Advance Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Merging Dataframes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame([{'Name': 'Chris', 'Item Purchased': 'Sponge', 'Cost': 22.50},\n",
    "                   {'Name': 'Kevyn', 'Item Purchased': 'Kitty Litter', 'Cost': 2.50},\n",
    "                   {'Name': 'Filip', 'Item Purchased': 'Spoon', 'Cost': 5.00}],\n",
    "                  index=['Store 1', 'Store 1', 'Store 2'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Date'] = ['December 1', 'January 1', 'mid-May']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Delivered'] = True\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Feedback'] = ['Positive', None, 'Negative']\n",
    "df['Date'] = pd.Series({'Store 3': 'December 1', 'Store 2': 'mid-May'})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "adf = df.reset_index()\n",
    "adf['Date'] = pd.Series({0: 'December 1', 2: 'mid-May'})\n",
    "adf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "staff_df = pd.DataFrame([{'Name': 'Kelly_staff', 'Role': 'Director of HR'},\n",
    "                         {'Name': 'Sally', 'Role': 'Course liasion'},\n",
    "                         {'Name': 'James', 'Role': 'Grader'}])\n",
    "staff_df = staff_df.set_index('Name')\n",
    "staff_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "student_df = pd.DataFrame([{'Name': 'James', 'School': 'Business'},\n",
    "                           {'Name': 'Mike_student', 'School': 'Law'},\n",
    "                           {'Name': 'Sally', 'School': 'Engineering'}])\n",
    "student_df = student_df.set_index('Name')\n",
    "student_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "print(staff_df.head())\n",
    "print()\n",
    "print(student_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.merge(staff_df, student_df, how='outer', left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.merge(staff_df, student_df, how='inner', left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.merge(staff_df, student_df, how='left', left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.merge(staff_df, student_df, how='right', left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "staff_df = staff_df.reset_index()\n",
    "student_df = student_df.reset_index()\n",
    "\n",
    "print(staff_df.head())\n",
    "print()\n",
    "print(student_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "pd.merge(staff_df, student_df, how='left', left_on='Name', right_on='Name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "staff_df = pd.DataFrame([{'Name': 'Kelly_staff', 'Role': 'Director of HR', 'Location': 'State Street'},\n",
    "                         {'Name': 'Sally', 'Role': 'Course liasion', 'Location': 'Washington Avenue'},\n",
    "                         {'Name': 'James', 'Role': 'Grader', 'Location': 'Washington Avenue'}])\n",
    "student_df = pd.DataFrame([{'Name': 'James', 'School': 'Business', 'Location': '1024 Billiard Avenue'},\n",
    "                           {'Name': 'Mike_student', 'School': 'Law', 'Location': 'Fraternity House #22'},\n",
    "                           {'Name': 'Sally', 'School': 'Engineering', 'Location': '512 Wilson Crescent'}])\n",
    "print(staff_df)\n",
    "print(student_df)\n",
    "pd.merge(staff_df, student_df, how='left', left_on='Name', right_on='Name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "staff_df = pd.DataFrame([{'First Name': 'Kelly_staff', 'Last Name': 'Desjardins', 'Role': 'Director of HR'},\n",
    "                         {'First Name': 'Sally', 'Last Name': 'Brooks', 'Role': 'Course liasion'},\n",
    "                         {'First Name': 'James', 'Last Name': 'Wilde', 'Role': 'Grader'}])\n",
    "student_df = pd.DataFrame([{'First Name': 'James', 'Last Name': 'Hammond', 'School': 'Business'},\n",
