├── images
    └── 1.png
├── README.md
├── .ipynb_checkpoints
    └── profit_estimation_of_companies-checkpoint.ipynb
├── profit_estimation_of_companies.ipynb
└── 1000_Companies.csv


/images/1.png:
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https://raw.githubusercontent.com/boosuro/profit_estimation_of_companies/HEAD/images/1.png


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/README.md:
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 1 | # profit estimation of companies using linear regression
 2 | 
 3 | profit estimation of companies with linear regression
 4 | 
 5 | ## Visualizing data before processing
 6 | 
 7 | ![Screenshot](images/1.png)
 8 | 
 9 | 
10 | ## r2_score
11 | 
12 | 0.9209536193310004
13 | 


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/.ipynb_checkpoints/profit_estimation_of_companies-checkpoint.ipynb:
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 1 | {
 2 |  "cells": [
 3 |   {
 4 |    "cell_type": "code",
 5 |    "execution_count": null,
 6 |    "metadata": {},
 7 |    "outputs": [],
 8 |    "source": []
 9 |   }
10 |  ],
11 |  "metadata": {
12 |   "kernelspec": {
13 |    "display_name": "Python 3",
14 |    "language": "python",
15 |    "name": "python3"
16 |   },
17 |   "language_info": {
18 |    "codemirror_mode": {
19 |     "name": "ipython",
20 |     "version": 3
21 |    },
22 |    "file_extension": ".py",
23 |    "mimetype": "text/x-python",
24 |    "name": "python",
25 |    "nbconvert_exporter": "python",
26 |    "pygments_lexer": "ipython3",
27 |    "version": "3.6.4"
28 |   }
29 |  },
30 |  "nbformat": 4,
31 |  "nbformat_minor": 2
32 | }
33 | 


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/profit_estimation_of_companies.ipynb:
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  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "# profit estimation of companies with linear regression"
  8 |    ]
  9 |   },
 10 |   {
 11 |    "cell_type": "code",
 12 |    "execution_count": 1,
 13 |    "metadata": {},
 14 |    "outputs": [],
 15 |    "source": [
 16 |     "#importing libraries\n",
 17 |     "import numpy as np\n",
 18 |     "import matplotlib.pyplot as plt\n",
 19 |     "import seaborn as sns\n",
 20 |     "import pandas as pd\n",
 21 |     "%matplotlib inline"
 22 |    ]
 23 |   },
 24 |   {
 25 |    "cell_type": "markdown",
 26 |    "metadata": {},
 27 |    "source": [
 28 |     "### loading the dataset"
 29 |    ]
 30 |   },
 31 |   {
 32 |    "cell_type": "code",
 33 |    "execution_count": 2,
 34 |    "outputs": [
 35 |     {
 36 |      "data": {
 37 |       "text/plain": "   R&D Spend  Administration  Marketing Spend       State     Profit\n0  165349.20       136897.80        471784.10    New York  192261.83\n1  162597.70       151377.59        443898.53  California  191792.06\n2  153441.51       101145.55        407934.54     Florida  191050.39\n3  144372.41       118671.85        383199.62    New York  182901.99\n4  142107.34        91391.77        366168.42     Florida  166187.94",
 38 |       "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>R&amp;D Spend</th>\n      <th>Administration</th>\n      <th>Marketing Spend</th>\n      <th>State</th>\n      <th>Profit</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>165349.20</td>\n      <td>136897.80</td>\n      <td>471784.10</td>\n      <td>New York</td>\n      <td>192261.83</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>162597.70</td>\n      <td>151377.59</td>\n      <td>443898.53</td>\n      <td>California</td>\n      <td>191792.06</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>153441.51</td>\n      <td>101145.55</td>\n      <td>407934.54</td>\n      <td>Florida</td>\n      <td>191050.39</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>144372.41</td>\n      <td>118671.85</td>\n      <td>383199.62</td>\n      <td>New York</td>\n      <td>182901.99</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>142107.34</td>\n      <td>91391.77</td>\n      <td>366168.42</td>\n      <td>Florida</td>\n      <td>166187.94</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
 39 |      },
 40 |      "execution_count": 2,
 41 |      "metadata": {},
 42 |      "output_type": "execute_result"
 43 |     }
 44 |    ],
 45 |    "source": [
 46 |     "companies = pd.read_csv('1000_Companies.csv')\n",
 47 |     "companies.head()"
 48 |    ],
 49 |    "metadata": {
 50 |     "collapsed": false,
 51 |     "pycharm": {
 52 |      "name": "#%%\n"
 53 |     }
 54 |    }
 55 |   },
 56 |   {
 57 |    "cell_type": "code",
 58 |    "source": [],
 59 |    "metadata": {
 60 |     "collapsed": false,
 61 |     "pycharm": {
 62 |      "name": "#%% \n"
 63 |     }
 64 |    },
 65 |    "execution_count": 2,
 66 |    "outputs": []
 67 |   },
 68 |   {
 69 |    "cell_type": "code",
 70 |    "execution_count": 2,
 71 |    "metadata": {
 72 |     "pycharm": {
 73 |      "name": "#%%\n"
 74 |     }
 75 |    },
 76 |    "outputs": [],
 77 |    "source": []
 78 |   },
 79 |   {
 80 |    "cell_type": "markdown",
 81 |    "metadata": {},
 82 |    "source": [
 83 |     "### Observing Correlation between Columns"
 84 |    ]
 85 |   },
 86 |   {
 87 |    "cell_type": "code",
 88 |    "execution_count": 3,
 89 |    "metadata": {},
 90 |    "outputs": [
 91 |     {
 92 |      "data": {
 93 |       "text/plain": "                 R&D Spend  Administration  Marketing Spend\nR&D Spend         1.000000        0.582434         0.978407\nAdministration    0.582434        1.000000         0.520465\nMarketing Spend   0.978407        0.520465         1.000000",
 94 |       "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>R&amp;D Spend</th>\n      <th>Administration</th>\n      <th>Marketing Spend</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>R&amp;D Spend</th>\n      <td>1.000000</td>\n      <td>0.582434</td>\n      <td>0.978407</td>\n    </tr>\n    <tr>\n      <th>Administration</th>\n      <td>0.582434</td>\n      <td>1.000000</td>\n      <td>0.520465</td>\n    </tr>\n    <tr>\n      <th>Marketing Spend</th>\n      <td>0.978407</td>\n      <td>0.520465</td>\n      <td>1.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
 95 |      },
 96 |      "execution_count": 3,
 97 |      "metadata": {},
 98 |      "output_type": "execute_result"
 99 |     }
100 |    ],
101 |    "source": [
102 |     "companies[['R&D Spend','Administration','Marketing Spend']].corr()\n"
103 |    ]
104 |   },
105 |   {
106 |    "cell_type": "markdown",
107 |    "source": [
108 |     "### removing column due to high correlation"
109 |    ],
110 |    "metadata": {
111 |     "collapsed": false,
112 |     "pycharm": {
113 |      "name": "#%% md\n"
114 |     }
115 |    }
116 |   },
117 |   {
118 |    "cell_type": "code",
119 |    "execution_count": 4,
120 |    "outputs": [],
121 |    "source": [
122 |     "companies.drop(['Marketing Spend'],axis=1,inplace=True)\n"
123 |    ],
124 |    "metadata": {
125 |     "collapsed": false,
126 |     "pycharm": {
127 |      "name": "#%%\n"
128 |     }
129 |    }
130 |   },
131 |   {
132 |    "cell_type": "code",
133 |    "execution_count": 5,
134 |    "outputs": [
135 |     {
136 |      "data": {
137 |       "text/plain": "     R&D Spend  Administration       State        Profit\n0    165349.20      136897.800    New York  192261.83000\n1    162597.70      151377.590  California  191792.06000\n2    153441.51      101145.550     Florida  191050.39000\n3    144372.41      118671.850    New York  182901.99000\n4    142107.34       91391.770     Florida  166187.94000\n..         ...             ...         ...           ...\n995   54135.00      118451.999  California   95279.96251\n996  134970.00      130390.080  California  164336.60550\n997  100275.47      241926.310  California  413956.48000\n998  128456.23      321652.140  California  333962.19000\n999  161181.72      270939.860    New York  476485.43000\n\n[1000 rows x 4 columns]",
138 |       "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>R&amp;D Spend</th>\n      <th>Administration</th>\n      <th>State</th>\n      <th>Profit</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>165349.20</td>\n      <td>136897.800</td>\n      <td>New York</td>\n      <td>192261.83000</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>162597.70</td>\n      <td>151377.590</td>\n      <td>California</td>\n      <td>191792.06000</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>153441.51</td>\n      <td>101145.550</td>\n      <td>Florida</td>\n      <td>191050.39000</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>144372.41</td>\n      <td>118671.850</td>\n      <td>New York</td>\n      <td>182901.99000</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>142107.34</td>\n      <td>91391.770</td>\n      <td>Florida</td>\n      <td>166187.94000</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>995</th>\n      <td>54135.00</td>\n      <td>118451.999</td>\n      <td>California</td>\n      <td>95279.96251</td>\n    </tr>\n    <tr>\n      <th>996</th>\n      <td>134970.00</td>\n      <td>130390.080</td>\n      <td>California</td>\n      <td>164336.60550</td>\n    </tr>\n    <tr>\n      <th>997</th>\n      <td>100275.47</td>\n      <td>241926.310</td>\n      <td>California</td>\n      <td>413956.48000</td>\n    </tr>\n    <tr>\n      <th>998</th>\n      <td>128456.23</td>\n      <td>321652.140</td>\n      <td>California</td>\n      <td>333962.19000</td>\n    </tr>\n    <tr>\n      <th>999</th>\n      <td>161181.72</td>\n      <td>270939.860</td>\n      <td>New York</td>\n      <td>476485.43000</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 4 columns</p>\n</div>"
139 |      },
140 |      "execution_count": 5,
141 |      "metadata": {},
142 |      "output_type": "execute_result"
143 |     }
144 |    ],
145 |    "source": [
146 |     "companies"
147 |    ],
148 |    "metadata": {
149 |     "collapsed": false,
150 |     "pycharm": {
151 |      "name": "#%%\n"
152 |     }
153 |    }
154 |   },
155 |   {
156 |    "cell_type": "markdown",
157 |    "source": [
158 |     "### Encoding Data\n",
159 |     "\n"
160 |    ],
161 |    "metadata": {
162 |     "collapsed": false,
163 |     "pycharm": {
164 |      "name": "#%% md\n"
165 |     }
166 |    }
167 |   },
168 |   {
169 |    "cell_type": "code",
170 |    "execution_count": 6,
171 |    "outputs": [],
172 |    "source": [
173 |     "dummies=pd.get_dummies(companies.State)\n"
174 |    ],
175 |    "metadata": {
176 |     "collapsed": false,
177 |     "pycharm": {
178 |      "name": "#%%\n"
179 |     }
180 |    }
181 |   },
182 |   {
183 |    "cell_type": "code",
184 |    "execution_count": 7,
185 |    "outputs": [],
186 |    "source": [
187 |     "companies=pd.concat([companies,dummies],axis=1)"
188 |    ],
189 |    "metadata": {
190 |     "collapsed": false,
191 |     "pycharm": {
192 |      "name": "#%%\n"
193 |     }
194 |    }
195 |   },
196 |   {
197 |    "cell_type": "code",
198 |    "execution_count": 8,
199 |    "outputs": [
200 |     {
201 |      "data": {
202 |       "text/plain": "     R&D Spend  Administration       State        Profit  California  Florida  \\\n0    165349.20      136897.800    New York  192261.83000           0        0   \n1    162597.70      151377.590  California  191792.06000           1        0   \n2    153441.51      101145.550     Florida  191050.39000           0        1   \n3    144372.41      118671.850    New York  182901.99000           0        0   \n4    142107.34       91391.770     Florida  166187.94000           0        1   \n..         ...             ...         ...           ...         ...      ...   \n995   54135.00      118451.999  California   95279.96251           1        0   \n996  134970.00      130390.080  California  164336.60550           1        0   \n997  100275.47      241926.310  California  413956.48000           1        0   \n998  128456.23      321652.140  California  333962.19000           1        0   \n999  161181.72      270939.860    New York  476485.43000           0        0   \n\n     New York  \n0           1  \n1           0  \n2           0  \n3           1  \n4           0  \n..        ...  \n995         0  \n996         0  \n997         0  \n998         0  \n999         1  \n\n[1000 rows x 7 columns]",
