"6 1321400060 6/27/2014 257500.000 3 2.250 1715 6819 2.000 0.000 0.000 3 7 1715 ? 1995 0.000 98003 47.31 -122.33 2238 6819 330 S 327th Ln, Federal Way, WA 98003, United ...\n",
"18 16000397 12/5/2014 189000.000 2 1.000 1200 9850 1.000 0.000 0.000 4 7 1200 ? 1921 0.000 98002 47.31 -122.21 1060 5095 201 Pike St NE, Auburn, WA 98002, United States\n",
"42 7203220400 7/7/2014 861990.000 5 2.750 3595 5639 2.000 0.000 0.000 3 9 3595 ? 2014 0.000 98053 47.68 -122.02 3625 5639 8824 237th Pl NE, Union Hill-Novelty Hill, WA ...\n",
"79 1531000030 3/23/2015 720000.000 4 2.500 3450 39683 2.000 0.000 0.000 3 10 3450 ? 2002 0.000 98010 47.34 -122.02 3350 39750 Green River To Cedar River Trail, Maple Valley...\n",
"112 2525310310 9/16/2014 272500.000 3 1.750 1540 12600 1.000 0.000 0.000 4 7 1160 ? 1980 0.000 98038 47.36 -122.03 1540 11656 26914 233rd Pl SE, Maple Valley, WA 98038, Uni..."
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[df['sqft_basement'] == '?'].head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Considering `?` as null and fill with `0`."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"df['sqft_basement'] = df['sqft_basement'].str.replace('?','0')"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"df['sqft_basement'] = df['sqft_basement'].astype('float')"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"df.to_csv('clean_data.csv',index=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Data Exploration"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp = df['price'].groupby([df['date']]).mean()\n",
"temp.index = pd.to_datetime(temp.index)\n",
"temp.plot(figsize=(15,7),title='Avg. House Price based on time')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp = df['price'].groupby([df['sqft_living']]).mean()\n",
"temp.plot(figsize=(15,7),title='Avg. House Price based on Sqft.')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp = df['price'].groupby([df['zipcode']]).mean()\n",
"temp = temp.sort_values(ascending=False)[:10]\n",
"temp.plot(kind='bar',figsize=(15,7),title='Top 10 areas with max. Avg. House Price')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp = df['price'].groupby([df['zipcode']]).mean()\n",
"temp = temp.sort_values(ascending=False)[-10:]\n",
"temp.plot(kind='bar',figsize=(15,7),title='Bottom 10 areas with min. Avg. House Price')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp = df['price'].groupby([df['grade'], df['condition']]).mean().unstack()\n",
"temp.plot(kind='bar',figsize=(15,7),title='Avg. House Price in different grade and condition.')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"df['renovated'] = np.where(df['yr_renovated'] > 0, True, False) # To find renovation has been done or not."
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp = df['price'].groupby([df['sqft_living'],df['renovated']]).mean().unstack()\n",
"temp.plot(figsize=(15,7),title='Avg. House Price based on Sqft. and Renovation')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp = df['price'].groupby([df['date'],df['renovated']]).mean().unstack()\n",
"temp.index = pd.to_datetime(temp.index)\n",
"temp.plot(figsize=(15,7),title='Avg. House Price based on time',color=['blue','red'])\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x1008 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(15, 14))\n",
"plt.subplot(2, 1, 1)\n",
"temp.iloc[:,0].plot(title='Avg. House Price based on time Without renovation')\n",
"plt.legend(loc='best')\n",
"plt.subplot(2, 1, 2)\n",
"temp.iloc[:,1].plot(title='Avg. House Price based on time With renovation',color='red')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"temp = df['price'].groupby([df['bedrooms'], df['floors']]).mean().unstack()\n",
"temp.plot(kind='bar',figsize=(15,7),title='Avg. House Price in different floors and bedrooms.')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2.500 5377\n",
"1.000 3851\n",
"1.750 3048\n",
"2.250 2047\n",
"2.000 1930\n",
"1.500 1445\n",
"2.750 1185\n",
"3.000 753\n",
"3.500 731\n",
"3.250 589\n",
"3.750 155\n",
"4.000 136\n",
"4.500 100\n",
"4.250 79\n",
"0.750 71\n",
"4.750 23\n",
"5.000 21\n",
"5.250 13\n",
"5.500 10\n",
"1.250 9\n",
"6.000 6\n",
"5.750 4\n",
"0.500 4\n",
"8.000 2\n",
"6.250 2\n",
"6.750 2\n",
"6.500 2\n",
"7.500 1\n",
"7.750 1\n",
"Name: bathrooms, dtype: int64"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['bathrooms'].value_counts() # Checking different size bathrooms"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Here we find bathrooms are in decimals but there are many such cases where the bathrooms is in with 0.25,0.50,0.75. So, we can't impute and change the values."