    "                           {'First Name': 'Mike_student', 'Last Name': 'Smith', 'School': 'Law'},\n",
    "                           {'First Name': 'Sally', 'Last Name': 'Brooks', 'School': 'Engineering'}])\n",
    "print(staff_df)\n",
    "print(student_df)\n",
    "pd.merge(staff_df, student_df, how='inner', left_on=['First Name','Last Name'], right_on=['First Name','Last Name'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Idiomatic Pandas: Making Code Pandorable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('data/census.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(df.where(df['SUMLEV']==50)\n",
    "    .dropna()\n",
    "    .set_index(['STNAME','CTYNAME'])\n",
    "    .rename(columns={'ESTIMATESBASE2010': 'Estimates Base 2010'}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['SUMLEV']==50]\n",
    "df.set_index(['STNAME','CTYNAME'], inplace=True)\n",
    "df.rename(columns={'ESTIMATESBASE2010': 'Estimates Base 2010'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "def min_max(row):\n",
    "    data = row[['POPESTIMATE2010',\n",
    "                'POPESTIMATE2011',\n",
    "                'POPESTIMATE2012',\n",
    "                'POPESTIMATE2013',\n",
    "                'POPESTIMATE2014',\n",
    "                'POPESTIMATE2015']]\n",
    "    return pd.Series({'min': np.min(data), 'max': np.max(data)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.apply(min_max, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "def min_max(row):\n",
    "    data = row[['POPESTIMATE2010',\n",
    "                'POPESTIMATE2011',\n",
    "                'POPESTIMATE2012',\n",
    "                'POPESTIMATE2013',\n",
    "                'POPESTIMATE2014',\n",
    "                'POPESTIMATE2015']]\n",
    "    row['max'] = np.max(data)\n",
    "    row['min'] = np.min(data)\n",
    "    return row\n",
    "df.apply(min_max, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rows = ['POPESTIMATE2010',\n",
    "        'POPESTIMATE2011',\n",
    "        'POPESTIMATE2012',\n",
    "        'POPESTIMATE2013',\n",
    "        'POPESTIMATE2014',\n",
    "        'POPESTIMATE2015']\n",
    "df.apply(lambda x: np.max(x[rows]), axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Group by"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SUMLEV</th>\n",
       "      <th>REGION</th>\n",
       "      <th>DIVISION</th>\n",
       "      <th>STATE</th>\n",
       "      <th>COUNTY</th>\n",
       "      <th>STNAME</th>\n",
       "      <th>CTYNAME</th>\n",
       "      <th>CENSUS2010POP</th>\n",
       "      <th>ESTIMATESBASE2010</th>\n",
       "      <th>POPESTIMATE2010</th>\n",
       "      <th>...</th>\n",
       "      <th>RDOMESTICMIG2011</th>\n",
       "      <th>RDOMESTICMIG2012</th>\n",
       "      <th>RDOMESTICMIG2013</th>\n",
       "      <th>RDOMESTICMIG2014</th>\n",
       "      <th>RDOMESTICMIG2015</th>\n",
       "      <th>RNETMIG2011</th>\n",
       "      <th>RNETMIG2012</th>\n",
       "      <th>RNETMIG2013</th>\n",
       "      <th>RNETMIG2014</th>\n",
       "      <th>RNETMIG2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>54571</td>\n",
       "      <td>54571</td>\n",
       "      <td>54660</td>\n",
       "      <td>...</td>\n",
       "      <td>7.242091</td>\n",
       "      <td>-2.915927</td>\n",
       "      <td>-3.012349</td>\n",
       "      <td>2.265971</td>\n",
       "      <td>-2.530799</td>\n",
       "      <td>7.606016</td>\n",
       "      <td>-2.626146</td>\n",
       "      <td>-2.722002</td>\n",
       "      <td>2.592270</td>\n",
       "      <td>-2.187333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Baldwin County</td>\n",
       "      <td>182265</td>\n",
       "      <td>182265</td>\n",
       "      <td>183193</td>\n",
       "      <td>...</td>\n",
       "      <td>14.832960</td>\n",
       "      <td>17.647293</td>\n",
       "      <td>21.845705</td>\n",