203 |       "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>R&amp;D Spend</th>\n      <th>Administration</th>\n      <th>State</th>\n      <th>Profit</th>\n      <th>California</th>\n      <th>Florida</th>\n      <th>New York</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>165349.20</td>\n      <td>136897.800</td>\n      <td>New York</td>\n      <td>192261.83000</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>162597.70</td>\n      <td>151377.590</td>\n      <td>California</td>\n      <td>191792.06000</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>153441.51</td>\n      <td>101145.550</td>\n      <td>Florida</td>\n      <td>191050.39000</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>144372.41</td>\n      <td>118671.850</td>\n      <td>New York</td>\n      <td>182901.99000</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>142107.34</td>\n      <td>91391.770</td>\n      <td>Florida</td>\n      <td>166187.94000</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</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    </tr>\n    <tr>\n      <th>995</th>\n      <td>54135.00</td>\n      <td>118451.999</td>\n      <td>California</td>\n      <td>95279.96251</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>996</th>\n      <td>134970.00</td>\n      <td>130390.080</td>\n      <td>California</td>\n      <td>164336.60550</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>997</th>\n      <td>100275.47</td>\n      <td>241926.310</td>\n      <td>California</td>\n      <td>413956.48000</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>998</th>\n      <td>128456.23</td>\n      <td>321652.140</td>\n      <td>California</td>\n      <td>333962.19000</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>999</th>\n      <td>161181.72</td>\n      <td>270939.860</td>\n      <td>New York</td>\n      <td>476485.43000</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 7 columns</p>\n</div>"
204 |      },
205 |      "execution_count": 8,
206 |      "metadata": {},
207 |      "output_type": "execute_result"
208 |     }
209 |    ],
210 |    "source": [
211 |     "companies"
212 |    ],
213 |    "metadata": {
214 |     "collapsed": false,
215 |     "pycharm": {
216 |      "name": "#%%\n"
217 |     }
218 |    }
219 |   },
220 |   {
221 |    "cell_type": "code",
222 |    "execution_count": 9,
223 |    "outputs": [
224 |     {
225 |      "data": {
226 |       "text/plain": "     R&D Spend  Administration        Profit  California  Florida  New York\n0    165349.20      136897.800  192261.83000           0        0         1\n1    162597.70      151377.590  191792.06000           1        0         0\n2    153441.51      101145.550  191050.39000           0        1         0\n3    144372.41      118671.850  182901.99000           0        0         1\n4    142107.34       91391.770  166187.94000           0        1         0\n..         ...             ...           ...         ...      ...       ...\n995   54135.00      118451.999   95279.96251           1        0         0\n996  134970.00      130390.080  164336.60550           1        0         0\n997  100275.47      241926.310  413956.48000           1        0         0\n998  128456.23      321652.140  333962.19000           1        0         0\n999  161181.72      270939.860  476485.43000           0        0         1\n\n[1000 rows x 6 columns]",
227 |       "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>R&amp;D Spend</th>\n      <th>Administration</th>\n      <th>Profit</th>\n      <th>California</th>\n      <th>Florida</th>\n      <th>New York</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>165349.20</td>\n      <td>136897.800</td>\n      <td>192261.83000</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>162597.70</td>\n      <td>151377.590</td>\n      <td>191792.06000</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>153441.51</td>\n      <td>101145.550</td>\n      <td>191050.39000</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>144372.41</td>\n      <td>118671.850</td>\n      <td>182901.99000</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>142107.34</td>\n      <td>91391.770</td>\n      <td>166187.94000</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</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    </tr>\n    <tr>\n      <th>995</th>\n      <td>54135.00</td>\n      <td>118451.999</td>\n      <td>95279.96251</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>996</th>\n      <td>134970.00</td>\n      <td>130390.080</td>\n      <td>164336.60550</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>997</th>\n      <td>100275.47</td>\n      <td>241926.310</td>\n      <td>413956.48000</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>998</th>\n      <td>128456.23</td>\n      <td>321652.140</td>\n      <td>333962.19000</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>999</th>\n      <td>161181.72</td>\n      <td>270939.860</td>\n      <td>476485.43000</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 6 columns</p>\n</div>"
228 |      },
229 |      "execution_count": 9,
230 |      "metadata": {},
231 |      "output_type": "execute_result"
232 |     }
233 |    ],
234 |    "source": [
235 |     "companies.drop(['State'],axis=1,inplace=True)\n",
236 |     "companies"
237 |    ],
238 |    "metadata": {
239 |     "collapsed": false,
240 |     "pycharm": {
241 |      "name": "#%%\n"
242 |     }
243 |    }
244 |   },
245 |   {
246 |    "cell_type": "markdown",
247 |    "source": [
248 |     "### Scaling"
249 |    ],
250 |    "metadata": {
251 |     "collapsed": false,
252 |     "pycharm": {
253 |      "name": "#%% md\n"
254 |     }
255 |    }
256 |   },
257 |   {
258 |    "cell_type": "code",
259 |    "metadata": {
260 |     "pycharm": {
261 |      "name": "#%%\n"
262 |     }
263 |    },
264 |    "source": [
265 |     "from sklearn.preprocessing import MinMaxScaler\n",
266 |     "scale=MinMaxScaler()\n",
267 |     "companies[['R&D Spend','Administration']]=scale.fit_transform(companies[['R&D Spend','Administration']])"
268 |    ],
269 |    "execution_count": 10,
270 |    "outputs": []
271 |   },
272 |   {
273 |    "cell_type": "markdown",
274 |    "source": [
275 |     "### Specifying X and y"
276 |    ],
277 |    "metadata": {
278 |     "collapsed": false,
279 |     "pycharm": {
280 |      "name": "#%% md\n"
281 |     }
282 |    }
283 |   },
284 |   {
285 |    "cell_type": "code",
286 |    "execution_count": 11,
287 |    "metadata": {},
288 |    "outputs": [
289 |     {
290 |      "data": {
291 |       "text/plain": "array([192261.83   , 191792.06   , 191050.39   , 182901.99   ,\n       166187.94   , 156991.12   , 156122.51   , 155752.6    ,\n       152211.77   , 149759.96   , 146121.95   , 144259.4    ,\n       141585.52   , 134307.35   , 132602.65   , 129917.04   ,\n       126992.93   , 125370.37   , 124266.9    , 122776.86   ,\n       118474.03   , 111313.02   , 110352.25   , 108733.99   ,\n       108552.04   , 107404.34   , 105733.54   , 105008.31   ,\n       103282.38   , 101004.64   ,  99937.59   ,  97483.56   ,\n        97427.84   ,  96778.92   ,  96712.8    ,  96479.51   ,\n        90708.19   ,  89949.14   ,  81229.06   ,  81005.76   ,\n        78239.91   ,  77798.83   ,  71498.49   ,  69758.98   ,\n        65200.33   ,  64926.08   ,  49490.75   ,  42559.73   ,\n        35673.41   ,  14681.4    , 123485.2464 ,  82155.48418,\n       125867.0108 , 104976.1696 ,  89803.10053,  75297.23305,\n       114284.5283 , 171985.0761 ,  72337.96774, 169566.5772 ,\n       158670.9451 , 114522.8756 ,  85842.60573, 101106.2297 ,\n        59328.81874, 157142.6178 ,  68669.64059, 177717.3712 ,\n        94409.4396 , 183945.1553 ,  82484.38635, 144515.3371 ,\n       105333.2634 , 122331.0988 , 168459.4156 ,  60947.70089,\n       162733.9549 , 181574.4968 ,  73577.54452,  84782.43014,\n       168870.3298 ,  72607.06952,  56788.15621,  67473.63267,\n        52731.98078, 140237.9002 , 166598.769  , 102990.7964 ,\n        78406.85364, 111764.3688 ,  63662.63887, 142575.2414 ,\n       115980.2967 , 132915.7689 , 155954.2985 , 167412.0544 ,\n        88710.46186, 164139.2642 , 131574.5314 , 169314.5613 ,\n        86636.24242, 177468.7724 , 157979.8234 ,  56944.49153,\n        98500.64098,  87218.86913, 178759.6067 , 101668.3534 ,\n       151782.7938 ,  68872.96194, 139016.2635 ,  69109.60065,\n        55091.53354, 136286.8026 , 122307.1786 , 154356.7737 ,\n       114806.5004 ,  55623.75707,  73896.1952 , 172901.7308 ,\n       129480.6633 , 115890.5961 , 169404.2619 , 161666.9449 ,\n        50116.99489,  86613.17655,  91640.68127, 138793.2935 ,\n       128986.8828 , 111461.9497 , 129804.4397 , 178847.5987 ,\n       101028.4891 , 136845.5092 ,  94579.44358, 148748.3508 ,\n        91139.21223, 173343.3994 , 175906.2735 , 112883.4905 ,\n       138079.1059 ,  78689.62408, 140832.487  , 182316.0217 ,\n       129232.9188 , 152520.9015 , 133849.5093 , 169431.5992 ,\n       109333.0556 , 121505.8533 , 108917.0157 , 169324.8128 ,\n       161423.4719 , 171478.4813 , 137670.7546 , 105582.7164 ,\n       141472.3512 , 169572.5573 , 126993.8211 , 119743.4502 ,\n       103155.6747 ,  86313.32028, 105674.9799 , 152268.8856 ,\n       101971.6268 , 166402.282  ,  84757.65569, 142289.0538 ,\n       155518.6099 , 177675.5109 , 111138.1732 , 142490.6665 ,\n        65814.59883,  88870.21435, 125271.5697 , 163462.6654 ,\n       154539.592  , 151150.6182 , 178296.5808 , 106401.1276 ,\n        76644.45054, 110228.3529 , 122570.3004 ,  54205.63339,\n        73850.06347, 117353.9972 ,  63814.70273,  67199.40514,\n       181391.6784 , 181550.5766 , 156935.8793 , 181579.6225 ,\n        94376.97653,  76229.26494,  89583.54765, 176839.1597 ,\n       113578.8837 ,  74477.11333,  88648.95289,  94066.01447,\n       146874.0356 , 163549.8031 , 138872.7426 , 121482.7874 ,\n        89594.65343,  94297.52743, 159509.0049 ,  81169.63193,\n       117700.8395 ,  61393.64099, 169661.4036 , 171651.9025 ,\n       128265.0066 ,  75270.75002, 109658.5406 , 145976.1753 ,\n        53395.76517, 144038.6425 ,  54300.45973,  58223.36571,\n        66007.66868, 121491.3304 ,  89915.86699, 182098.1774 ,\n        68160.48294, 136575.5531 , 111422.6523 , 141814.0678 ,\n        85830.64565, 121927.8732 ,  96616.9285 ,  90687.2921 ,\n       155424.6379 , 122954.7315 , 113188.4725 , 163883.8311 ,\n        68984.01982,  99306.23774,  52325.33808,  58694.93455,\n        80229.05713, 104723.2993 ,  51256.61958,  51336.06868,\n        53225.76119,  64672.41127, 173263.9503 , 155791.1289 ,\n       118334.7237 ,  90164.46578, 140872.6387 , 116492.8715 ,\n        58918.75889,  64349.48913, 164375.9029 , 169059.9825 ,\n       109663.6663 ,  68719.18949, 102833.6068 , 158338.6258 ,\n       168686.6571 , 170883.8945 ,  92949.45565, 110023.323  ,\n       126506.0207 , 130602.3478 , 117289.0711 , 117645.3106 ,\n       148944.8378 , 114970.5243 , 170174.8327 ,  92758.09438,\n       142762.3312 , 168802.8408 ,  56138.89476, 160646.0668 ,\n       162479.376  , 146925.293  ,  61291.12602, 112642.5803 ,\n       116273.3187 , 109285.2152 , 103264.1697 ,  60111.34964,\n        55227.36587,  73733.02555,  98129.02423,  82589.46419,\n       168876.3098 , 104996.6726 , 147736.0156 , 181512.1335 ,\n        95260.31381,  91977.27207, 126295.865  , 174329.2516 ,\n       118265.5261 , 153825.4044 ,  94093.35179, 167934.0264 ,\n       103243.6667 , 160935.6715 , 107019.6345 , 173336.5651 ,\n        73154.67029, 145877.9318 , 164180.2702 , 184632.0056 ,\n       151992.0952 , 100693.6069 , 180684.3252 ,  83391.64379,\n       121140.2166 ,  66656.07583, 123814.1486 , 150292.0553 ,\n       159514.1307 ,  87019.81924,  96793.76682, 105154.7165 ,\n       175999.3913 , 169169.3318 , 182911.4628 , 134979.7368 ,\n        70244.95388, 169623.8148 , 135817.7966 ,  50070.86316,\n        60368.49134, 182028.1255 ,  92289.08842, 184555.1194 ,\n       135591.4094 ,  73790.26307, 160667.424  , 121248.7116 ,\n       135506.8346 , 154351.6479 , 116529.6061 , 142869.1176 ,\n       131062.8109 , 165941.819  , 172384.0302 , 142712.7823 ,\n        91790.18226, 100435.6109 , 144750.2672 , 137468.2876 ,\n       161824.1346 ,  92920.40974, 108421.5267 , 141046.0598 ,\n       156147.3684 , 182641.5067 , 150475.728  ,  79794.22283,\n        55832.20416, 152920.7099 , 145711.345  , 128195.809  ,\n        80504.99325, 172615.5432 , 102213.3913 ,  91240.87291,\n       158160.0789 ,  54244.9308 , 171176.9165 , 167377.0285 ,\n       154029.5801 , 105503.2673 ,  65204.63479,  65181.56893,\n       169235.1122 , 144807.5047 , 171235.8626 ,  92485.57543,\n       161936.0467 , 107910.6604 , 183965.6583 , 152134.7618 ,\n        51913.56964,  94320.5933 , 103906.5968 , 136632.7906 ,\n        72949.64036,  51690.5996 , 106212.3292 , 149849.5324 ,\n        64574.16776, 120375.6258 , 154765.9792 ,  86983.939  ,\n       171557.9304 , 157690.2186 ,  67839.26938, 175747.3753 ,\n        53177.92087, 123648.4161 ,  59636.36364, 105740.7603 ,\n       165029.4358 , 180633.922  , 126997.2382 , 171687.7827 ,\n       125636.3521 ,  52225.38599,  59981.49735,  88971.02073,\n        63306.39937,  58666.74293,  77017.77587, 161008.2863 ,\n        77847.29279,  97478.0542 ,  85976.72948, 149792.2949 ,\n       128937.3339 ,  80082.11902, 154238.8815 , 174414.6808 ,\n       156182.3943 ,  71376.03566, 145680.5905 , 185028.3968 ,\n        68921.65655, 172937.611  , 150707.2409 , 185352.1732 ,\n       106018.405  , 131659.9605 , 114839.8177 ,  97372.12207,\n        78308.61013,  85769.13667, 126436.8231 ,  67226.74247,\n       174996.4532 ,  59225.44949, 102740.489  , 141180.1836 ,\n       157325.4362 ,  90312.25819, 162440.0786 , 126117.3181 ,\n        58784.63514, 165530.0505 ,  90550.60548, 161123.6156 ,\n        87309.42402,  72735.21323,  97238.85262,  68648.28331,\n       157529.6118 ,  85529.93509,  80539.1649 , 163525.0287 ,\n       139080.3354 , 165186.6254 ,  68347.57275,  90544.62544,\n        88027.88306,  64997.04199, 184979.7022 ,  70555.91594,\n        91209.26412, 120790.8114 , 157615.041  , 145240.6305 ,\n        65085.034  ,  75968.70607, 181243.886  , 102274.046  ,\n       167257.4277 ,  95537.9585 , 158961.4042 ,  80106.89347,\n       127075.833  , 184887.4387 ,  67282.27141,  77242.4545 ,\n       164713.348  ,  84909.71956, 160000.2225 ,  73872.27504,\n       101119.044  , 107252.8561 , 117043.8895 , 155881.6838 ,\n       141832.0079 ,  81963.26862, 142494.938  , 143333.8521 ,\n        72478.92582, 134122.8826 ,  57893.60924, 174050.7527 ,\n        66273.3533 , 139130.7386 ,  99032.8645 , 141073.3972 ,\n       156340.4382 ,  88072.30621, 126393.2542 ,  65664.24355,\n       134894.3077 , 110963.8978 , 103171.0519 ,  84808.91317,\n       139555.3214 ,  68705.52083,  96214.55727,  98444.25774,\n       145073.1894 , 138588.2636 , 138736.9103 ,  77629.44849,\n       135641.8126 ,  91657.76709, 169403.4076 , 133617.1421 ,\n        70509.78421, 124269.4859 ,  54119.34996, 174320.7087 ,\n       151804.1511 , 180524.5727 ,  54971.93275,  69995.5008 ,\n        77837.89559, 100556.066  , 184099.7821 , 151774.2509 ,\n       153976.614  , 183093.4268 ,  91843.14832,  59342.48741,\n       115751.3466 , 108629.9738 , 182876.4368 , 143061.3332 ,\n       176623.024  , 154901.8116 , 181946.9678 ,  99906.80457,\n        77132.25091, 175771.2955 ,  78153.1291 ,  56852.22806,\n       169564.8687 ,  75445.02546, 148158.0355 , 144203.5207 ,\n       142226.6905 , 175396.2616 , 118130.5481 , 108776.0576 ,\n       107382.7084 , 120617.3903 , 150393.716  , 106070.5168 ,\n       160842.5538 , 146499.0017 ,  97712.98433, 125981.4858 ,\n        71885.19331, 130070.1243 , 104151.7784 , 106169.6146 ,\n       147194.3948 , 141527.0259 , 113981.2549 , 184581.6024 ,\n        54060.40386,  76376.20305,  99301.96628,  98464.76074,\n       174007.1838 , 128337.6214 , 176344.525  , 107669.7503 ,\n        90482.26217,  79710.50227,  84583.38025, 166679.9267 ,\n        74052.53052, 129889.8688 ,  84552.62576, 131051.7051 ,\n       116205.8296 ,  65471.1737 , 128060.831  , 127773.7891 ,\n       108896.5127 , 176833.1797 ,  54991.58145, 181929.0277 ,\n       102873.7585 ,  57541.6412 ,  65513.03398, 162182.9369 ,\n        51671.80519, 138022.7227 , 180257.1795 ,  60408.64304,\n       178552.8682 , 182059.7343 , 114403.2748 ,  85101.93511,\n       157086.2346 , 150024.6621 , 127248.3999 , 154190.1869 ,\n       126058.372  , 138213.2296 , 101352.2656 , 100958.4372 ,\n        63373.88839, 179522.4889 , 184865.2271 , 102619.1797 ,\n       175826.8244 , 165119.1364 , 134268.9664 ,  61306.50327,\n       165495.0246 ,  77667.8916 , 154051.7917 , 111643.0594 ,\n       106517.3112 ,  68575.66854, 155915.0011 , 124695.7773 ,\n       172769.3156 , 185068.5485 , 157591.1208 , 106865.8621 ,\n       104824.1057 , 120990.7156 ,  56620.7151 , 159613.2285 ,\n       175705.515  ,  98776.57709, 165987.9507 ,  52609.81711,\n       117842.6519 ,  80045.38449,  80066.74177, 137719.4492 ,\n       149477.9157 , 180783.423  , 103404.2734 ,  88302.96488,\n       100992.6089 , 141082.7944 , 142586.3472 , 175166.4572 ,\n        56991.47755, 109105.8141 , 167373.6113 , 153627.2089 ,\n       126846.883  ,  76545.35274,  65255.03798, 171780.0462 ,\n       118944.6878 , 168285.1402 ,  95226.99644,  59264.74689,\n       163470.354  , 162747.6235 ,  56775.34184,  79808.74578,\n        83356.61784,  74502.74207, 145965.9238 ,  59784.15604,\n       133834.1321 ,  71717.75221,  91441.63138, 164779.9827 ,\n        98397.27172,  92502.66126, 136315.8485 ,  79796.7857 ,\n       144805.7962 ,  94294.11026, 100589.3834 ,  81824.87341,\n        64950.05596, 113472.9515 , 116685.0871 , 114373.3746 ,\n        99277.19183, 109998.5485 , 124765.8292 , 163155.1205 ,\n       144820.3191 , 139915.8323 ,  50468.96294,  92362.55748,\n       158565.8673 ,  79167.17296, 103903.1796 ,  98368.22581,\n       182202.4009 ,  70232.13951,  53483.75718, 120345.7256 ,\n       143415.8641 ,  56789.0105 , 110848.5685 , 144287.2413 ,\n        90108.93684,  85570.94108,  98808.18587,  61960.03617,\n       127725.0945 ,  70282.5427 , 159431.2644 ,  50994.35213,\n        83632.55396,  88481.51178, 168402.1781 ,  87716.921  ,\n       173519.3834 , 177513.1956 , 181258.409  , 119914.3085 ,\n       152243.2568 , 142852.0318 , 176432.517  , 164424.5975 ,\n        57258.01646, 177442.2894 , 149190.8738 , 130689.4855 ,\n       107994.381  , 111257.774  , 123690.2763 , 163138.0347 ,\n        91370.72519, 166902.0425 ,  55641.69719,  58179.79685,\n       156545.4682 , 104862.5488 , 181441.2273 , 164884.2062 ,\n       132897.8287 ,  81580.54608, 127455.1384 , 116045.2229 ,\n       161630.2104 , 140594.1397 ,  51276.26828, 121248.7116 ,\n        65868.41919,  60243.7648 ,  52276.64348, 162399.9269 ,\n        68210.88613, 119961.2945 ,  72657.47271, 182979.8061 ,\n       112054.8279 ,  74208.01155, 164330.6254 , 174254.9283 ,\n       119482.037  , 117637.622  , 160252.2384 , 152175.7678 ,\n       106433.5906 , 120445.6777 , 141408.2794 ,  52086.1365 ,\n       133019.1381 , 172966.6569 , 163028.6854 , 109278.3809 ,\n       144130.0517 , 140289.1577 , 141273.3013 ,  57992.70704,\n       125971.2343 , 120723.3224 , 128977.4856 ,  65219.15775,\n       100404.0021 , 177911.2954 , 137842.4672 , 127909.6214 ,\n       154173.101  , 170343.1281 ,  59766.21593,  90712.92084,\n        93280.9207 ,  87045.44798,  79170.59013, 181485.6505 ,\n       174421.5151 ,  63924.90632, 140964.9022 ,  55195.75709,\n       140870.0758 , 169745.1241 ,  83444.60985, 185032.6682 ,\n       168246.6971 , 156488.2307 , 152900.2069 , 167391.5514 ,\n       163226.881  , 130427.2181 ,  87219.72342, 125467.2024 ,\n       173897.8345 , 142927.2094 ,  76356.55435, 158208.7735 ,\n        67733.33725,  97340.51329, 170464.4375 , 120738.6997 ,\n       149669.2769 ,  79513.16096, 168145.8907 , 170465.2918 ,\n       125667.9609 ,  63742.94226, 159389.4041 ,  72870.19126,\n       124577.0308 , 177000.6208 , 166579.1203 , 143338.9779 ,\n       169673.3637 ,  74324.19518, 184669.5944 , 136050.1639 ,\n       184516.6762 ,  95065.53537, 170547.3037 , 146196.5825 ,\n       109344.1613 , 150516.734  ,  55771.54948,  88082.55771,\n       109877.2392 , 185272.7241 ,  88592.56966,  86750.71746,\n        99201.1599 ,  97955.60308, 164695.4079 , 173531.3435 ,\n       110363.331  , 144184.7263 , 102771.2435 ,  87654.55773,\n       181102.0736 ,  64966.2875 , 180257.1795 , 140589.8682 ,\n        71772.42685,  77627.73991,  51286.51978,  80859.52417,\n        86101.45602, 132471.5373 ,  50428.81124,  99424.12995,\n        97446.44542, 138908.6228 , 148134.1153 , 159173.2684 ,\n        82229.80752, 100759.3874 , 113444.7599 ,  62531.55709,\n        87112.08271, 128995.4258 ,  53649.48971, 104159.467  ,\n        63978.72668, 167407.783  , 116603.0751 , 165584.7252 ,\n        88737.79919, 152894.2269 ,  64769.80049,  51324.1086 ,\n        57067.50948,  66357.07385,  71235.93187, 166415.9507 ,\n        57463.90068,  80804.84952,  70902.75824, 159247.5918 ,\n       112487.9536 , 116260.5043 , 121916.7675 , 161488.398  ,\n       161456.7893 , 176018.1857 , 118219.3944 , 134983.154  ,\n       180378.4888 , 139722.7625 ,  84378.35032, 178978.3053 ,\n        97882.98831,  54932.63535,  95148.40164, 106235.395  ,\n       103813.479  , 134723.4494 , 174364.2776 ,  82522.82946,\n        65743.69265,  96581.04826,  70153.5447 ,  93606.40571,\n       151891.2888 ,  79299.58812,  83553.10486,  60650.40749,\n       123228.959  ,  52481.67341, 161467.0408 , 107682.5646 ,\n       140522.3792 , 102118.5649 ,  57143.54142, 159227.0888 ,\n       163673.6754 , 157493.7316 ,  91623.59544, 157949.9232 ,\n        94974.98049, 148975.5923 , 158516.3184 , 110682.8359 ,\n       146690.3629 ,  58605.23395, 120412.3603 , 161783.1286 ,\n        76487.26093,  95178.30183, 104231.2275 ,  58963.18204,\n        76017.40068,  59803.80475, 129642.9786 ,  51003.74933,\n        77362.05529, 185502.5285 , 180753.5228 , 172495.0881 ,\n       140251.5689 ,  63093.68082, 171416.9724 , 111814.772  ,\n       123671.4819 ,  92903.32391, 105457.9899 ,  74425.00156,\n       173861.9543 ,  62223.15791,  60869.96038, 110395.794  ,\n       161076.6296 , 107704.7762 , 141344.2075 , 168760.9805 ,\n        97599.36358,  89558.7732 ,  99322.46927,  60065.21791,\n       102489.3274 ,  94400.89669, 154569.4922 ,  90808.60147,\n       138855.6568 , 103378.6447 , 134808.0242 ,  84305.73556,\n        83178.92524,  86221.9111 , 165330.1463 , 161035.6236 ,\n       138841.9881 ,  89012.02672, 132077.709  ,  95279.96251,\n       164336.6055 , 413956.48   , 333962.19   , 476485.43   ])"
292 |      },
293 |      "execution_count": 11,
294 |      "metadata": {},
295 |      "output_type": "execute_result"
296 |     }
297 |    ],
298 |    "source": [
299 |     "y=companies.iloc[:,2].values\n",
300 |     "y\n"
301 |    ]
302 |   },
303 |   {
304 |    "cell_type": "code",
305 |    "metadata": {
306 |     "pycharm": {
307 |      "name": "#%%\n"
308 |     }
309 |    },
310 |    "source": [
311 |     "companies.drop(['Profit'],axis=1,inplace=True)\n",
312 |     "companies\n"
313 |    ],
314 |    "execution_count": 12,
315 |    "outputs": [
316 |     {
317 |      "data": {
318 |       "text/plain": "     R&D Spend  Administration  California  Florida  New York\n0     1.000000        0.316659           0        0         1\n1     0.983359        0.370214           1        0         0\n2     0.927985        0.184424           0        1         0\n3     0.873136        0.249247           0        0         1\n4     0.859438        0.148348           0        1         0\n..         ...             ...         ...      ...       ...\n995   0.327398        0.248434           1        0         0\n996   0.816272        0.292589           1        0         0\n997   0.606447        0.705122           1        0         0\n998   0.776878        1.000000           1        0         0\n999   0.974796        0.812433           0        0         1\n\n[1000 rows x 5 columns]",
319 |       "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>R&amp;D Spend</th>\n      <th>Administration</th>\n      <th>California</th>\n      <th>Florida</th>\n      <th>New York</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1.000000</td>\n      <td>0.316659</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.983359</td>\n      <td>0.370214</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.927985</td>\n      <td>0.184424</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0.873136</td>\n      <td>0.249247</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.859438</td>\n      <td>0.148348</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>995</th>\n      <td>0.327398</td>\n      <td>0.248434</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>996</th>\n      <td>0.816272</td>\n      <td>0.292589</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>997</th>\n      <td>0.606447</td>\n      <td>0.705122</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>998</th>\n      <td>0.776878</td>\n      <td>1.000000</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>999</th>\n      <td>0.974796</td>\n      <td>0.812433</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 5 columns</p>\n</div>"
320 |      },
321 |      "execution_count": 12,
322 |      "metadata": {},
323 |      "output_type": "execute_result"
324 |     }
325 |    ]
326 |   },
327 |   {
328 |    "cell_type": "code",