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 936x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df['bathrooms'].value_counts().plot(kind='bar',title='Houses with different Bathroom sizes',figsize=(13,7))\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Data Preparation for modelling"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"df['date'] = pd.to_datetime(df['date'])\n",
"\n",
"df['Day'] = df['date'].dt.day.values\n",
"df['Week'] = df['date'].dt.week.values\n",
"df['WeekDay'] = df['date'].dt.weekday.values\n",
"df['month'] = df['date'].dt.month.values\n",
"df['year'] = df['date'].dt.year.values"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"795000620 3\n",
"1825069031 2\n",
"2019200220 2\n",
"7129304540 2\n",
"1781500435 2\n",
"3969300030 2\n",
"2560801222 2\n",
"3883800011 2\n",
"2228900270 2\n",
"251300110 2\n",
"Name: id, dtype: int64"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['id'].value_counts()[:10]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are some house id's which appear more than 1 times. Still for modelling considering same id's multiple times as the price were given at different time and conditions."
]
},
{
"cell_type": "code",
"execution_count": 47,
"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>id</th>\n",
" <th>date</th>\n",
" <th>price</th>\n",
" <th>bedrooms</th>\n",
" <th>bathrooms</th>\n",
" <th>sqft_living</th>\n",
" <th>sqft_lot</th>\n",
" <th>floors</th>\n",
" <th>waterfront</th>\n",
" <th>view</th>\n",
" <th>condition</th>\n",
" <th>grade</th>\n",
" <th>sqft_above</th>\n",
" <th>sqft_basement</th>\n",
" <th>yr_built</th>\n",
" <th>yr_renovated</th>\n",
" <th>zipcode</th>\n",
" <th>lat</th>\n",
" <th>long</th>\n",
" <th>sqft_living15</th>\n",
" <th>sqft_lot15</th>\n",
" <th>address</th>\n",
" <th>renovated</th>\n",
" <th>Day</th>\n",
" <th>Week</th>\n",
" <th>WeekDay</th>\n",
" <th>month</th>\n",
" <th>year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>7129300520</td>\n",
" <td>2014-10-13</td>\n",
" <td>221900.000</td>\n",
" <td>3</td>\n",
" <td>1.000</td>\n",
" <td>1180</td>\n",
" <td>5650</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>7</td>\n",
" <td>1180</td>\n",
" <td>0.000</td>\n",
" <td>1955</td>\n",
" <td>0.000</td>\n",
" <td>98178</td>\n",
" <td>47.51</td>\n",
" <td>-122.26</td>\n",
" <td>1340</td>\n",
" <td>5650</td>\n",
" <td>5746 S Ryan St, Rainier Beach, WA 98178, Unite...</td>\n",
" <td>False</td>\n",
" <td>13</td>\n",
" <td>42</td>\n",
" <td>0</td>\n",
" <td>10</td>\n",
" <td>2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>6414100192</td>\n",
" <td>2014-12-09</td>\n",
" <td>538000.000</td>\n",
" <td>3</td>\n",
" <td>2.250</td>\n",
" <td>2570</td>\n",
" <td>7242</td>\n",
" <td>2.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>7</td>\n",
" <td>2170</td>\n",
" <td>400.000</td>\n",
" <td>1951</td>\n",
" <td>1991.000</td>\n",
" <td>98125</td>\n",
" <td>47.72</td>\n",
" <td>-122.32</td>\n",
" <td>1690</td>\n",
" <td>7639</td>\n",
" <td>12526 8th Ave NE, Pinehurst, WA 98125, United ...</td>\n",
" <td>True</td>\n",
" <td>9</td>\n",
" <td>50</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" <td>2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5631500400</td>\n",
" <td>2015-02-25</td>\n",