       "      <td>19.243287</td>\n",
       "      <td>17.197872</td>\n",
       "      <td>15.844176</td>\n",
       "      <td>18.559627</td>\n",
       "      <td>22.727626</td>\n",
       "      <td>20.317142</td>\n",
       "      <td>18.293499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Barbour County</td>\n",
       "      <td>27457</td>\n",
       "      <td>27457</td>\n",
       "      <td>27341</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.728132</td>\n",
       "      <td>-2.500690</td>\n",
       "      <td>-7.056824</td>\n",
       "      <td>-3.904217</td>\n",
       "      <td>-10.543299</td>\n",
       "      <td>-4.874741</td>\n",
       "      <td>-2.758113</td>\n",
       "      <td>-7.167664</td>\n",
       "      <td>-3.978583</td>\n",
       "      <td>-10.543299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Bibb County</td>\n",
       "      <td>22915</td>\n",
       "      <td>22919</td>\n",
       "      <td>22861</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.527043</td>\n",
       "      <td>-5.068871</td>\n",
       "      <td>-6.201001</td>\n",
       "      <td>-0.177537</td>\n",
       "      <td>0.177258</td>\n",
       "      <td>-5.088389</td>\n",
       "      <td>-4.363636</td>\n",
       "      <td>-5.403729</td>\n",
       "      <td>0.754533</td>\n",
       "      <td>1.107861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Blount County</td>\n",
       "      <td>57322</td>\n",
       "      <td>57322</td>\n",
       "      <td>57373</td>\n",
       "      <td>...</td>\n",
       "      <td>1.807375</td>\n",
       "      <td>-1.177622</td>\n",
       "      <td>-1.748766</td>\n",
       "      <td>-2.062535</td>\n",
       "      <td>-1.369970</td>\n",
       "      <td>1.859511</td>\n",
       "      <td>-0.848580</td>\n",
       "      <td>-1.402476</td>\n",
       "      <td>-1.577232</td>\n",
       "      <td>-0.884411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Bullock County</td>\n",
       "      <td>10914</td>\n",
       "      <td>10915</td>\n",
       "      <td>10887</td>\n",
       "      <td>...</td>\n",
       "      <td>-30.953709</td>\n",
       "      <td>-5.180127</td>\n",
       "      <td>-1.130263</td>\n",
       "      <td>14.354290</td>\n",
       "      <td>-16.167247</td>\n",
       "      <td>-29.001673</td>\n",
       "      <td>-2.825524</td>\n",
       "      <td>1.507017</td>\n",
       "      <td>17.243790</td>\n",
       "      <td>-13.193961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Butler County</td>\n",
       "      <td>20947</td>\n",
       "      <td>20946</td>\n",
       "      <td>20944</td>\n",
       "      <td>...</td>\n",
       "      <td>-14.032727</td>\n",
       "      <td>-11.684234</td>\n",
       "      <td>-5.655413</td>\n",
       "      <td>1.085428</td>\n",
       "      <td>-6.529805</td>\n",
       "      <td>-13.936612</td>\n",
       "      <td>-11.586865</td>\n",
       "      <td>-5.557058</td>\n",
       "      <td>1.184103</td>\n",
       "      <td>-6.430868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Calhoun County</td>\n",
       "      <td>118572</td>\n",
       "      <td>118586</td>\n",
       "      <td>118437</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.155670</td>\n",
       "      <td>-4.611706</td>\n",
       "      <td>-5.524649</td>\n",
       "      <td>-4.463211</td>\n",
       "      <td>-3.376322</td>\n",
       "      <td>-5.791579</td>\n",
       "      <td>-4.092677</td>\n",
       "      <td>-5.062836</td>\n",
       "      <td>-3.912834</td>\n",
       "      <td>-2.806406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Chambers County</td>\n",
       "      <td>34215</td>\n",
       "      <td>34170</td>\n",
       "      <td>34098</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.731639</td>\n",