329 |    "execution_count": 13,
330 |    "metadata": {},
331 |    "outputs": [
332 |     {
333 |      "data": {
334 |       "text/plain": "(1000, 5)"
335 |      },
336 |      "execution_count": 13,
337 |      "metadata": {},
338 |      "output_type": "execute_result"
339 |     }
340 |    ],
341 |    "source": [
342 |     "X=companies.iloc[:,:].values\n",
343 |     "X.shape"
344 |    ]
345 |   },
346 |   {
347 |    "cell_type": "markdown",
348 |    "metadata": {},
349 |    "source": [
350 |     "### splitting dataset into train and test"
351 |    ]
352 |   },
353 |   {
354 |    "cell_type": "code",
355 |    "execution_count": 14,
356 |    "metadata": {},
357 |    "outputs": [],
358 |    "source": [
359 |     "from sklearn.model_selection import train_test_split\n",
360 |     "X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.25,random_state=0)\n"
361 |    ]
362 |   },
363 |   {
364 |    "cell_type": "markdown",
365 |    "metadata": {},
366 |    "source": [
367 |     "### fitting model to training set"
368 |    ]
369 |   },
370 |   {
371 |    "cell_type": "code",
372 |    "execution_count": 15,
373 |    "metadata": {},
374 |    "outputs": [
375 |     {
376 |      "data": {
377 |       "text/plain": "LinearRegression()"
378 |      },
379 |      "execution_count": 15,
380 |      "metadata": {},
381 |      "output_type": "execute_result"
382 |     }
383 |    ],
384 |    "source": [
385 |     "from sklearn.linear_model import LinearRegression\n",
386 |     "lin_reg = LinearRegression()\n",
387 |     "lin_reg.fit(X_train,y_train)"
388 |    ]
389 |   },
390 |   {
391 |    "cell_type": "markdown",
392 |    "metadata": {},
393 |    "source": [
394 |     "### predicting the test dataset"
395 |    ]
396 |   },
397 |   {
398 |    "cell_type": "code",
399 |    "execution_count": 16,
400 |    "metadata": {},
401 |    "outputs": [],
402 |    "source": [
403 |     "y_pred = lin_reg.predict(X_test)\n"
404 |    ]
405 |   },
406 |   {
407 |    "cell_type": "markdown",
408 |    "metadata": {},
409 |    "source": [
410 |     "### finding coefficients and intercepts"
411 |    ]
412 |   },
413 |   {
414 |    "cell_type": "code",
415 |    "execution_count": 17,
416 |    "metadata": {},
417 |    "outputs": [
418 |     {
419 |      "name": "stdout",
420 |      "output_type": "stream",
421 |      "text": [
422 |       "[ 1.20926284e+05  2.29991450e+05 -2.13364325e+16 -2.13364325e+16\n",
423 |       " -2.13364325e+16]\n"
424 |      ]
425 |     }
426 |    ],
427 |    "source": [
428 |     "# coefficient \n",
429 |     "print(lin_reg.coef_)"
430 |    ]
431 |   },
432 |   {
433 |    "cell_type": "code",
434 |    "execution_count": 18,
435 |    "metadata": {},
436 |    "outputs": [
437 |     {
438 |      "name": "stdout",
439 |      "output_type": "stream",
440 |      "text": [
441 |       "2.1336432488839856e+16\n"
442 |      ]
443 |     }
444 |    ],
445 |    "source": [
446 |     "# intercepts\n",
447 |     "print(lin_reg.intercept_)"
448 |    ]
449 |   },
450 |   {
451 |    "cell_type": "markdown",
452 |    "metadata": {},
453 |    "source": [
454 |     "### evaluating the model"
455 |    ]
456 |   },
457 |   {
458 |    "cell_type": "code",
459 |    "execution_count": 19,
460 |    "metadata": {},
461 |    "outputs": [
462 |     {
463 |      "data": {
464 |       "text/plain": "0.9227851574991782"
465 |      },
466 |      "execution_count": 19,
467 |      "metadata": {},
468 |      "output_type": "execute_result"
469 |     }
470 |    ],
471 |    "source": [
472 |     "# calculating the  R squared error\n",
473 |     "from sklearn.metrics import r2_score\n",
474 |     "r2_score(y_test,y_pred)"
475 |    ]
476 |   },
477 |   {
478 |    "cell_type": "code",
479 |    "execution_count": 19,
480 |    "metadata": {},
481 |    "outputs": [],
482 |    "source": []
483 |   }
484 |  ],
485 |  "metadata": {
486 |   "kernelspec": {
487 |    "display_name": "Python 3",
488 |    "language": "python",
489 |    "name": "python3"
490 |   },
491 |   "language_info": {
492 |    "codemirror_mode": {
493 |     "name": "ipython",
494 |     "version": 3
495 |    },
496 |    "file_extension": ".py",
497 |    "mimetype": "text/x-python",
498 |    "name": "python",
499 |    "nbconvert_exporter": "python",
500 |    "pygments_lexer": "ipython3",
501 |    "version": "3.6.4"
502 |   }
503 |  },
504 |  "nbformat": 4,
505 |  "nbformat_minor": 2
506 | }


--------------------------------------------------------------------------------
/1000_Companies.csv:
--------------------------------------------------------------------------------
   1 | R&D Spend,Administration,Marketing Spend,State,Profit
   2 | 165349.2,136897.8,471784.1,New York,192261.83
   3 | 162597.7,151377.59,443898.53,California,191792.06
   4 | 153441.51,101145.55,407934.54,Florida,191050.39
   5 | 144372.41,118671.85,383199.62,New York,182901.99
   6 | 142107.34,91391.77,366168.42,Florida,166187.94
   7 | 131876.9,99814.71,362861.36,New York,156991.12
   8 | 134615.46,147198.87,127716.82,California,156122.51
   9 | 130298.13,145530.06,323876.68,Florida,155752.6
  10 | 120542.52,148718.95,311613.29,New York,152211.77
  11 | 123334.88,108679.17,304981.62,California,149759.96
  12 | 101913.08,110594.11,229160.95,Florida,146121.95
  13 | 100671.96,91790.61,249744.55,California,144259.4
  14 | 93863.75,127320.38,249839.44,Florida,141585.52
  15 | 91992.39,135495.07,252664.93,California,134307.35
  16 | 119943.24,156547.42,256512.92,Florida,132602.65
  17 | 114523.61,122616.84,261776.23,New York,129917.04
  18 | 78013.11,121597.55,264346.06,California,126992.93
  19 | 94657.16,145077.58,282574.31,New York,125370.37
  20 | 91749.16,114175.79,294919.57,Florida,124266.9
  21 | 86419.7,153514.11,0,New York,122776.86
  22 | 76253.86,113867.3,298664.47,California,118474.03
  23 | 78389.47,153773.43,299737.29,New York,111313.02
  24 | 73994.56,122782.75,303319.26,Florida,110352.25
  25 | 67532.53,105751.03,304768.73,Florida,108733.99
  26 | 77044.01,99281.34,140574.81,New York,108552.04
  27 | 64664.71,139553.16,137962.62,California,107404.34
  28 | 75328.87,144135.98,134050.07,Florida,105733.54
  29 | 72107.6,127864.55,353183.81,New York,105008.31
  30 | 66051.52,182645.56,118148.2,Florida,103282.38
  31 | 65605.48,153032.06,107138.38,New York,101004.64
  32 | 61994.48,115641.28,91131.24,Florida,99937.59
  33 | 61136.38,152701.92,88218.23,New York,97483.56
  34 | 63408.86,129219.61,46085.25,California,97427.84
  35 | 55493.95,103057.49,214634.81,Florida,96778.92
  36 | 46426.07,157693.92,210797.67,California,96712.8
  37 | 46014.02,85047.44,205517.64,New York,96479.51
  38 | 28663.76,127056.21,201126.82,Florida,90708.19
  39 | 44069.95,51283.14,197029.42,California,89949.14
  40 | 20229.59,65947.93,185265.1,New York,81229.06
  41 | 38558.51,82982.09,174999.3,California,81005.76
  42 | 28754.33,118546.05,172795.67,California,78239.91
  43 | 27892.92,84710.77,164470.71,Florida,77798.83
  44 | 23640.93,96189.63,148001.11,California,71498.49
  45 | 15505.73,127382.3,35534.17,New York,69758.98
  46 | 22177.74,154806.14,28334.72,California,65200.33
  47 | 1000.23,124153.04,1903.93,New York,64926.08
  48 | 1315.46,115816.21,297114.46,Florida,49490.75
  49 | 0,135426.92,0,California,42559.73
  50 | 542.05,51743.15,0,New York,35673.41
  51 | 0,116983.8,45173.06,California,14681.4
  52 | 87151,123327.9523,236937.1317,New York,123485.2464
  53 | 38772,116183.1212,143589.7191,California,82155.48418
  54 | 89939,123739.6968,242316.5853,Florida,125867.0108
  55 | 65485,120128.2187,195132.5255,New York,104976.1696
  56 | 47724,117505.1933,160862.6275,Florida,89803.10053
  57 | 30744,114997.5096,128099.6711,New York,75297.23305
  58 | 76381,121737.3896,216156.3873,California,114284.5283
  59 | 143923,131712.2998,346478.8607,Florida,171985.0761
  60 | 27280,114485.9303,121415.8737,New York,72337.96774
  61 | 141092,131294.2049,341016.4385,California,169566.5772
  62 | 128338,129410.636,316407.5606,Florida,158670.9451
  63 | 76660,121778.5936,216694.7185,California,114522.8756
  64 | 43088,116820.5277,151917.4528,Florida,85842.60573
  65 | 60955,119459.2077,186391.8781,California,101106.2297
  66 | 12052,112236.9898,92033.40609,Florida,59328.81874
  67 | 126549,129146.4284,312955.6803,New York,157142.6178
  68 | 22986,113851.7728,113130.5889,California,68669.64059
  69 | 150633,132703.2632,359425.824,New York,177717.3712
  70 | 53116,118301.5084,171266.5062,Florida,94409.4396
  71 | 157923,133779.8836,373491.8989,New York,183945.1553
  72 | 39157,116239.9797,144332.5776,California,82484.38635
  73 | 111768,126963.503,284435.7004,New York,144515.3371
  74 | 65903,120189.9508,195939.0576,Florida,105333.2634
  75 | 85800,123128.4304,234330.3735,Florida,122331.0988
  76 | 139796,131102.8057,338515.8029,New York,168459.4156
  77 | 13947,112516.8521,95689.81377,California,60947.70089
  78 | 133094,130113.0238,325584.2756,Florida,162733.9549
  79 | 155148,133370.059,368137.5289,New York,181574.4968
  80 | 28731,114700.2205,124215.5821,Florida,73577.54452
  81 | 41847,116637.2512,149522.94,New York,84782.43014
  82 | 140277,131173.8419,339443.8938,Florida,168870.3298
  83 | 27595,114532.4509,122023.667,New York,72607.06952
  84 | 9078,111797.776,86295.06497,California,56788.15621
  85 | 21586,113645.0144,110429.2851,Florida,67473.63267
  86 | 4330,111096.5697,77133.786,California,52731.98078
  87 | 106761,126224.0464,274774.6802,New York,140237.9002
  88 | 137618,130781.1487,334313.346,Florida,166598.769
  89 | 63161,119784.9998,190648.3612,California,102990.7964
  90 | 34384,115535.0813,135123.0611,New York,78406.85364
  91 | 73431,121301.7202,210464.3542,California,111764.3688
  92 | 17125,112986.1936,101821.7734,California,63662.63887
  93 | 109497,126628.1113,280053.7997,Florida,142575.2414
  94 | 78366,122030.5434,219986.4502,California,115980.2967
  95 | 98190,124958.2421,258236.9123,New York,132915.7689
  96 | 125158,128940.9992,310271.742,California,155954.2985
  97 | 138570,130921.7444,336150.2326,New York,167412.0544
  98 | 46445,117316.3048,158394.7935,Florida,88710.46186
  99 | 134739,130355.9649,328758.3076,California,164139.2642
 100 | 96620,124726.3773,255207.593,New York,131574.5314
 101 | 140797,131250.6379,340447.2352,California,169314.5613
 102 | 44017,116957.7267,153709.9609,New York,86636.24242
 103 | 150342,132660.287,358864.3387,California,177468.7724
 104 | 127529,129291.1592,314846.5929,Florida,157979.8234
 105 | 9261,111824.8023,86648.16397,New York,56944.49153
 106 | 57905,119008.7698,180506.8948,Florida,98500.64098
 107 | 44699,117058.4475,155025.8817,New York,87218.86913
 108 | 151853,132883.4384,361779.8174,California,178759.6067
 109 | 61613,119556.3841,187661.4909,Florida,101668.3534
 110 | 120275,128219.8555,300849.9801,New York,151782.7938
 111 | 23224,113886.9217,113589.8106,California,68872.96194
 112 | 105331,126012.8575,272015.4913,Florida,139016.2635
 113 | 23501,113927.8303,114124.2829,California,69109.60065
 114 | 7092,111504.4745,82463.07255,Florida,55091.53354
 115 | 102136,125541.0053,265850.7301,California,136286.8026
 116 | 85772,123124.2953,234276.3474,Florida,122307.1786
 117 | 123288,128664.829,306663.5719,New York,154356.7737
 118 | 76992,121827.6249,217335.3134,California,114806.5004
 119 | 7715,111596.4819,83665.15275,New York,55623.75707
 120 | 29104,114755.3069,124935.2867,Florida,73896.1952
 121 | 144996,131870.7654,348549.2171,New York,172901.7308
 122 | 94169,124364.4025,250478.3818,California,129480.6633
 123 | 78261,122015.0366,219783.8524,New York,115890.5961
 124 | 140902,131266.1448,340649.833,Florida,169404.2619
 125 | 131845,129928.5658,323174.3267,Florida,161666.9449
 126 | 1269,110644.5073,71227.57814,New York,50116.99489
 127 | 43990,116953.7392,153657.8643,California,86613.17655
 128 | 49875,117822.8628,165012.9879,Florida,91640.68127
 129 | 105070,125974.3118,271511.8911,New York,138793.2935
 130 | 93591,124279.0408,249363.1293,Florida,128986.8828
 131 | 73077,121249.4398,209781.3102,New York,111461.9497
 132 | 94548,124420.3749,251209.6634,Florida,129804.4397
 133 | 151956,132898.6499,361978.5561,New York,178847.5987
 134 | 60864,119445.7684,186216.2934,California,101028.4891
 135 | 102790,125637.591,267112.6249,Florida,136845.5092
 136 | 53315,118330.8977,171650.4773,California,94579.44358
 137 | 116723,127695.2799,293996.3864,New York,148748.3508
 138 | 49288,117736.1719,163880.3698,Florida,91139.21223
 139 | 145513,131947.1183,349546.77,California,173343.3994
 140 | 148513,132390.1719,355335.2782,New York,175906.2735
 141 | 74741,121495.1869,212992.0028,California,112883.4905