" <td>180000.000</td>\n",
" <td>2</td>\n",
" <td>1.000</td>\n",
" <td>770</td>\n",
" <td>10000</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>6</td>\n",
" <td>770</td>\n",
" <td>0.000</td>\n",
" <td>1933</td>\n",
" <td>0.000</td>\n",
" <td>98028</td>\n",
" <td>47.74</td>\n",
" <td>-122.23</td>\n",
" <td>2720</td>\n",
" <td>8062</td>\n",
" <td>8315 NE 155th St, Kenmore, WA 98028, United St...</td>\n",
" <td>False</td>\n",
" <td>25</td>\n",
" <td>9</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2015</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2487200875</td>\n",
" <td>2014-12-09</td>\n",
" <td>604000.000</td>\n",
" <td>4</td>\n",
" <td>3.000</td>\n",
" <td>1960</td>\n",
" <td>5000</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>5</td>\n",
" <td>7</td>\n",
" <td>1050</td>\n",
" <td>910.000</td>\n",
" <td>1965</td>\n",
" <td>0.000</td>\n",
" <td>98136</td>\n",
" <td>47.52</td>\n",
" <td>-122.39</td>\n",
" <td>1360</td>\n",
" <td>5000</td>\n",
" <td>4419 SW Brace Point Dr, Fauntleroy, WA 98136, ...</td>\n",
" <td>False</td>\n",
" <td>9</td>\n",
" <td>50</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" <td>2014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1954400510</td>\n",
" <td>2015-02-18</td>\n",
" <td>510000.000</td>\n",
" <td>3</td>\n",
" <td>2.000</td>\n",
" <td>1680</td>\n",
" <td>8080</td>\n",
" <td>1.000</td>\n",
" <td>0.000</td>\n",
" <td>0.000</td>\n",
" <td>3</td>\n",
" <td>8</td>\n",
" <td>1680</td>\n",
" <td>0.000</td>\n",
" <td>1987</td>\n",
" <td>0.000</td>\n",
" <td>98074</td>\n",
" <td>47.62</td>\n",
" <td>-122.04</td>\n",
" <td>1800</td>\n",
" <td>7503</td>\n",
" <td>22460 NE 10th St, Sammamish, WA 98074, United ...</td>\n",
" <td>False</td>\n",
" <td>18</td>\n",
" <td>8</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2015</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id date price bedrooms bathrooms sqft_living sqft_lot floors waterfront view condition grade sqft_above sqft_basement yr_built yr_renovated zipcode lat long sqft_living15 sqft_lot15 address renovated Day Week WeekDay month year\n",
"0 7129300520 2014-10-13 221900.000 3 1.000 1180 5650 1.000 0.000 0.000 3 7 1180 0.000 1955 0.000 98178 47.51 -122.26 1340 5650 5746 S Ryan St, Rainier Beach, WA 98178, Unite... False 13 42 0 10 2014\n",
"1 6414100192 2014-12-09 538000.000 3 2.250 2570 7242 2.000 0.000 0.000 3 7 2170 400.000 1951 1991.000 98125 47.72 -122.32 1690 7639 12526 8th Ave NE, Pinehurst, WA 98125, United ... True 9 50 1 12 2014\n",
"2 5631500400 2015-02-25 180000.000 2 1.000 770 10000 1.000 0.000 0.000 3 6 770 0.000 1933 0.000 98028 47.74 -122.23 2720 8062 8315 NE 155th St, Kenmore, WA 98028, United St... False 25 9 2 2 2015\n",
"3 2487200875 2014-12-09 604000.000 4 3.000 1960 5000 1.000 0.000 0.000 5 7 1050 910.000 1965 0.000 98136 47.52 -122.39 1360 5000 4419 SW Brace Point Dr, Fauntleroy, WA 98136, ... False 9 50 1 12 2014\n",
"4 1954400510 2015-02-18 510000.000 3 2.000 1680 8080 1.000 0.000 0.000 3 8 1680 0.000 1987 0.000 98074 47.62 -122.04 1800 7503 22460 NE 10th St, Sammamish, WA 98074, United ... False 18 8 2 2 2015"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Finding house locality\n",
"\n",
"Full address fetched from bing can be break into 4 types."