       "      <td>3.849092</td>\n",
       "      <td>2.872721</td>\n",
       "      <td>-2.287222</td>\n",
       "      <td>1.349468</td>\n",
       "      <td>-1.821092</td>\n",
       "      <td>4.701181</td>\n",
       "      <td>3.781439</td>\n",
       "      <td>-1.290228</td>\n",
       "      <td>2.346901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Cherokee County</td>\n",
       "      <td>25989</td>\n",
       "      <td>25986</td>\n",
       "      <td>25976</td>\n",
       "      <td>...</td>\n",
       "      <td>6.339327</td>\n",
       "      <td>1.113180</td>\n",
       "      <td>5.488706</td>\n",
       "      <td>-0.076806</td>\n",
       "      <td>-3.239866</td>\n",
       "      <td>6.416167</td>\n",
       "      <td>1.420264</td>\n",
       "      <td>5.757384</td>\n",
       "      <td>0.230419</td>\n",
       "      <td>-2.931307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Chilton County</td>\n",
       "      <td>43643</td>\n",
       "      <td>43631</td>\n",
       "      <td>43665</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.372935</td>\n",
       "      <td>-2.653369</td>\n",
       "      <td>0.480044</td>\n",
       "      <td>0.456017</td>\n",
       "      <td>-2.253483</td>\n",
       "      <td>-0.823761</td>\n",
       "      <td>-2.447504</td>\n",
       "      <td>0.868651</td>\n",
       "      <td>0.957636</td>\n",
       "      <td>-1.752709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Choctaw County</td>\n",
       "      <td>13859</td>\n",
       "      <td>13858</td>\n",
       "      <td>13841</td>\n",
       "      <td>...</td>\n",
       "      <td>-15.455274</td>\n",
       "      <td>-0.737028</td>\n",
       "      <td>-8.766391</td>\n",
       "      <td>-1.274984</td>\n",
       "      <td>-5.291205</td>\n",
       "      <td>-15.528177</td>\n",
       "      <td>-0.737028</td>\n",
       "      <td>-8.766391</td>\n",
       "      <td>-1.274984</td>\n",
       "      <td>-5.291205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Clarke County</td>\n",
       "      <td>25833</td>\n",
       "      <td>25840</td>\n",
       "      <td>25767</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.194363</td>\n",
       "      <td>-17.667705</td>\n",
       "      <td>-0.318345</td>\n",
       "      <td>-8.686428</td>\n",
       "      <td>-5.613667</td>\n",
       "      <td>-6.077488</td>\n",
       "      <td>-17.509958</td>\n",
       "      <td>-0.159172</td>\n",
       "      <td>-8.486280</td>\n",
       "      <td>-5.411736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Clay County</td>\n",
       "      <td>13932</td>\n",
       "      <td>13932</td>\n",
       "      <td>13880</td>\n",
       "      <td>...</td>\n",
       "      <td>-10.744102</td>\n",
       "      <td>-13.345130</td>\n",
       "      <td>4.902871</td>\n",
       "      <td>5.702648</td>\n",
       "      <td>3.912450</td>\n",
       "      <td>-10.816697</td>\n",
       "      <td>-13.345130</td>\n",
       "      <td>4.977157</td>\n",
       "      <td>5.776708</td>\n",
       "      <td>3.986270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Cleburne County</td>\n",
       "      <td>14972</td>\n",
       "      <td>14972</td>\n",
       "      <td>14973</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.673524</td>\n",
       "      <td>-5.151880</td>\n",
       "      <td>7.345821</td>\n",
       "      <td>3.654485</td>\n",
       "      <td>-3.123961</td>\n",
       "      <td>-3.673524</td>\n",
       "      <td>-5.151880</td>\n",
       "      <td>7.345821</td>\n",
       "      <td>3.654485</td>\n",
       "      <td>-3.123961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Coffee County</td>\n",
       "      <td>49948</td>\n",
       "      <td>49948</td>\n",
       "      <td>50177</td>\n",
       "      <td>...</td>\n",