 142 | 104234,125850.8475,269898.8268,California,138079.1059
 143 | 34715,115583.9649,135761.7265,Florida,78689.62408
 144 | 107457,126326.8348,276117.6141,California,140832.487
 145 | 156016,133498.2492,369812.3372,New York,182316.0217
 146 | 93879,124321.5739,249918.826,California,129232.9188
 147 | 121139,128347.4549,302517.0705,New York,152520.9015
 148 | 99283,125119.6613,260345.8588,Florida,133849.5093
 149 | 140934,131270.8707,340711.577,California,169431.5992
 150 | 70585,120881.4099,204972.9894,New York,109333.0556
 151 | 84834,122985.7671,232466.4738,California,121505.8533
 152 | 70098,120809.4875,204033.3216,New York,108917.0157
 153 | 140809,131252.4101,340470.3892,California,169324.8128
 154 | 131560,129886.4757,322624.4184,Florida,161423.4719
 155 | 143330,131624.7229,345334.6656,New York,171478.4813
 156 | 103756,125780.2543,268976.5245,Florida,137670.7546
 157 | 66195,120233.0747,196502.4724,New York,105582.7164
 158 | 108206,126437.4506,277562.8117,California,141472.3512
 159 | 141099,131295.2386,341029.945,Florida,169572.5573
 160 | 91258,123934.4927,244861.5994,New York,126993.8211
 161 | 82771,122681.0939,228485.9097,California,119743.4502
 162 | 63354,119813.5029,191020.7552,Florida,103155.6747
 163 | 43639,116901.9019,152980.6088,California,86313.32028
 164 | 66303,120249.0247,196710.8587,Florida,105674.9799
 165 | 120844,128303.888,301947.8672,California,152268.8856
 166 | 61968,119608.8121,188346.4644,Florida,101971.6268
 167 | 137388,130747.1813,333869.5604,New York,166402.282
 168 | 41818,116632.9683,149466.9844,California,84757.65569
 169 | 109162,126578.637,279407.4163,New York,142289.0538
 170 | 124648,128865.68,309287.6956,Florida,155518.6099
 171 | 150584,132696.0267,359331.2784,New York,177675.5109
 172 | 72698,121193.4674,209050.0287,California,111138.1732
 173 | 109398,126613.4906,279862.7789,New York,142490.6665
 174 | 19644,113358.211,106682.1908,Florida,65814.59883
 175 | 46632,117343.9218,158755.6105,Florida,88870.21435
 176 | 89242,123636.7607,240971.7219,New York,125271.5697
 177 | 133947,130238.9987,327230.1415,California,163462.6654
 178 | 123502,128696.4335,307076.4854,Florida,154539.592
 179 | 119535,128110.5689,299422.1481,New York,151150.6182
 180 | 151311,132803.3933,360734.0269,Florida,178296.5808
 181 | 67153,120374.5565,198350.9361,New York,106401.1276
 182 | 32321,115230.4081,131142.4969,Florida,76644.45054
 183 | 71633,121036.1833,206995.1083,New York,110228.3529
 184 | 86080,123169.7821,234870.6342,California,122570.3004
 185 | 6055,111351.3256,80462.17821,Florida,54205.63339
 186 | 29050,114747.3319,124831.0935,California,73850.06347
 187 | 79974,122268.0202,223089.0906,New York,117353.9972
 188 | 17303,113012.4814,102165.2249,Florida,63814.70273
 189 | 21265,113597.6077,109809.9147,California,67199.40514
 190 | 154934,133338.4545,367724.6153,New York,181391.6784
 191 | 155120,133365.9238,368083.5028,California,181550.5766
 192 | 126307,129110.6887,312488.7406,California,156935.8793
 193 | 155154,133370.9451,368149.1059,Florida,181579.6225
 194 | 53078,118295.8964,171193.1851,California,94376.97653
 195 | 31835,115158.6334,130204.7586,New York,76229.26494
 196 | 47467,117467.2384,160366.7453,California,89583.54765
 197 | 149605,132551.4435,357442.2952,New York,176839.1597
 198 | 75555,121615.4022,214562.618,Florida,113578.8837
 199 | 29784,114855.7324,126247.3485,California,74477.11333
 200 | 46373,117305.6715,158255.8693,New York,88648.95289
 201 | 52714,118242.1392,170490.8461,California,94066.01447
 202 | 114529,127371.26,289763.0574,California,146874.0356
 203 | 134049,130254.0625,327426.9507,Florida,163549.8031
 204 | 105163,125988.0465,271691.3349,New York,138872.7426
 205 | 84807,122981.7797,232414.3773,Florida,121482.7874
 206 | 47480,117469.1583,160391.8288,New York,89594.65343
 207 | 52985,118282.1617,171013.7414,California,94297.52743
 208 | 129319,129555.5146,318300.4028,Florida,159509.0049
 209 | 37618,116012.6932,141363.0729,New York,81169.63193
 210 | 80380,122327.9801,223872.4687,California,117700.8395
 211 | 14469,112593.9434,96697.01419,Florida,61393.64099
 212 | 141203,131310.5978,341230.6133,California,169661.4036
 213 | 143533,131654.7029,345726.3546,Florida,171651.9025
 214 | 92746,124154.2473,247732.6995,California,128265.0066
 215 | 30713,114992.9313,128039.8566,Florida,75270.75002
 216 | 70966,120937.6777,205708.13,New York,109658.5406
 217 | 113478,127216.0435,287735.1501,California,145976.1753
 218 | 5107,111211.3206,78633.00963,New York,53395.76517
 219 | 111210,126881.095,283359.0379,Florida,144038.6425
 220 | 6166,111367.7186,80676.35302,New York,54300.45973
 221 | 10758,112045.886,89536.62956,California,58223.36571
 222 | 19870,113391.5877,107118.2584,New York,66007.66868
 223 | 84817,122983.2565,232433.6723,Florida,121491.3304
 224 | 47856,117524.6877,161117.3219,Florida,89915.86699
 225 | 155761,133460.5896,369320.314,New York,182098.1774
 226 | 22390,113763.7528,111980.6053,California,68160.48294
 227 | 102474,125590.9227,266502.902,Florida,136575.5531
 228 | 73031,121242.6463,209692.5531,New York,111422.6523
 229 | 108606,126496.5244,278334.6128,Florida,141814.0678
 230 | 43074,116818.4601,151890.4398,New York,85830.64565
 231 | 85328,123058.7233,233419.6482,Florida,121927.8732
 232 | 55700,118683.1253,176252.3413,New York,96616.9285
 233 | 48759,117658.0468,162859.6628,California,90687.2921
 234 | 124538,128849.4347,309075.4503,Florida,155424.6379
 235 | 86530,123236.2402,235738.9105,California,122954.7315
 236 | 75098,121547.9103,213680.8353,New York,113188.4725
 237 | 134440,130311.8072,328181.3863,Florida,163883.8311
 238 | 23354,113906.1207,113840.646,California,68984.01982
 239 | 58848,119148.0363,182326.4159,New York,99306.23774
 240 | 3854,111026.2719,76215.3427,California,52325.33808
 241 | 11310,112127.4079,90601.71506,California,58694.93455
 242 | 36517,115850.0925,139238.6904,Florida,80229.05713
 243 | 65189,120084.5041,194561.3927,California,104723.2993
 244 | 2603,110841.5185,73801.53479,New York,51256.61958
 245 | 2696,110855.2532,73980.97854,California,51336.06868
 246 | 4908,111181.9314,78249.03858,New York,53225.76119
 247 | 18307,113160.7567,104102.4457,Florida,64672.41127
 248 | 145420,131933.3836,349367.3263,California,173263.9503
 249 | 124967,128912.7914,309903.2069,New York,155791.1289
 250 | 81122,122437.5621,225304.1597,California,118334.7237
 251 | 48147,117567.6639,161678.8072,New York,90164.46578
 252 | 107504,126333.776,276208.3008,California,140872.6387
 253 | 78966,122119.1542,221144.1518,Florida,116492.8715
 254 | 11572,112166.1013,91107.24478,New York,58918.75889
 255 | 17929,113104.932,103373.0936,Florida,64349.48913
 256 | 135016,130396.8735,329292.7799,New York,164375.9029
 257 | 140499,131206.6279,339872.2434,California,169059.9825
 258 | 70972,120938.5638,205719.707,Florida,109663.6663
 259 | 23044,113860.3385,113242.5001,New York,68719.18949
 260 | 62977,119757.8258,190293.3327,California,102833.6068
 261 | 127949,129353.1867,315656.9841,Florida,158338.6258
 262 | 140062,131142.0898,339029.0507,California,168686.6571
 263 | 142634,131521.9344,343991.7317,Florida,170883.8945
 264 | 51407,118049.1155,167968.9861,California,92949.45565
 265 | 71393,121000.739,206532.0276,Florida,110023.323
 266 | 90687,123850.1648,243759.8533,New York,126506.0207
 267 | 95482,124558.3123,253011.8189,California,130602.3478
 268 | 79898,122256.7962,222942.4484,New York,117289.0711
 269 | 80315,122318.3806,223747.051,Florida,117645.3106
 270 | 116953,127729.2474,294440.1721,New York,148944.8378
 271 | 77184,121855.9803,217705.778,California,114970.5243
 272 | 141804,131399.3563,342390.2444,New York,170174.8327
 273 | 51183,118016.0342,167536.7775,Florida,92758.09438
 274 | 109716,126660.4543,280476.3608,Florida,142762.3312
 275 | 140198,131162.1749,339291.463,New York,168802.8408
 276 | 8318,111685.5357,84828.64289,California,56138.89476
 277 | 130650,129752.0827,320868.571,Florida,160646.0668
 278 | 132796,130069.0138,325009.2838,New York,162479.376
 279 | 114589,127380.1211,289878.8276,Florida,146925.293
 280 | 14349,112576.2213,96465.47386,New York,61291.12602
 281 | 74459,121453.5399,212447.883,Florida,112642.5803
 282 | 78709,122081.1992,220648.2696,New York,116273.3187
 283 | 70529,120873.1396,204864.9373,California,109285.2152
 284 | 63481,119832.2588,191265.802,Florida,103264.1697
 285 | 12968,112372.2689,93800.83059,California,60111.34964
 286 | 7251,111527.9563,82769.86348,New York,55227.36587
 287 | 28913,114727.0991,124566.7516,Florida,73733.02555
 288 | 57470,118944.527,179667.5611,California,98129.02423
 289 | 39280,116258.1449,144569.9064,New York,82589.46419
 290 | 140284,131174.8757,339457.4003,California,168876.3098
 291 | 65509,120131.7631,195178.8336,California,104996.6726
 292 | 115538,127520.2737,291709.9257,Florida,147736.0156
 293 | 155075,133359.278,367996.6752,California,181512.1335
 294 | 54112,118448.6022,173188.2909,New York,95260.31381
 295 | 50269,117881.0505,165773.212,California,91977.27207
 296 | 90441,123813.8344,243285.1957,New York,126295.865
 297 | 146667,132117.5463,351773.4162,Florida,174329.2516
 298 | 81041,122425.5996,225147.87,California,118265.5261
 299 | 122666,128572.9692,305463.4212,New York,153825.4044
 300 | 52746,118246.8651,170552.5902,California,94093.35179
 301 | 139181,131011.9797,337329.1588,California,167934.0264
 302 | 63457,119828.7144,191219.494,Florida,103243.6667
 303 | 130989,129802.1478,321522.6724,New York,160935.6715
 304 | 67877,120481.4801,199747.896,Florida,107019.6345
 305 | 145505,131945.9368,349531.334,New York,173336.5651
 306 | 28236,114627.1167,123260.4783,California,73154.67029
 307 | 113363,127199.0598,287513.2573,Florida,145877.9318
 308 | 134787,130363.0537,328850.9238,New York,164180.2702
 309 | 158727,133898.622,375043.2191,California,184632.0056
 310 | 120520,128256.0382,301322.7083,Florida,151992.0952
 311 | 60472,119387.876,185459.9283,California,100693.6069
 312 | 154106,133216.1717,366126.987,Florida,180684.3252
 313 | 40219,116396.8207,146381.7095,California,83391.64379
 314 | 84406,122922.5582,231640.6467,Florida,121140.2166
 315 | 20629,113503.6803,108582.751,New York,66656.07583
 316 | 87536,123384.8108,237679.9902,California,123814.1486
 317 | 118530,127962.1459,297482.9979,New York,150292.0553
 318 | 129325,129556.4007,318311.9798,Florida,159514.1307
 319 | 44466,117024.037,154576.3076,New York,87019.81924
 320 | 55907,118713.696,176651.7484,California,96793.76682
 321 | 65694,120159.0848,195535.7916,New York,105154.7165
 322 | 148622,132406.2696,355545.594,Florida,175999.3913
 323 | 140627,131225.5315,340119.2197,Florida,169169.3318
 324 | 156713,133601.1853,371157.2006,New York,182911.4628
 325 | 100606,125315.048,262898.5909,California,134979.7368
 326 | 24830,114124.1031,116688.592,Florida,70244.95388
 327 | 141159,131304.0997,341145.7152,New York,169623.8148
 328 | 101587,125459.9265,264791.4331,Florida,135817.7966
 329 | 1215,110636.5323,71123.385,New York,50070.86316
 330 | 13269,112416.722,94381.61091,Florida,60368.49134
 331 | 155679,133448.4795,369162.0948,New York,182028.1255
 332 | 50634,117934.9554,166477.4805,California,92289.08842
 333 | 158637,133885.3304,374869.5639,Florida,184555.1194
 334 | 101322,125420.7901,264280.1149,California,135591.4094
 335 | 28980,114736.994,124696.0283,New York,73790.26307
 336 | 130675,129755.7748,320916.8085,Florida,160667.424
 337 | 84533,122941.3141,231885.6935,California,121248.7116
 338 | 101223,125406.1693,264089.0941,New York,135506.8346
 339 | 123282,128663.9429,306651.9948,California,154351.6479
 340 | 79009,122125.5046,221227.1204,California,116529.6061
 341 | 109841,126678.9148,280717.5486,Florida,142869.1176
 342 | 96021,124637.9143,254051.8209,California,131062.8109
 343 | 136849,130667.5793,332829.5584,New York,165941.819
 344 | 144390,131781.2685,347379.9385,California,172384.0302
 345 | 109658,126651.8885,280364.4496,New York,142712.7823
 346 | 50050,117848.7076,165350.6509,Florida,91790.18226
 347 | 60170,119343.2753,184877.2185,California,100435.6109
 348 | 112043,127004.1162,284966.3136,New York,144750.2672
 349 | 103519,125745.2531,268519.2324,California,137468.2876
 350 | 132029,129955.7397,323529.3552,New York,161824.1346
 351 | 51373,118044.0942,167903.383,California,92920.40974
 352 | 69518,120723.8305,202914.21,Florida,108421.5267
 353 | 107707,126363.756,276599.9898,New York,141046.0598
 354 | 125384,128974.3759,310707.8096,Florida,156147.3684
 355 | 156397,133554.517,370547.4778,New York,182641.5067
 356 | 118745,127993.8981,297897.841,California,150475.728