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
"temp = df['address'].str.split(',')\n",
"df['locality_1'] = temp.str.get(-4)\n",
"df['locality_2'] = temp.str.get(-3)\n",
"df['locality_3'] = temp.str.get(-2)\n",
"df['locality_4'] = temp.str.get(-1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### check top 10 locality of each type"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"I-90 E 90\n",
"2425 NE Larchmount St 83\n",
"3710 SW Southern St 75\n",
"137 25th Ave E 73\n",
"7019 26th Ave NW 70\n",
"702 N 97th St 70\n",
"7008 3rd Ave NW 68\n",
"7011 18th Ave NW 65\n",
"826 25th Ave 65\n",
"3743 Belvidere Ave SW 64\n",
"Name: locality_1, dtype: int64"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['locality_1'].value_counts()[:10]"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" Renton 1026\n",
" Sammamish 932\n",
" Federal Way 665\n",
" Kent 625\n",
" Shoreline 557\n",
" Maple Valley 526\n",
" Union Hill-Novelty Hill 404\n",
" Auburn 399\n",
" Highline 366\n",
" East Hill-Meridian 351\n",
"Name: locality_2, dtype: int64"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['locality_2'].value_counts()[:10]"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" WA 98117 629\n",
" WA 98103 618\n",
" WA 98052 583\n",
" WA 98034 556\n",
" WA 98042 556\n",
" WA 98038 554\n",
" WA 98115 547\n",
" WA 98126 515\n",
" WA 98059 477\n",
" WA 98023 472\n",
"Name: locality_3, dtype: int64"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['locality_3'].value_counts()[:10]"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" United States 21597\n",
"Name: locality_4, dtype: int64"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['locality_4'].value_counts()[:10]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here as we can see in last type only one country `United States` is present. So, this column didn't give us anything meaningful in modelling.\n",
"\n",
"`Locality_3` is also same as `zipcode`. So may not consider any one column in features."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Selecting the features."
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"features = ['bedrooms','bathrooms','sqft_living','sqft_lot','floors','waterfront','view','condition','grade',\n",
" 'sqft_above','sqft_basement','yr_built','yr_renovated','zipcode','sqft_living15','sqft_lot15',\n",
" 'renovated','Day','Week','WeekDay','month','year','locality_1','locality_2']"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"df['renovated'] = df['renovated'].astype('int') # Changing bool type to int"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"df['locality_1'].fillna('',inplace=True)\n",
"df['locality_2'].fillna('',inplace=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Using `Label Encoder` to encode locality column class values to integer"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [],
"source": [
"le = preprocessing.LabelEncoder()"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [],
"source": [
"le.fit(df['locality_1'])\n",
"df['locality_1'] = le.transform(df['locality_1'])"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
"le.fit(df['locality_2'])\n",
"df['locality_2'] = le.transform(df['locality_2'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### `Classes` in each column"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"bedrooms 12\n",
"bathrooms 29\n",
"sqft_living 1034\n",
"sqft_lot 9776\n",
"floors 6\n",
"waterfront 2\n",
"view 5\n",
"condition 5\n",
"grade 11\n",
"sqft_above 942\n",
"sqft_basement 303\n",
"yr_built 116\n",
"yr_renovated 70\n",
"zipcode 70\n",
"sqft_living15 777\n",
"sqft_lot15 8682\n",
"renovated 2\n",
"Day 31\n",
"Week 52\n",
"WeekDay 7\n",
"month 12\n",
"year 2\n",
"locality_1 1884\n",
"locality_2 212\n",
"dtype: int64"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[features].nunique()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. Modelling "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Checking cross validation on Random Forest."