       "      <td>0.377640</td>\n",
       "      <td>7.675579</td>\n",
       "      <td>-13.146535</td>\n",
       "      <td>-3.602859</td>\n",
       "      <td>2.214774</td>\n",
       "      <td>2.166460</td>\n",
       "      <td>11.513368</td>\n",
       "      <td>-10.438741</td>\n",
       "      <td>-0.767822</td>\n",
       "      <td>5.350738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Colbert County</td>\n",
       "      <td>54428</td>\n",
       "      <td>54428</td>\n",
       "      <td>54514</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.073423</td>\n",
       "      <td>1.065051</td>\n",
       "      <td>1.762390</td>\n",
       "      <td>1.835688</td>\n",
       "      <td>-0.110260</td>\n",
       "      <td>0.513964</td>\n",
       "      <td>1.469035</td>\n",
       "      <td>2.276420</td>\n",
       "      <td>2.533249</td>\n",
       "      <td>0.588052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Conecuh County</td>\n",
       "      <td>13228</td>\n",
       "      <td>13228</td>\n",
       "      <td>13208</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.861559</td>\n",
       "      <td>-7.504690</td>\n",
       "      <td>-6.107224</td>\n",
       "      <td>-14.645416</td>\n",
       "      <td>2.684140</td>\n",
       "      <td>-4.861559</td>\n",
       "      <td>-7.504690</td>\n",
       "      <td>-6.107224</td>\n",
       "      <td>-14.645416</td>\n",
       "      <td>2.684140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Coosa County</td>\n",
       "      <td>11539</td>\n",
       "      <td>11758</td>\n",
       "      <td>11758</td>\n",
       "      <td>...</td>\n",
       "      <td>-33.930581</td>\n",
       "      <td>-10.291443</td>\n",
       "      <td>-4.313831</td>\n",
       "      <td>-22.958017</td>\n",
       "      <td>-5.387581</td>\n",
       "      <td>-34.017138</td>\n",
       "      <td>-10.380162</td>\n",
       "      <td>-4.403703</td>\n",
       "      <td>-23.049483</td>\n",
       "      <td>-5.387581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Covington County</td>\n",
       "      <td>37765</td>\n",
       "      <td>37765</td>\n",
       "      <td>37796</td>\n",
       "      <td>...</td>\n",
       "      <td>6.696899</td>\n",
       "      <td>-4.612668</td>\n",
       "      <td>0.740271</td>\n",
       "      <td>3.697932</td>\n",
       "      <td>-0.316945</td>\n",
       "      <td>6.881460</td>\n",
       "      <td>-4.559952</td>\n",
       "      <td>0.793147</td>\n",
       "      <td>3.750759</td>\n",
       "      <td>-0.264121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>41</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Crenshaw County</td>\n",
       "      <td>13906</td>\n",
       "      <td>13906</td>\n",
       "      <td>13853</td>\n",
       "      <td>...</td>\n",
       "      <td>1.729792</td>\n",
       "      <td>3.950156</td>\n",
       "      <td>-1.864936</td>\n",
       "      <td>3.084648</td>\n",
       "      <td>3.439504</td>\n",
       "      <td>2.666763</td>\n",
       "      <td>5.099293</td>\n",
       "      <td>-0.502098</td>\n",
       "      <td>4.734577</td>\n",
       "      <td>5.087600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Cullman County</td>\n",
       "      <td>80406</td>\n",
       "      <td>80410</td>\n",
       "      <td>80473</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.404233</td>\n",
       "      <td>-1.019628</td>\n",
       "      <td>4.071247</td>\n",
       "      <td>5.087142</td>\n",
       "      <td>7.915406</td>\n",
       "      <td>-1.031427</td>\n",
       "      <td>-0.634159</td>\n",
       "      <td>4.542916</td>\n",
       "      <td>5.593387</td>\n",
       "      <td>8.417777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Dale County</td>\n",
       "      <td>50251</td>\n",
