CHPC.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "rents = pd.read_hdf('data/rents.h5', 'rents')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pid</th>\n",
       "      <th>date</th>\n",
       "      <th>region</th>\n",
       "      <th>neighborhood</th>\n",
       "      <th>rent</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>sqft</th>\n",
       "      <th>rent_sqft</th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>county</th>\n",
       "      <th>fips_block</th>\n",
       "      <th>state</th>\n",
       "      <th>bathrooms</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5873872320</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>muskegon</td>\n",
       "      <td></td>\n",
       "      <td>600.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>-86.235567</td>\n",
       "      <td>43.219625</td>\n",
       "      <td>Muskegon</td>\n",
       "      <td>261210005004029</td>\n",
       "      <td>MI</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5873877617</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>merced</td>\n",
       "      <td>Merced</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>874.0</td>\n",
       "      <td>1.058352</td>\n",
       "      <td>-120.508000</td>\n",
       "      <td>37.330200</td>\n",
       "      <td>Merced</td>\n",
       "      <td>060470010021060</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5849836436</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>bozeman</td>\n",
       "      <td>2990 West Winds Way</td>\n",
       "      <td>1850.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1566.0</td>\n",
       "      <td>1.181354</td>\n",
       "      <td>-111.079491</td>\n",
       "      <td>45.696211</td>\n",
       "      <td>Gallatin</td>\n",
       "      <td>300310005031204</td>\n",
       "      <td>MT</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5873915596</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>myrtlebeach</td>\n",
       "      <td>LANDING ROAD</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1150.0</td>\n",
       "      <td>1.043478</td>\n",
       "      <td>-78.877855</td>\n",
       "      <td>33.727425</td>\n",
       "      <td>Horry</td>\n",
       "      <td>450510501021018</td>\n",
       "      <td>SC</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5862944298</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>fayar</td>\n",
       "      <td>2444 Jeremiah</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1425.0</td>\n",
       "      <td>0.701754</td>\n",
       "      <td>-94.193988</td>\n",
       "      <td>36.096740</td>\n",
       "      <td>Washington</td>\n",
       "      <td>051430105072017</td>\n",
       "      <td>AR</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          pid       date       region         neighborhood    rent  bedrooms  \\\n",
       "0  5873872320 2016-11-13     muskegon                        600.0       2.0   \n",
       "1  5873877617 2016-11-13       merced               Merced   925.0       2.0   \n",
       "2  5849836436 2016-11-13      bozeman  2990 West Winds Way  1850.0       3.0   \n",
       "3  5873915596 2016-11-13  myrtlebeach         LANDING ROAD  1200.0       2.0   \n",
       "4  5862944298 2016-11-13        fayar        2444 Jeremiah  1000.0       3.0   \n",
       "\n",
       "     sqft  rent_sqft   longitude   latitude      county       fips_block  \\\n",
       "0   700.0   0.857143  -86.235567  43.219625    Muskegon  261210005004029   \n",
       "1   874.0   1.058352 -120.508000  37.330200      Merced  060470010021060   \n",
       "2  1566.0   1.181354 -111.079491  45.696211    Gallatin  300310005031204   \n",
       "3  1150.0   1.043478  -78.877855  33.727425       Horry  450510501021018   \n",
       "4  1425.0   0.701754  -94.193988  36.096740  Washington  051430105072017   \n",
       "\n",
       "  state  bathrooms  \n",
       "0    MI        NaN  \n",
       "1    CA        NaN  \n",
       "2    MT        NaN  \n",
       "3    SC        NaN  \n",
       "4    AR        NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rents.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "CA = rents[rents['state']=='CA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>pid</th>\n",
       "      <th>date</th>\n",
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       "      <th>neighborhood</th>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5873877617</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>merced</td>\n",
       "      <td>Merced</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>874.0</td>\n",
       "      <td>1.058352</td>\n",
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       "      <td>37.330200</td>\n",
       "      <td>Merced</td>\n",
       "      <td>060470010021060</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>5873876292</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>chico</td>\n",
       "      <td>Chico</td>\n",
       "      <td>735.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>650.0</td>\n",
       "      <td>1.130769</td>\n",
       "      <td>-121.825955</td>\n",
       "      <td>39.719617</td>\n",
       "      <td>Butte</td>\n",
       "      <td>060070012001017</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5873889346</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>slo</td>\n",
       "      <td>Atascadero</td>\n",
       "      <td>1675.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.675000</td>\n",
       "      <td>-120.661533</td>\n",
       "      <td>35.485117</td>\n",
       "      <td>San Luis Obispo</td>\n",
       "      <td>060790125023017</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5873893871</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>santamaria</td>\n",
       "      <td>Santa Maria</td>\n",
       "      <td>1818.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1084.0</td>\n",
       "      <td>1.677122</td>\n",
       "      <td>-120.426800</td>\n",
       "      <td>34.828600</td>\n",
       "      <td>Santa Barbara</td>\n",
       "      <td>060830020061208</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>5849643168</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>redding</td>\n",
       "      <td>Wilson Ave</td>\n",
       "      <td>1050.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>0.954545</td>\n",
       "      <td>-122.325522</td>\n",
       "      <td>40.566627</td>\n",
       "      <td>Shasta</td>\n",
       "      <td>060890113004008</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "           pid       date      region neighborhood    rent  bedrooms    sqft  \\\n",
       "1   5873877617 2016-11-13      merced       Merced   925.0       2.0   874.0   \n",