 357 | 36008,115774.9211,138256.5735,Florida,79794.22283
 358 | 7959,111632.517,84135.95141,New York,55832.20416
 359 | 121607,128416.5713,303420.0778,California,152920.7099
 360 | 113168,127170.2613,287137.0042,Florida,145711.345
 361 | 92665,124142.2849,247576.4097,California,128195.809
 362 | 36840,115897.7946,139861.9198,Florida,80504.99325
 363 | 144661,131821.291,347902.8337,California,172615.5432
 364 | 62251,119650.6068,188892.5137,Florida,102213.3913
 365 | 49407,117753.7464,164109.9806,New York,91240.87291
 366 | 127740,129322.3207,315253.718,California,158160.0789
 367 | 6101,111358.1191,80550.93534,New York,54244.9308
 368 | 142977,131572.5902,344653.5511,Florida,171176.9165
 369 | 138529,130915.6893,336071.123,New York,167377.0285
 370 | 122905,128608.2658,305924.5723,California,154029.5801
 371 | 66102,120219.3401,196323.0287,New York,105503.2673
 372 | 18930,113252.7642,105304.5259,Florida,65204.63479
 373 | 18903,113248.7767,105252.4293,Florida,65181.56893
 374 | 140704,131236.9032,340267.7914,New York,169235.1122
 375 | 112110,127014.0111,285095.5903,California,144807.5047
 376 | 143046,131582.7805,344786.6868,Florida,171235.8626
 377 | 50864,117968.9228,166921.2661,New York,92485.57543
 378 | 132160,129975.0864,323782.1201,Florida,161936.0467
 379 | 68920,120635.5151,201760.3674,New York,107910.6604
 380 | 157947,133783.428,373538.207,Florida,183965.6583
 381 | 120687,128280.7015,301644.9353,New York,152134.7618
 382 | 3372,110955.0879,75285.32239,California,51913.56964
 383 | 53012,118286.1492,171065.8379,Florida,94320.5933
 384 | 64233,119943.3176,192716.7881,California,103906.5968
 385 | 102541,125600.8176,266632.1787,New York,136632.7906
 386 | 27996,114591.6724,122797.3976,Florida,72949.64036
 387 | 3111,110916.5422,74781.72217,California,51690.5996
 388 | 66932,120341.9182,197924.516,New York,106212.3292
 389 | 118012,127885.6453,296483.5154,California,149849.5324
 390 | 18192,113143.773,103880.5529,California,64574.16776
 391 | 83511,122790.3805,229913.7417,Florida,120375.6258
 392 | 123767,128735.5699,307587.8037,California,154765.9792
 393 | 44424,117017.8343,154495.2685,New York,86983.939
 394 | 143423,131638.4576,345514.1093,California,171557.9304
 395 | 127190,129241.0942,314192.4915,New York,157690.2186
 396 | 22014,113708.2234,111255.1123,Florida,67839.26938
 397 | 148327,132362.7026,354976.3907,California,175747.3753
 398 | 4852,111173.6611,78140.98643,New York,53177.92087
 399 | 87342,123356.16,237305.6667,California,123648.4161
 400 | 12412,112290.1563,92728.02707,California,59636.36364
 401 | 66380,120260.3964,196859.4305,Florida,105740.7603
 402 | 135781,130509.8522,330768.8495,New York,165029.4358
 403 | 154047,133207.4583,366013.1464,Florida,180633.922
 404 | 91262,123935.0835,244869.3174,New York,126997.2382
 405 | 143575,131660.9056,345807.3938,California,171687.7827
 406 | 89669,123699.822,241795.6195,Florida,125636.3521
 407 | 3737,111008.9928,75989.59088,New York,52225.38599
 408 | 12816,112349.8208,93507.54618,California,59981.49735
 409 | 46750,117361.3485,158983.2918,Florida,88971.02073
 410 | 16708,112924.6091,101017.1708,California,63306.39937
 411 | 11277,112122.5343,90538.04147,Florida,58666.74293
 412 | 32758,115294.9462,131985.6896,California,77017.77587
 413 | 131074,129814.701,321686.6801,Florida,161008.2863
 414 | 33729,115438.348,133859.2368,New York,77847.29279
 415 | 56708,118831.9913,178197.28,California,97478.0542
 416 | 43245,116843.7142,152220.3848,New York,85976.72948
 417 | 117945,127875.7505,296354.2388,Florida,149792.2949
 418 | 93533,124270.4751,249251.2181,New York,128937.3339
 419 | 36345,115824.6907,138906.8159,California,80082.11902
 420 | 123150,128644.4486,306397.3005,New York,154238.8815
 421 | 146767,132132.3147,351966.3665,Florida,174414.6808
 422 | 125425,128980.4309,310786.9192,Florida,156182.3943
 423 | 26154,114319.6374,119243.2536,New York,71376.03566
 424 | 113132,127164.9447,287067.5421,California,145680.5905
 425 | 159191,133967.1476,375938.5084,Florida,185028.3968
 426 | 23281,113895.3397,113699.7923,New York,68921.65655
 427 | 145038,131876.9681,348630.2563,Florida,172937.611
 428 | 119016,128033.9206,298420.7362,New York,150707.2409
 429 | 159570,134023.1201,376669.7899,Florida,185352.1732
 430 | 66705,120308.3938,197486.5188,New York,106018.405
 431 | 96720,124741.1458,255400.5433,California,131659.9605
 432 | 77031,121833.3846,217410.564,Florida,114839.8177
 433 | 56584,118813.6785,177958.0217,California,97372.12207
 434 | 34269,115518.0976,134901.1683,New York,78308.61013
 435 | 43002,116807.8268,151751.5156,Florida,85769.13667
 436 | 90606,123838.2024,243603.5636,California,126436.8231
 437 | 21297,113602.3336,109871.6588,New York,67226.74247
 438 | 147448,132232.8879,353280.3578,California,174996.4532
 439 | 11931,112219.12,91799.93626,California,59225.44949
 440 | 62868,119741.7282,190083.0169,Florida,102740.489
 441 | 107864,126386.9425,276902.9217,California,141180.1836
 442 | 126763,129178.0329,313368.5938,New York,157325.4362
 443 | 48320,117593.2133,162012.6111,California,90312.25819
 444 | 132750,130062.2203,324920.5267,New York,162440.0786
 445 | 90232,123782.9684,242881.9296,Florida,126117.3181
 446 | 11415,112142.9148,90804.31285,California,58784.63514
 447 | 136367,130596.3953,331899.5381,New York,165530.0505
 448 | 48599,117634.4173,162550.9424,California,90550.60548
 449 | 131209,129834.6384,321947.163,New York,161123.6156
 450 | 44805,117074.1021,155230.409,California,87309.42402
 451 | 27745,114554.6036,122313.0924,Florida,72735.21323
 452 | 56428,118790.6397,177657.0193,New York,97238.85262
 453 | 22961,113848.0807,113082.3514,Florida,68648.28331
 454 | 127002,129213.3295,313829.745,New York,157529.6118
 455 | 42722,116766.4752,151211.2548,California,85529.93509
 456 | 36880,115903.702,139939.0999,Florida,80539.1649
 457 | 134020,130249.7797,327370.9952,New York,163525.0287
 458 | 105406,126023.9338,272160.204,California,139080.3354
 459 | 135965,130537.0261,331123.878,Florida,165186.6254
 460 | 22609,113796.0957,112403.1664,California,68347.57275
 461 | 48592,117633.3835,162537.4359,Florida,90544.62544
 462 | 45646,117198.3048,156853.1208,California,88027.88306
 463 | 18687,113216.8769,104835.6567,Florida,64997.04199
 464 | 159134,133958.7296,375828.5267,New York,184979.7022
 465 | 25194,114177.8603,117390.931,California,70555.91594
 466 | 49370,117748.2821,164038.589,New York,91209.26412
 467 | 83997,122862.1552,230851.4801,Florida,120790.8114
 468 | 127102,129228.0979,314022.6953,New York,157615.041
 469 | 112617,127088.8871,286073.8482,California,145240.6305
 470 | 18790,113232.0884,105034.3955,New York,65085.034
 471 | 31530,115113.5896,129616.2603,Florida,75968.70607
 472 | 154761,133312.905,367390.8113,Florida,181243.886
 473 | 62322,119661.0924,189029.5084,New York,102274.046
 474 | 138389,130895.0135,335800.9926,California,167257.4277
 475 | 54437,118496.5997,173815.3793,Florida,95537.9585
 476 | 128678,129460.8488,317063.5916,New York,158961.4042
 477 | 36374,115828.9736,138962.7715,Florida,80106.89347
 478 | 91354,123948.6704,245046.8317,New York,127075.833
 479 | 159026,133942.7797,375620.1405,Florida,184887.4387
 480 | 21362,113611.9331,109997.0765,New York,67282.27141
 481 | 33021,115333.7873,132493.1489,California,77242.4545
 482 | 135411,130455.2089,330054.9335,Florida,164713.348
 483 | 41996,116659.2562,149810.4359,California,84909.71956
 484 | 129894,129640.4332,319409.8669,New York,160000.2225
 485 | 29076,114751.1717,124881.2606,Florida,73872.27504
 486 | 60970,119461.4229,186420.8207,California,101119.044
 487 | 68150,120521.798,200274.6503,New York,107252.8561
 488 | 79611,122214.4107,222388.6811,California,117043.8895
 489 | 125073,128928.446,310107.7342,California,155881.6838
 490 | 108627,126499.6258,278375.1323,Florida,141832.0079
 491 | 38547,116149.8921,143155.5809,California,81963.26862
 492 | 109403,126614.229,279872.4264,New York,142494.938
 493 | 110385,126759.2552,281767.1981,California,143333.8521
 494 | 27445,114510.2982,121734.2416,New York,72478.92582
 495 | 99603,125166.9203,260963.2997,Florida,134122.8826
 496 | 10372,111988.8798,88791.8415,California,57893.60924
 497 | 146341,132069.4011,351144.3983,New York,174050.7527
 498 | 20181,113437.5176,107718.3338,California,66273.3533
 499 | 105465,126032.6472,272274.0447,California,139130.7386
 500 | 58528,119100.7772,181708.975,Florida,99032.8645
 501 | 107739,126368.4819,276661.7339,New York,141073.3972
 502 | 125610,129007.7526,311143.8772,Florida,156340.4382
 503 | 45698,117205.9844,156953.455,New York,88072.30621
 504 | 90555,123830.6705,243505.159,California,126393.2542
 505 | 19468,113332.2185,106342.5983,Florida,65664.24355
 506 | 100506,125300.2795,262705.6406,New York,134894.3077
 507 | 72494,121163.3397,208656.4101,California,110963.8978
 508 | 63372,119816.1612,191055.4862,Florida,103171.0519
 509 | 41878,116641.8294,149582.7545,California,84808.91317
 510 | 105962,126106.0464,273233.0075,Florida,139555.3214
 511 | 23028,113857.9755,113211.6281,California,68705.52083
 512 | 55229,118613.5659,175343.5455,Florida,96214.55727
 513 | 57839,118999.0226,180379.5476,New York,98444.25774
 514 | 112421,127059.941,285695.6657,California,145073.1894
 515 | 104830,125938.8675,271048.8105,New York,138588.2636
 516 | 105004,125964.5646,271384.5439,Florida,138736.9103
 517 | 33474,115400.6884,133367.2136,New York,77629.44849
 518 | 101381,125429.5035,264393.9555,California,135641.8126
 519 | 49895,117825.8165,165051.5779,New York,91657.76709
 520 | 140901,131265.9971,340647.9035,Florida,169403.4076
 521 | 99011,125079.4911,259821.0341,Florida,133617.1421
 522 | 25140,114169.8853,117286.7378,New York,70509.78421
 523 | 88069,123463.5267,238708.4152,California,124269.4859
 524 | 5954,111336.4094,80267.29844,Florida,54119.34996
 525 | 146657,132116.0694,351754.1212,New York,174320.7087
 526 | 120300,128223.5476,300898.2177,Florida,151804.1511
 527 | 153919,133188.5546,365766.17,New York,180524.5727
 528 | 6952,111483.7986,82192.94216,Florida,54971.93275
 529 | 24538,114080.9792,116125.1772,New York,69995.5008
 530 | 33718,115436.7234,133838.0123,California,77837.89559
 531 | 60311,119364.0988,185149.2784,Florida,100556.066
 532 | 158104,133806.6145,373841.1389,California,184099.7821
 533 | 120265,128218.3786,300830.6851,New York,151774.2509
 534 | 122843,128599.1094,305804.9431,Florida,153976.614
 535 | 156926,133632.6421,371568.1847,California,183093.4268
 536 | 50112,117857.864,165470.28,New York,91843.14832
 537 | 12068,112239.3528,92064.27813,California,59342.48741
 538 | 78098,121990.964,219469.3435,California,115751.3466
 539 | 69762,120759.8655,203385.0087,Florida,108629.9738
 540 | 156672,133595.1302,371078.091,California,182876.4368
 541 | 110066,126712.1438,281151.6868,New York,143061.3332
 542 | 149352,132514.0793,356954.131,California,176623.024
 543 | 123926,128759.0518,307894.5946,New York,154901.8116
 544 | 155584,133434.4494,368978.7921,Florida,181946.9678
 545 | 59551,119251.8585,183682.8563,California,99906.80457
 546 | 32892,115314.736,132244.243,New York,77132.25091
 547 | 148355,132366.8378,355030.4168,California,175771.2955
 548 | 34087,115491.219,134549.9988,New York,78153.1291
 549 | 9153,111808.8523,86439.77767,California,56852.22806
 550 | 141090,131293.9095,341012.5795,Florida,169564.8687
 551 | 30917,115023.059,128433.4751,New York,75445.02546
 552 | 116032,127593.2299,292663.1,Florida,148158.0355
 553 | 111403,126909.5981,283731.4319,New York,144203.5207
 554 | 109089,126567.856,279266.5626,California,142226.6905
 555 | 147916,132302.0043,354183.3651,Florida,175396.2616
 556 | 80883,122402.2655,224843.0086,New York,118130.5481
 557 | 69933,120785.1196,203714.9537,California,108776.0576
 558 | 68302,120544.2461,200567.9347,Florida,107382.7084
 559 | 83794,122832.1752,230459.791,California,120617.3903
 560 | 118649,127979.7204,297712.6087,Florida,150393.716
 561 | 66766,120317.4026,197604.2185,California,106070.5168
 562 | 130880,129786.0502,321312.3566,Florida,160842.5538
 563 | 114090,127306.4265,288916.0057,New York,146499.0017
 564 | 56983,118872.6046,178727.8933,California,97712.98433
 565 | 90073,123759.4865,242575.1387,New York,125981.4858
 566 | 26750,114407.6574,120393.2372,Florida,71885.19331
 567 | 94859,124466.3048,251809.7387,New York,130070.1243
 568 | 64520,119985.7031,193270.5554,California,104151.7784
 569 | 66882,120334.534,197828.0408,New York,106169.6146
 570 | 114904,127426.6417,290486.621,Florida,147194.3948
 571 | 108270,126446.9024,277686.2998,Florida,141527.0259
 572 | 76026,121684.9616,215471.4138,New York,113981.2549