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [],
"source": [
"model = RandomForestRegressor(max_depth=6, random_state=0,n_jobs=-1,\n",
" n_estimators=100)\n",
"\n",
"results = cross_val_score(model, df[features], df['price'], cv=3, n_jobs=-1,scoring='mean_squared_error')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Scores(RMSE) in each fold."
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[197081.31489784172, 188161.47458932866, 201429.77488234517]"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sqrt(-results).tolist()"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"195557.52145650517"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sqrt(-results).mean() # Average"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Avg. **RMSE** error from Random Forest."
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'Feature Importance Score')"
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"model.fit(df[features],df['price'])\n",
"feature = pd.DataFrame(model.feature_importances_,features)\n",
"feature = feature.sort_values(by=0,ascending=False)\n",
"\n",
"feature.plot(kind='bar', title='Feature Importances',figsize=(15,8),color='red')\n",
"plt.ylabel('Feature Importance Score By Random Forest')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Checking cross validation on Xgboost."
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [],
"source": [
"model = XGBRegressor(max_depth=6, random_state=0,n_jobs=-1,\n",
" n_estimators=100)\n",
"results = cross_val_score(model, df[features], df['price'], cv=3, n_jobs=-1,scoring='mean_squared_error')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Scores(RMSE) in each fold."
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[144586.97291371762, 142203.88186014266, 150204.79558287642]"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sqrt(-results).tolist()"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"145665.2167855789"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sqrt(-results).mean() # Average"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Avg. RMSE error from Xgboost."
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'Feature Importance Score By Xgboost')"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"model.fit(df[features],df['price'])\n",
"feature = pd.DataFrame(model.feature_importances_,features)\n",
"feature = feature.sort_values(by=0,ascending=False)\n",
"\n",
"feature.plot(kind='bar', title='Feature Importances',figsize=(15,8),color='red')\n",
"plt.ylabel('Feature Importance Score By Xgboost')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Parameter Tuning on Xgboost Model. "
]
},
{
"cell_type": "code",
"execution_count": 113,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Wall time: 3min 32s\n"
]
}
],
"source": [
"%%time\n",
"\n",
"params = {\n",
" 'learning_rate': [0.05, 0.1, 0.2],\n",
" 'n_estimators' : [100,500],\n",
" 'max_depth' : [3,4,5],\n",
" 'n_jobs' : [-1]\n",
"}\n",
"gs = GridSearchCV(model, params, cv=5, n_jobs=-1,scoring='mean_squared_error')\n",
"gs.fit(df[features],df['price'])"
]
},
{
"cell_type": "code",
"execution_count": 114,
"metadata": {},
"outputs": [],
"source": [
"res_df = pd.DataFrame()\n",
"for i in range(len(gs.grid_scores_)):\n",
" temp = pd.DataFrame()\n",
" temp['mean'] = list([gs.grid_scores_[i][1]])\n",
" temp['learning_rate'] = list([gs.grid_scores_[i][0]['learning_rate']])\n",
" temp['max_depth'] = list([gs.grid_scores_[i][0]['max_depth']])\n",
" temp['n_estimators'] = list([gs.grid_scores_[i][0]['n_estimators']])\n",
" res_df = pd.concat([res_df,temp])"
]
},
{
"cell_type": "code",
"execution_count": 115,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>mean</th>\n",
" <th>learning_rate</th>\n",
" <th>max_depth</th>\n",
" <th>n_estimators</th>\n",