       "15  5873876292 2016-11-13       chico        Chico   735.0       0.0   650.0   \n",
       "20  5873889346 2016-11-13         slo   Atascadero  1675.0       3.0  1000.0   \n",
       "25  5873893871 2016-11-13  santamaria  Santa Maria  1818.0       2.0  1084.0   \n",
       "50  5849643168 2016-11-13     redding   Wilson Ave  1050.0       2.0  1100.0   \n",
       "\n",
       "    rent_sqft   longitude   latitude           county       fips_block state  \\\n",
       "1    1.058352 -120.508000  37.330200           Merced  060470010021060    CA   \n",
       "15   1.130769 -121.825955  39.719617            Butte  060070012001017    CA   \n",
       "20   1.675000 -120.661533  35.485117  San Luis Obispo  060790125023017    CA   \n",
       "25   1.677122 -120.426800  34.828600    Santa Barbara  060830020061208    CA   \n",
       "50   0.954545 -122.325522  40.566627           Shasta  060890113004008    CA   \n",
       "\n",
       "    bathrooms  \n",
       "1         NaN  \n",
       "15        NaN  \n",
       "20        NaN  \n",
       "25        NaN  \n",
       "50        NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CA.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'Series' object has no attribute 'year'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-92972f636dc5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mCA\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCA\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'date'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0myear\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   4374\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4375\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4376\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4377\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4378\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'Series' object has no attribute 'year'"
     ]
    }
   ],
   "source": [
    "CA['year'] = CA['date'].year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/paul/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n",
      "/home/paul/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "CA['year'] = pd.DatetimeIndex(CA['date']).year\n",
    "CA['month'] = pd.DatetimeIndex(CA['date']).month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pid</th>\n",
       "      <th>date</th>\n",
       "      <th>region</th>\n",
       "      <th>neighborhood</th>\n",
       "      <th>rent</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5873877617</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>merced</td>\n",
       "      <td>Merced</td>\n",
       "      <td>925.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>874.0</td>\n",
       "      <td>1.058352</td>\n",
       "      <td>-120.508000</td>\n",
       "      <td>37.330200</td>\n",
       "      <td>Merced</td>\n",
       "      <td>060470010021060</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>5873876292</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>chico</td>\n",
       "      <td>Chico</td>\n",
       "      <td>735.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>650.0</td>\n",
       "      <td>1.130769</td>\n",
       "      <td>-121.825955</td>\n",
       "      <td>39.719617</td>\n",
       "      <td>Butte</td>\n",
       "      <td>060070012001017</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5873889346</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>slo</td>\n",
       "      <td>Atascadero</td>\n",
       "      <td>1675.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1.675000</td>\n",
       "      <td>-120.661533</td>\n",
       "      <td>35.485117</td>\n",
       "      <td>San Luis Obispo</td>\n",
       "      <td>060790125023017</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5873893871</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>santamaria</td>\n",
       "      <td>Santa Maria</td>\n",
       "      <td>1818.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1084.0</td>\n",
       "      <td>1.677122</td>\n",
       "      <td>-120.426800</td>\n",
       "      <td>34.828600</td>\n",
       "      <td>Santa Barbara</td>\n",
       "      <td>060830020061208</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>5849643168</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>redding</td>\n",
       "      <td>Wilson Ave</td>\n",
       "      <td>1050.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>0.954545</td>\n",
       "      <td>-122.325522</td>\n",
       "      <td>40.566627</td>\n",
       "      <td>Shasta</td>\n",
       "      <td>060890113004008</td>\n",
       "      <td>CA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           pid       date      region neighborhood    rent  bedrooms    sqft  \\\n",
       "1   5873877617 2016-11-13      merced       Merced   925.0       2.0   874.0   \n",
       "15  5873876292 2016-11-13       chico        Chico   735.0       0.0   650.0   \n",
       "20  5873889346 2016-11-13         slo   Atascadero  1675.0       3.0  1000.0   \n",
       "25  5873893871 2016-11-13  santamaria  Santa Maria  1818.0       2.0  1084.0   \n",
       "50  5849643168 2016-11-13     redding   Wilson Ave  1050.0       2.0  1100.0   \n",
       "\n",
       "    rent_sqft   longitude   latitude           county       fips_block state  \\\n",
       "1    1.058352 -120.508000  37.330200           Merced  060470010021060    CA   \n",
       "15   1.130769 -121.825955  39.719617            Butte  060070012001017    CA   \n",
       "20   1.675000 -120.661533  35.485117  San Luis Obispo  060790125023017    CA   \n",
       "25   1.677122 -120.426800  34.828600    Santa Barbara  060830020061208    CA   \n",
       "50   0.954545 -122.325522  40.566627           Shasta  060890113004008    CA   \n",
       "\n",
       "    bathrooms  year  month  \n",
       "1         NaN  2016     11  \n",
       "15        NaN  2016     11  \n",
       "20        NaN  2016     11  \n",
       "25        NaN  2016     11  \n",
       "50        NaN  2016     11  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CA.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#grouped = df.groupby('Team')\n",
    "#print grouped['Points'].agg([np.sum, np.mean, np.std])\n",
    "CA3 = CA[CA['bedrooms']<4]\n",
    "grouped = CA3.groupby(['bedrooms','year','month'])\n",
    "grouped['rent'].agg([np.median,np.size]).unstack(level=0).to_csv('data/CA.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped = CA3.groupby(['county','bedrooms','year','month'])\n",
    "grouped['rent'].agg([np.median,np.size]).unstack(level=1).to_csv('data/Counties.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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