 573 | 158668,133889.9086,374929.3785,California,184581.6024
 574 | 5885,111326.2192,80134.16275,Florida,54060.40386
 575 | 32007,115184.0351,130536.6331,New York,76376.20305
 576 | 58843,119147.2979,182316.7684,Florida,99301.96628
 577 | 57863,119002.567,180425.8557,New York,98464.76074
 578 | 146290,132061.8692,351045.9937,Florida,174007.1838
 579 | 92831,124166.8005,247896.7072,New York,128337.6214
 580 | 149026,132465.9341,356325.1131,California,176344.525
 581 | 68638,120593.8681,201216.2476,Florida,107669.7503
 582 | 48519,117622.6025,162396.5822,California,90482.26217
 583 | 35910,115760.448,138067.4822,New York,79710.50227
 584 | 41614,116602.8407,149073.3658,Florida,84583.38025
 585 | 137713,130795.1787,334496.6487,California,166679.9267
 586 | 29287,114782.3332,125288.3857,New York,74052.53052
 587 | 94648,124435.1434,251402.6136,California,129889.8688
 588 | 41578,116597.524,149003.9037,California,84552.62576
 589 | 96008,124635.9944,254026.7374,Florida,131051.7051
 590 | 78630,122069.5322,220495.8389,California,116205.8296
 591 | 19242,113298.8418,105906.5307,New York,65471.1737
 592 | 92507,124118.9507,247271.5483,California,128060.831
 593 | 92171,124069.3287,246623.2354,New York,127773.7891
 594 | 70074,120805.9431,203987.0135,Florida,108896.5127
 595 | 149598,132550.4097,357428.7887,California,176833.1797
 596 | 6975,111487.1954,82237.32073,New York,54991.58145
 597 | 155563,133431.3481,368938.2725,California,181929.0277
 598 | 63024,119764.767,190384.0193,California,102873.7585
 599 | 9960,111928.0338,87996.88638,Florida,57541.6412
 600 | 19291,113306.0783,106001.0764,New York,65513.03398
 601 | 132449,130017.7672,324339.7464,Florida,162182.9369
 602 | 3089,110913.2932,74739.27311,New York,51671.80519
 603 | 104168,125841.1003,269771.4796,California,138022.7227
 604 | 153606,133142.3294,365162.2357,Florida,180257.1795
 605 | 13316,112423.6631,94472.29754,New York,60408.64304
 606 | 151611,132847.6987,361312.8777,California,178552.8682
 607 | 155716,133453.9438,369233.4864,Florida,182059.7343
 608 | 76520,121757.9178,216424.5881,California,114403.2748
 609 | 42221,116692.4852,150244.574,Florida,85101.93511
 610 | 126483,129136.6812,312828.3331,California,157086.2346
 611 | 118217,127915.9207,296879.0635,Florida,150024.6621
 612 | 91556,123978.5027,245436.5912,New York,127248.3999
 613 | 123093,128636.0305,306287.3188,California,154190.1869
 614 | 90163,123772.7781,242748.7939,New York,126058.372
 615 | 104391,125874.034,270201.7588,Florida,138213.2296
 616 | 61243,119501.7408,186947.5749,New York,101352.2656
 617 | 60782,119433.6582,186058.0742,California,100958.4372
 618 | 16787,112936.2762,101169.6015,New York,63373.88839
 619 | 152746,133015.3207,363502.8633,Florida,179522.4889
 620 | 159000,133938.9399,375569.9734,Florida,184865.2271
 621 | 62726,119720.757,189809.0275,New York,102619.1797
 622 | 148420,132376.4373,355155.8345,California,175826.8244
 623 | 135886,130525.3591,330971.4473,Florida,165119.1364
 624 | 99774,125192.1744,261293.2446,New York,134268.9664
 625 | 14367,112578.8796,96500.20491,Florida,61306.50327
 626 | 136326,130590.3403,331820.4285,New York,165495.0246
 627 | 33519,115407.3342,133454.0412,Florida,77667.8916
 628 | 122931,128612.1056,305974.7394,New York,154051.7917
 629 | 73289,121280.749,210190.3648,California,111643.0594
 630 | 67289,120394.6416,198613.3484,Florida,106517.3112
 631 | 22876,113835.5275,112918.3436,California,68575.66854
 632 | 125112,128934.2057,310182.9848,New York,155915.0011
 633 | 88568,123537.2213,239671.237,Florida,124695.7773
 634 | 144841,131847.8743,348250.1442,California,172769.3156
 635 | 159238,133974.0888,376029.195,New York,185068.5485
 636 | 127074,129223.9628,313968.6692,California,157591.1208
 637 | 67697,120454.8969,199400.5855,California,106865.8621
 638 | 65307,120101.9308,194789.074,Florida,104824.1057
 639 | 84231,122896.7134,231302.9837,California,120990.7156
 640 | 8882,111768.8298,85916.88243,New York,56620.7151
 641 | 129441,129573.5321,318535.8022,California,159613.2285
 642 | 148278,132355.4661,354881.8451,New York,175705.515
 643 | 58228,119056.4719,181130.1242,Florida,98776.57709
 644 | 136903,130675.5543,332933.7515,California,165987.9507
 645 | 4187,111075.4508,76857.86711,New York,52609.81711
 646 | 80546,122352.4958,224192.7661,California,117842.6519
 647 | 36302,115818.3403,138823.8473,New York,80045.38449
 648 | 36327,115822.0324,138872.0849,California,80066.74177
 649 | 103813,125788.6723,269086.5062,Florida,137719.4492
 650 | 117577,127821.4025,295644.1818,New York,149477.9157
 651 | 154222,133233.3031,366350.8093,Florida,180783.423
 652 | 63645,119856.4791,191582.2405,New York,103404.2734
 653 | 45968,117245.8592,157474.4207,California,88302.96488
 654 | 60822,119439.5656,186135.2543,Florida,100992.6089
 655 | 107750,126370.1064,276682.9584,New York,141082.7944
 656 | 109510,126630.0312,280078.8832,California,142586.3472
 657 | 147647,132262.2771,353664.3289,Florida,175166.4572
 658 | 9316,111832.9249,86754.28662,California,56991.47755
 659 | 70319,120842.1258,204459.7417,Florida,109105.8141
 660 | 138525,130915.0986,336063.405,California,167373.6113
 661 | 122434,128538.7064,305015.7765,Florida,153627.2089
 662 | 91086,123909.091,244529.7249,New York,126846.883
 663 | 32205,115213.2767,130918.6746,California,76545.35274
 664 | 18989,113261.4776,105418.3665,New York,65255.03798
 665 | 143683,131676.8555,346015.7801,Florida,171780.0462
 666 | 81836,122543.0089,226681.8247,New York,118944.6878
 667 | 139592,131072.678,338122.1844,California,168285.1402
 668 | 54073,118442.8425,173113.0403,New York,95226.99644
 669 | 11977,112225.9135,91888.69339,Florida,59264.74689
 670 | 133956,130240.3279,327247.507,Florida,163470.354
 671 | 133110,130115.3867,325615.1477,New York,162747.6235
 672 | 9063,111795.5607,86266.12243,California,56775.34184
 673 | 36025,115777.4317,138289.3751,Florida,79808.74578
 674 | 40178,116390.7656,146302.5999,New York,83356.61784
 675 | 29814,114860.1629,126305.2336,Florida,74502.74207
 676 | 113466,127214.2713,287711.996,New York,145965.9238
 677 | 12585,112315.7057,93061.83105,Florida,59784.15604
 678 | 99265,125117.003,260311.1278,New York,133834.1321
 679 | 26554,114378.7113,120015.0547,California,71717.75221
 680 | 49642,117788.4523,164563.4137,Florida,91441.63138
 681 | 135489,130466.7283,330205.4347,California,164779.9827
 682 | 57784,118990.8999,180273.425,New York,98397.27172
 683 | 50884,117971.8765,166959.8561,Florida,92502.66126
 684 | 102170,125546.0266,265916.3332,California,136315.8485
 685 | 36011,115775.3641,138262.362,New York,79796.7857
 686 | 112108,127013.7157,285091.7313,California,144805.7962
 687 | 52981,118281.571,171006.0234,California,94294.11026
 688 | 60350,119369.8585,185224.529,Florida,100589.3834
 689 | 38385,116125.9672,142843.0015,California,81824.87341
 690 | 18632,113208.7542,104729.5341,New York,64950.05596
 691 | 75431,121597.0893,214323.3597,California,113472.9515
 692 | 79191,122152.3832,221578.2899,New York,116685.0871
 693 | 76485,121752.7488,216357.0555,Florida,114373.3746
 694 | 58814,119143.015,182260.8128,California,99277.19183
 695 | 71364,120996.4562,206476.0721,New York,109998.5485
 696 | 88650,123549.3314,239829.4563,California,124765.8292
 697 | 133587,130185.8323,326535.5205,California,163155.1205
 698 | 112125,127016.2263,285124.5329,Florida,144820.3191
 699 | 106384,126168.3693,274047.2577,New York,139915.8323
 700 | 1681,110705.3533,72022.53327,Florida,50468.96294
 701 | 50720,117947.6562,166643.4177,New York,92362.55748
 702 | 128215,129392.4708,316170.2318,California,158565.8673
 703 | 35274,115666.5206,136840.3185,Florida,79167.17296
 704 | 64229,119942.7269,192709.0701,New York,103903.1796
 705 | 57750,118985.8787,180207.8219,California,98368.22581
 706 | 155883,133478.6071,369555.7134,Florida,182202.4009
 707 | 24815,114121.8878,116659.6494,California,70232.13951
 708 | 5210,111226.5321,78831.74841,Florida,53483.75718
 709 | 83476,122785.2115,229846.2091,California,120345.7256
 710 | 110481,126773.4329,281952.4304,Florida,143415.8641
 711 | 9079,111797.9237,86296.99447,New York,56789.0105
 712 | 72359,121143.4023,208395.9273,California,110848.5685
 713 | 111501,126924.0712,283920.5232,New York,144287.2413
 714 | 48082,117558.0644,161553.3895,Florida,90108.93684
 715 | 42770,116773.564,151303.871,New York,85570.94108
 716 | 58265,119061.9362,181201.5158,California,98808.18587
 717 | 15132,112691.8583,97976.2745,New York,61960.03617
 718 | 92114,124060.9107,246513.2537,Florida,127725.0945
 719 | 24874,114130.6012,116773.4901,Florida,70282.5427
 720 | 129228,129542.0753,318124.8181,New York,159431.2644
 721 | 2296,110796.1793,73209.17745,California,50994.35213
 722 | 40501,116438.4678,146925.8293,Florida,83632.55396
 723 | 46177,117276.7253,157877.6868,New York,88481.51178
 724 | 139729,131092.9108,338386.5263,Florida,168402.1781
 725 | 45282,117144.5476,156150.7818,New York,87716.921
 726 | 145719,131977.5413,349944.2476,Florida,173519.3834
 727 | 150394,132667.9666,358964.6729,New York,177513.1956
 728 | 154778,133315.4157,367423.6129,California,181258.409
 729 | 82971,122710.6308,228871.8103,Florida,119914.3085
 730 | 120814,128299.4574,301889.9821,California,152243.2568
 731 | 109821,126675.9611,280678.9586,New York,142852.0318
 732 | 149129,132481.1456,356523.8519,Florida,176432.517
 733 | 135073,130405.2915,329402.7615,California,164424.5975
 734 | 9628,111879.0025,87356.29147,New York,57258.01646
 735 | 150311,132655.7088,358804.5242,California,177442.2894
 736 | 117241,127771.7805,294995.8688,California,149190.8738
 737 | 95584,124573.3761,253208.6282,Florida,130689.4855
 738 | 69018,120649.9882,201949.4587,California,107994.381
 739 | 72838,121214.1432,209320.1591,New York,111257.774
 740 | 87391,123363.3966,237400.2123,California,123690.2763
 741 | 133567,130182.8786,326496.9304,New York,163138.0347
 742 | 49559,117776.1945,164403.265,Florida,91370.72519
 743 | 137973,130833.5767,334998.3195,California,166902.0425
 744 | 7736,111599.5833,83705.6723,New York,55641.69719
 745 | 10707,112038.3541,89438.22492,California,58179.79685
 746 | 125850,129043.1969,311606.9579,New York,156545.4682
 747 | 65352,120108.5766,194875.9016,California,104862.5488
 748 | 154992,133347.0202,367836.5264,Florida,181441.2273
 749 | 135611,130484.7458,330440.834,New York,164884.2062
 750 | 98169,124955.1407,258196.3928,Florida,132897.8287
 751 | 38099,116083.7295,142291.1637,New York,81580.54608
 752 | 91798,124014.2424,245903.5309,California,127455.1384
 753 | 78442,122041.7675,220133.0924,Florida,116045.2229
 754 | 131802,129922.2153,323091.3581,New York,161630.2104
 755 | 107178,126285.6308,275579.2829,California,140594.1397
 756 | 2626,110844.9152,73845.91335,Florida,51276.26828
 757 | 84533,122941.3141,231885.6935,California,121248.7116
 758 | 19707,113367.5151,106803.7495,Florida,65868.41919
 759 | 13123,112395.16,94099.90352,California,60243.7648
 760 | 3797,111017.8538,76105.36105,Florida,52276.64348
 761 | 132703,130055.2791,324829.8401,New York,162399.9269
 762 | 22449,113772.4662,112094.446,California,68210.88613
 763 | 83026,122718.7535,228977.9329,New York,119961.2945
 764 | 27654,114541.1643,122137.5077,Florida,72657.47271
 765 | 156793,133613.0001,371311.5609,New York,182979.8061
 766 | 73771,121351.9329,211120.3851,California,112054.8279
 767 | 29469,114809.2117,125639.5552,New York,74208.01155
 768 | 134963,130389.0462,329190.5162,Florida,164330.6254
 769 | 146580,132104.6977,351605.5495,Florida,174254.9283
 770 | 82465,122635.9024,227895.4819,New York,119482.037
 771 | 80306,122317.0515,223729.6855,California,117637.622
 772 | 130189,129684.0001,319979.0702,Florida,160252.2384
 773 | 120735,128287.7904,301737.5514,New York,152175.7678
 774 | 67191,120380.1685,198424.2572,Florida,106433.5906
 775 | 83593,122802.4906,230071.961,New York,120445.6777
 776 | 108131,126426.3742,277418.099,Florida,141408.2794
 777 | 3574,110984.9202,75675.08194,New York,52086.1365
 778 | 98311,124976.1119,258470.3821,California,133019.1381
 779 | 145072,131881.9894,348695.8593,Florida,172966.6569
 780 | 133439,130163.975,326249.9541,California,163028.6854
 781 | 70521,120871.9581,204849.5013,New York,109278.3809
 782 | 111317,126896.8972,283565.4947,Florida,144130.0517
 783 | 106821,126232.9075,274890.4504,California,140289.1577
 784 | 107973,126403.0401,277113.2375,New York,141273.3013
 785 | 10488,112006.0112,89015.66382,California,57992.70704
 786 | 90061,123757.7143,242551.9846,California,125971.2343
 787 | 83918,122850.4881,230699.0493,Florida,120723.3224