" </tr>\n",
" </thead>\n",
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" <th>0</th>\n",
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" <td>0.200</td>\n",
" <td>5</td>\n",
" <td>500</td>\n",
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" <td>0.100</td>\n",
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" <td>0.200</td>\n",
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" <td>500</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>132729.183</td>\n",
" <td>0.100</td>\n",
" <td>3</td>\n",
" <td>500</td>\n",
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" <td>4</td>\n",
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" <td>137831.497</td>\n",
" <td>0.200</td>\n",
" <td>4</td>\n",
" <td>100</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>141230.326</td>\n",
" <td>0.050</td>\n",
" <td>3</td>\n",
" <td>500</td>\n",
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" <td>0.200</td>\n",
" <td>3</td>\n",
" <td>100</td>\n",
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" <td>0.100</td>\n",
" <td>4</td>\n",
" <td>100</td>\n",
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" <tr>\n",
" <th>0</th>\n",
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" <td>0.050</td>\n",
" <td>5</td>\n",
" <td>100</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>159101.930</td>\n",
" <td>0.100</td>\n",
" <td>3</td>\n",
" <td>100</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>164531.500</td>\n",
" <td>0.050</td>\n",
" <td>4</td>\n",
" <td>100</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>177865.939</td>\n",
" <td>0.050</td>\n",
" <td>3</td>\n",
" <td>100</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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],
"text/plain": [
" mean learning_rate max_depth n_estimators\n",
"0 125683.968 0.200 4 500\n",
"0 127346.563 0.200 5 500\n",
"0 127464.607 0.100 5 500\n",
"0 128269.821 0.200 3 500\n",
"0 128402.392 0.100 4 500\n",
"0 129112.890 0.050 5 500\n",
"0 132729.183 0.100 3 500\n",
"0 133032.299 0.050 4 500\n",
"0 133254.806 0.200 5 100\n",
"0 137831.497 0.200 4 100\n",
"0 141230.326 0.050 3 500\n",
"0 142263.375 0.100 5 100\n",
"0 145704.155 0.200 3 100\n",
"0 148409.845 0.100 4 100\n",
"0 155842.707 0.050 5 100\n",
"0 159101.930 0.100 3 100\n",
"0 164531.500 0.050 4 100\n",
"0 177865.939 0.050 3 100"
]
},
"execution_count": 115,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res_df['mean'] = res_df['mean'] * -1\n",
"res_df['mean'] = np.sqrt(res_df['mean'])\n",
"res_df = res_df.sort_values(by='mean')\n",
"res_df"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Checking Cross-fold on parameter tuned model."
]
},
{
"cell_type": "code",
"execution_count": 117,
"metadata": {},
"outputs": [],
"source": [
"model = XGBRegressor(max_depth=4, random_state=0,n_jobs=-1,learning_rate=0.2,\n",
" n_estimators=500)\n",
"results = cross_val_score(model, df[features], df['price'], cv=3, n_jobs=-1,scoring='mean_squared_error')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Scores(RMSE) in each fold."
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[132091.3665708369, 124356.59335775704, 135269.60054681185]"
]
},
"execution_count": 118,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sqrt(-results).tolist()"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"130572.52015846859"
]
},
"execution_count": 119,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.sqrt(-results).mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Avg. RMSE error from parameter tuned Xgboost"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Checking cross validation on Catboost"
]
},
{
"cell_type": "code",
"execution_count": 133,
"metadata": {},
"outputs": [],
"source": [
"df['bathrooms'] = df['bathrooms'].astype('str')\n",
"df['yr_renovated'] = df['yr_renovated'].astype('str')\n",
"df['floors'] = df['floors'].astype('str')"
]
},
{
"cell_type": "code",
"execution_count": 138,
"metadata": {
"scrolled": false
},
"outputs": [
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y=v.selectAll(\"g.pointtext\").data(c?n:[]);y.enter().append(\"g\").classed(\"pointtext\",!0).append(\"text\").attr(\"transform\",\"translate(20,0)\"),y.exit().remove(),y.selectAll(\"text\").call(f.textPointStyle,a)}function o(t){var e=t[0].trace,r=e.marker||{},n=r.line||{},a=s.select(this).select(\"g.legendpoints\").selectAll(\"path.legendbar\").data(c.traceIs(e,\"bar\")?[t]:[]);a.enter().append(\"path\").classed(\"legendbar\",!0).attr(\"d\",\"M6,6H-6V-6H6Z\").attr(\"transform\",\"translate(20,0)\"),a.exit().remove(),a.each(function(t){var e=s.select(this),a=t[0],o=(a.mlw+1||n.width+1)-1;e.style(\"stroke-width\",o+\"px\").call(d.fill,a.mc||r.color),o&&e.call(d.stroke,a.mlc||n.color)})}function i(t){var e=t[0].trace,r=s.select(this).select(\"g.legendpoints\").selectAll(\"path.legendbox\").data(c.traceIs(e,\"box\")&&e.visible?[t]:[]);r.enter().append(\"path\").classed(\"legendbox\",!0).attr(\"d\",\"M6,6H-6V-6H6Z\").attr(\"transform\",\"translate(20,0)\"),r.exit().remove(),r.each(function(){var t=e.line.width,r=s.select(this);r.style(\"stroke-width\",t+\"px\").call(d.fill,e.fillcolor),t&&r.call(d.stroke,e.line.color)})}function l(t){var e=t[0].trace,r=s.select(this).select(\"g.legendpoints\").selectAll(\"path.legendpie\").data(c.traceIs(e,\"pie\")&&e.visible?[t]:[]);r.enter().append(\"path\").classed(\"legendpie\",!0).attr(\"d\",\"M6,6H-6V-6H6Z\").attr(\"transform\",\"translate(20,0)\"),r.exit().remove(),r.size()&&r.call(p,t[0],e)}var s=t(\"d3\"),c=t(\"../../registry\"),u=t(\"../../lib\"),f=t(\"../drawing\"),d=t(\"../color\"),h=t(\"../../traces/scatter/subtypes\"),p=t(\"../../traces/pie/style_one\");e.exports=function(t){t.each(function(t){var e=s.select(this),r=e.selectAll(\"g.layers\").data([0]);r.enter().append(\"g\").classed(\"layers\",!0),r.style(\"opacity\",t[0].trace.opacity),r.selectAll(\"g.legendfill\").data([t]).enter().append(\"g\").classed(\"legendfill\",!0),r.selectAll(\"g.legendlines\").data([t]).enter().append(\"g\").classed(\"legendlines\",!0);var n=r.selectAll(\"g.legendsymbols\").data([t]);n.enter().append(\"g\").classed(\"legendsymbols\",!0),n.selectAll(\"g.legendpoints\").data([t]).enter().append(\"g\").classed(\"legendpoints\",!0)}).each(o).each(i).each(l).each(n).each(a)}},{\"../../lib\":136,\"../../registry\":206,\"../../traces/pie/style_one\":238,\"../../traces/scatter/subtypes\":260,\"../color\":25,\"../drawing\":49,d3:7}],84:[function(t,e,r){\"use strict\";function n(t,e){var r,n,a=e.currentTarget,o=a.getAttribute(\"data-attr\"),i=a.getAttribute(\"data-val\")||!0,l=t._fullLayout,s={},c=d.list(t,null,!0),f=\"on\";if(\"zoom\"===o){var h,p=\"in\"===i?.5:2,g=(1+p)/2,v=(1-p)/2;for(n=0;n<c.length;n++)if(r=c[n],!r.fixedrange)if(h=r._name,\"auto\"===i)s[h+\".autorange\"]=!0;else if(\"reset\"===i){if(void 0===r._rangeInitial)s[h+\".autorange\"]=!0;else{var m=r._rangeInitial.slice();s[h+\".range[0]\"]=m[0],s[h+\".range[1]\"]=m[1]}void 0!==r._showSpikeInitial&&(s[h+\".showspikes\"]=r._showSpikeInitial,\"on\"!==f||r._showSpikeInitial||(f=\"off\"))}else{var y=[r.r2l(r.range[0]),r.r2l(r.range[1])],x=[g*y[0]+v*y[1],g*y[1]+v*y[0]];s[h+\".range[0]\"]=r.l2r(x[0]),s[h+\".range[1]\"]=r.l2r(x[1])}l._cartesianSpikesEnabled=f}else{if(\"hovermode\"!==o||\"x\"!==i&&\"y\"!==i){if(\"hovermode\"===o&&\"closest\"===i){for(n=0;n<c.length;n++)r=c[n],\"on\"!==f||r.showspikes||(f=\"off\");l._cartesianSpikesEnabled=f}}else i=l._isHoriz?\"y\":\"x\",a.setAttribute(\"data-val\",i),\"closest
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