 788 | 93580,124277.4163,249341.9047,California,128977.4856
 789 | 18947,113255.2749,105337.3274,New York,65219.15775
 790 | 60133,119337.8109,184805.8269,California,100404.0021
 791 | 150860,132736.7876,359863.8212,New York,177911.2954
 792 | 103957,125809.9389,269364.3546,Florida,137842.4672
 793 | 92330,124092.8106,246930.0263,California,127909.6214
 794 | 123073,128633.0769,306248.7288,New York,154173.101
 795 | 142001,131428.4501,342770.3565,California,170343.1281
 796 | 12564,112312.6043,93021.31149,California,59766.21593
 797 | 48789,117662.4774,162917.5479,Florida,90712.92084
 798 | 51795,118106.4171,168717.6331,New York,93280.9207
 799 | 44496,117028.4676,154634.1927,Florida,87045.44798
 800 | 35278,115667.1113,136848.0365,New York,79170.59013
 801 | 155044,133354.6998,367936.8606,California,181485.6505
 802 | 146775,132133.4962,351981.8025,Florida,174421.5151
 803 | 17432,113031.5328,102414.1308,New York,63924.90632
 804 | 107612,126349.7259,276416.687,California,140964.9022
 805 | 7214,111522.492,82698.47188,Florida,55195.75709
 806 | 107501,126333.333,276202.5122,California,140870.0758
 807 | 141301,131325.0709,341419.7045,Florida,169745.1241
 808 | 40281,116405.9772,146501.3387,California,83444.60985
 809 | 159196,133967.886,375948.1559,Florida,185032.6682
 810 | 139547,131066.0322,338035.3568,New York,168246.6971
 811 | 125783,129033.302,311477.6812,California,156488.2307
 812 | 121583,128413.0269,303373.7697,New York,152900.2069
 813 | 138546,130918.2,336103.9245,Florida,167391.5514
 814 | 133671,130198.2378,326697.5987,New York,163226.881
 815 | 95277,124528.037,252616.2709,California,130427.2181
 816 | 44700,117058.5952,155027.8112,New York,87219.72342
 817 | 89471,123670.5804,241413.578,Florida,125467.2024
 818 | 146162,132042.9656,350799.0173,Florida,173897.8345
 819 | 109909,126688.9574,280848.7548,New York,142927.2094
 820 | 31984,115180.6384,130492.2545,California,76356.55435
 821 | 127797,129330.7387,315363.6997,Florida,158208.7735
 822 | 21890,113689.9105,111015.854,New York,67733.33725
 823 | 56547,118808.2141,177886.6301,Florida,97340.51329
 824 | 142143,131449.4213,343044.3458,New York,170464.4375
 825 | 83936,122853.1464,230733.7804,Florida,120738.6997
 826 | 117801,127854.4839,296076.3904,New York,149669.2769
 827 | 35679,115726.3328,137621.7671,California,79513.16096
 828 | 139429,131048.6054,337807.6754,Florida,168145.8907
 829 | 142144,131449.569,343046.2753,California,170465.2918
 830 | 89706,123705.2863,241867.0112,New York,125667.9609
 831 | 17219,113000.0759,102003.1467,Florida,63742.94226
 832 | 129179,129534.8387,318030.2724,California,159389.4041
 833 | 27903,114577.9377,122617.9539,New York,72870.19126
 834 | 88429,123516.6931,239403.0362,California,124577.0308
 835 | 149794,132579.3559,357806.9712,California,177000.6208
 836 | 137595,130777.752,334268.9674,Florida,166579.1203
 837 | 110391,126760.1413,281778.7751,California,143338.9779
 838 | 141217,131312.6654,341257.6263,New York,169673.3637
 839 | 29605,114829.2968,125901.9675,California,74324.19518
 840 | 158771,133905.1201,375128.1173,New York,184669.5944
 841 | 101859,125500.0967,265316.2578,Florida,136050.1639
 842 | 158592,133878.6846,374782.7363,California,184516.6762
 843 | 53884,118414.9302,172748.3643,New York,95065.53537
 844 | 142240,131463.7467,343231.5076,California,170547.3037
 845 | 113736,127254.1462,288232.9618,New York,146196.5825
 846 | 70598,120883.3298,204998.073,California,109344.1613
 847 | 118793,128000.987,297990.4571,Florida,150516.734
 848 | 7888,111622.0314,83998.95672,New York,55771.54948
 849 | 45710,117207.7566,156976.609,Florida,88082.55771
 850 | 71222,120975.485,206202.0827,New York,109877.2392
 851 | 159477,134009.3854,376490.3462,California,185272.7241
 852 | 46307,117295.9243,158128.5221,Florida,88592.56966
 853 | 44151,116977.5164,153968.5142,New York,86750.71746
 854 | 58725,119129.8711,182089.087,California,99201.1599
 855 | 57267,118914.547,179275.8721,Florida,97955.60308
 856 | 135390,130452.1075,330014.4139,California,164695.4079
 857 | 145733,131979.6089,349971.2607,Florida,173531.3435
 858 | 71791,121059.5175,207299.9697,California,110363.331
 859 | 111381,126906.349,283688.9828,Florida,144184.7263
 860 | 62904,119747.0449,190152.479,New York,102771.2435
 861 | 45209,117133.7666,156009.9281,California,87654.55773
 862 | 154595,133288.3894,367070.5139,New York,181102.0736
 863 | 18651,113211.5602,104766.1946,Florida,64966.2875
 864 | 153606,133142.3294,365162.2357,New York,180257.1795
 865 | 107173,126284.8924,275569.6353,California,140589.8682
 866 | 26618,114388.1631,120138.5429,New York,71772.42685
 867 | 33472,115400.393,133363.3546,Florida,77627.73991
 868 | 2638,110846.6874,73869.06738,Florida,51286.51978
 869 | 37255,115959.0837,140662.6634,New York,80859.52417
 870 | 43391,116865.2761,152502.0922,California,86101.45602
 871 | 97670,124881.4461,257233.5709,Florida,132471.5373
 872 | 1634,110698.4122,71931.84664,New York,50428.81124
 873 | 58986,119168.4168,182592.6873,Florida,99424.12995
 874 | 56671,118826.527,178125.8884,New York,97446.44542
 875 | 105205,125994.2492,271772.374,Florida,138908.6228
 876 | 116004,127589.0947,292609.074,New York,148134.1153
 877 | 128926,129497.4746,317542.1083,California,159173.2684
 878 | 38859,116195.9697,143757.5858,Florida,82229.80752
 879 | 60549,119399.2477,185608.5,California,100759.3874
 880 | 75398,121592.2157,214259.6861,New York,113444.7599
 881 | 15801,112790.6592,99267.11183,Florida,62531.55709
 882 | 44574,117039.987,154784.6939,California,87112.08271
 883 | 93601,124280.5176,249382.4243,New York,128995.4258
 884 | 5404,111255.1829,79206.07194,California,53649.48971
 885 | 64529,119987.0323,193287.9209,California,104159.467
 886 | 17495,113040.8369,102535.6895,Florida,63978.72668
 887 | 138565,130921.006,336140.5851,California,167407.783
 888 | 79095,122138.2055,221393.0577,New York,116603.0751
 889 | 136431,130605.8471,332023.0262,California,165584.7252
 890 | 46477,117321.0307,158456.5376,New York,88737.79919
 891 | 121576,128411.9931,303360.2632,Florida,152894.2269
 892 | 18421,113177.5928,104322.409,California,64769.80049
 893 | 2682,110853.1856,73953.9655,New York,51324.1086
 894 | 9405,111846.0688,86926.01236,California,57067.50948
 895 | 20279,113451.9907,107907.4251,California,66357.07385
 896 | 25990,114295.4172,118926.8152,Florida,71235.93187
 897 | 137404,130749.5442,333900.4324,New York,166415.9507
 898 | 9869,111914.5945,87821.30163,Florida,57463.90068
 899 | 37191,115949.6319,140539.1752,New York,80804.84952
 900 | 25600,114237.8202,118174.3091,California,70902.75824
 901 | 129013,129510.3231,317709.975,Florida,159247.5918
 902 | 74278,121426.809,212098.643,New York,112487.9536
 903 | 78694,122078.984,220619.3271,California,116260.5043
 904 | 85315,123056.8034,233394.5647,Florida,121916.7675
 905 | 131636,129897.6997,322771.0607,California,161488.398
 906 | 131599,129892.2354,322699.6691,Florida,161456.7893
 907 | 148644,132409.5186,355588.0431,California,176018.1857
 908 | 80987,122417.6247,225043.6768,Florida,118219.3944
 909 | 100610,125315.6387,262906.3089,New York,134983.154
 910 | 153748,133163.3006,365436.225,California,180378.4888
 911 | 106158,126134.9926,273611.1901,New York,139722.7625
 912 | 41374,116567.3964,148610.2852,Florida,84378.35032
 913 | 152109,132921.2456,362273.7701,New York,178978.3053
 914 | 57182,118901.9938,179111.8643,California,97882.98831
 915 | 6906,111477.0051,82104.18504,New York,54932.63535
 916 | 53981,118429.2556,172935.5261,Florida,95148.40164
 917 | 66959,120345.9057,197976.6125,Florida,106235.395
 918 | 64124,119927.22,192506.4723,New York,103813.479
 919 | 100306,125270.7426,262319.7401,California,134723.4494
 920 | 146708,132123.6013,351852.5258,Florida,174364.2776
 921 | 39202,116246.6255,144419.4052,New York,82522.82946
 922 | 19561,113345.9532,106522.0421,Florida,65743.69265
 923 | 55658,118676.9226,176171.3022,New York,96581.04826
 924 | 24723,114108.3008,116482.1352,Florida,70153.5447
 925 | 52176,118162.6849,169452.7737,New York,93606.40571
 926 | 120402,128238.6114,301095.027,California,151891.2888
 927 | 35429,115689.4117,137139.3914,Florida,79299.58812
 928 | 40408,116424.7331,146746.3855,California,83553.10486
 929 | 13599,112465.4579,95018.34682,New York,60650.40749
 930 | 86851,123283.6469,236358.2809,Florida,123228.959
 931 | 4037,111053.2981,76568.4417,California,52481.67341
 932 | 131611,129894.0076,322722.8231,New York,161467.0408
 933 | 68653,120596.0834,201245.1902,California,107682.5646
 934 | 107094,126273.2253,275417.2046,California,140522.3792
 935 | 62140,119634.2139,188678.3389,Florida,102118.5649
 936 | 9494,111859.2128,87097.73811,California,57143.54142
 937 | 128989,129506.7787,317663.6669,New York,159227.0888
 938 | 134194,130275.4768,327706.7286,California,163673.6754
 939 | 126960,129207.1267,313748.7059,New York,157493.7316
 940 | 49855,117819.9091,164974.3978,Florida,91623.59544
 941 | 127494,129285.9903,314779.0603,California,157949.9232
 942 | 53778,118399.2756,172543.837,New York,94974.98049
 943 | 116989,127734.564,294509.6342,California,148975.5923
 944 | 128157,129383.9051,316058.3207,New York,158516.3184
 945 | 72165,121114.7515,208021.6037,California,110682.8359
 946 | 114314,127339.5078,289348.2144,Florida,146690.3629
 947 | 11205,112111.901,90399.11728,New York,58605.23395
 948 | 83554,122796.7309,229996.7104,Florida,120412.3603
 949 | 131981,129948.6509,323436.7391,New York,161783.1286
 950 | 32137,115203.2341,130787.4684,California,76487.26093
 951 | 54016,118434.4245,173003.0587,Florida,95178.30183
 952 | 64613,119999.4378,193449.9991,New York,104231.2275
 953 | 11624,112173.7809,91207.57892,California,58963.18204
 954 | 31587,115122.0076,129726.2419,Florida,76017.40068
 955 | 12608,112319.1025,93106.20961,California,59803.80475
 956 | 94359,124392.4625,250844.9874,Florida,129642.9786
 957 | 2307,110797.8039,73230.40198,California,51003.74933
 958 | 33161,115354.4631,132763.2792,Florida,77362.05529
 959 | 159746,134049.1125,377009.3824,New York,185502.5285
 960 | 154187,133228.1341,366283.2767,California,180753.5228
 961 | 144520,131800.4675,347630.7738,New York,172495.0881
 962 | 106777,126226.4093,274805.5523,Florida,140251.5689
 963 | 16459,112887.8357,100536.7246,New York,63093.68082
 964 | 143258,131614.0896,345195.7414,California,171416.9724
 965 | 73490,121310.4336,210578.1949,New York,111814.772
 966 | 87369,123360.1475,237357.7633,Florida,123671.4819
 967 | 51353,118041.1406,167864.7929,Florida,92903.32391
 968 | 66049,120211.5128,196220.765,New York,105457.9899
 969 | 29723,114846.7236,126129.6488,California,74425.00156
 970 | 146120,132036.7628,350717.9782,Florida,173861.9543
 971 | 15440,112737.3451,98570.56134,New York,62223.15791
 972 | 13856,112503.4128,95514.22902,Florida,60869.96038
 973 | 71829,121065.1295,207373.2908,New York,110395.794
 974 | 131154,129826.5157,321841.0403,Florida,161076.6296
 975 | 68679,120599.9232,201295.3572,New York,107704.7762
 976 | 108056,126415.2979,277273.3863,California,141344.2075
 977 | 140149,131154.9383,339196.9174,Florida,168760.9805
 978 | 56850,118852.9626,178471.2694,California,97599.36358
 979 | 47438,117462.9555,160310.7897,New York,89558.7732
 980 | 58867,119150.8423,182363.0764,Florida,99322.46927
 981 | 12914,112364.2939,93696.63744,California,60065.21791
 982 | 62574,119698.3089,189515.7431,New York,102489.3274
 983 | 53106,118300.0316,171247.2112,California,94400.89669
 984 | 123537,128701.6025,307144.018,California,154569.4922
 985 | 48901,117679.018,163133.6522,Florida,90808.60147
 986 | 105143,125985.0928,271652.7448,California,138855.6568
 987 | 63615,119852.0486,191524.3554,New York,103378.6447
 988 | 100405,125285.3634,262510.7609,California,134808.0242
 989 | 41289,116554.8432,148446.2774,New York,84305.73556
 990 | 39970,116360.0473,145901.2633,Florida,83178.92524
 991 | 43532,116886.0996,152774.1521,Florida,86221.9111
 992 | 136133,130561.8371,331448.0344,California,165330.1463
 993 | 131106,129819.4269,321748.4242,New York,161035.6236
 994 | 105127,125982.7298,271621.8728,Florida,138841.9881
 995 | 46798,117368.4374,159075.908,California,89012.02672
 996 | 97209,124813.3635,256344.0701,New York,132077.709
 997 | 54135,118451.999,173232.6695,California,95279.96251
 998 | 134970,130390.08,329204.0228,California,164336.6055
 999 | 100275.47,241926.31,227142.82,California,413956.48
1000 | 128456.23,321652.14,281692.32,California,333962.19
1001 | 161181.72,270939.86,295442.17,New York,476485.43
1002 | 


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