       "      <td>50251</td>\n",
       "      <td>50358</td>\n",
       "      <td>...</td>\n",
       "      <td>-10.749798</td>\n",
       "      <td>-5.277150</td>\n",
       "      <td>-15.236079</td>\n",
       "      <td>-11.979785</td>\n",
       "      <td>-5.107706</td>\n",
       "      <td>-9.575283</td>\n",
       "      <td>-0.776637</td>\n",
       "      <td>-12.640155</td>\n",
       "      <td>-9.503292</td>\n",
       "      <td>-1.998668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>47</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Dallas County</td>\n",
       "      <td>43820</td>\n",
       "      <td>43820</td>\n",
       "      <td>43803</td>\n",
       "      <td>...</td>\n",
       "      <td>-15.635599</td>\n",
       "      <td>-11.308243</td>\n",
       "      <td>-16.745678</td>\n",
       "      <td>-9.344789</td>\n",
       "      <td>-14.687232</td>\n",
       "      <td>-15.727573</td>\n",
       "      <td>-11.378047</td>\n",
       "      <td>-16.792849</td>\n",
       "      <td>-9.368689</td>\n",
       "      <td>-14.711389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>49</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>DeKalb County</td>\n",
       "      <td>71109</td>\n",
       "      <td>71115</td>\n",
       "      <td>71142</td>\n",
       "      <td>...</td>\n",
       "      <td>0.294677</td>\n",
       "      <td>-9.302391</td>\n",
       "      <td>-1.748807</td>\n",
       "      <td>0.267830</td>\n",
       "      <td>0.028141</td>\n",
       "      <td>1.375159</td>\n",
       "      <td>-8.656001</td>\n",
       "      <td>-1.029539</td>\n",
       "      <td>1.198187</td>\n",
       "      <td>0.956790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>51</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Elmore County</td>\n",
       "      <td>79303</td>\n",
       "      <td>79296</td>\n",
       "      <td>79465</td>\n",
       "      <td>...</td>\n",
       "      <td>3.235576</td>\n",
       "      <td>0.822717</td>\n",
       "      <td>1.760531</td>\n",
       "      <td>-1.507057</td>\n",
       "      <td>2.067820</td>\n",
       "      <td>3.674511</td>\n",
       "      <td>1.558176</td>\n",
       "      <td>2.306047</td>\n",
       "      <td>-0.951175</td>\n",
       "      <td>2.757093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Escambia County</td>\n",
       "      <td>38319</td>\n",
       "      <td>38319</td>\n",
       "      <td>38309</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.449988</td>\n",
       "      <td>-3.855889</td>\n",
       "      <td>-4.822706</td>\n",
       "      <td>-1.189831</td>\n",
       "      <td>1.190902</td>\n",
       "      <td>-3.397716</td>\n",
       "      <td>-3.803428</td>\n",
       "      <td>-4.769999</td>\n",
       "      <td>-1.136950</td>\n",
       "      <td>1.243830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>55</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Etowah County</td>\n",
       "      <td>104430</td>\n",
       "      <td>104427</td>\n",
       "      <td>104442</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.015919</td>\n",
       "      <td>2.062637</td>\n",
       "      <td>-1.931884</td>\n",
       "      <td>-1.726932</td>\n",
       "      <td>-2.082234</td>\n",
       "      <td>-0.632554</td>\n",
       "      <td>2.446383</td>\n",
       "      <td>-1.518596</td>\n",
       "      <td>-1.234901</td>\n",
       "      <td>-1.588308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Fayette County</td>\n",
       "      <td>17241</td>\n",
       "      <td>17241</td>\n",
       "      <td>17231</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.015601</td>\n",
       "      <td>-0.646640</td>\n",
       "      <td>-3.725937</td>\n",
       "      <td>0.296745</td>\n",
       "      <td>-2.797536</td>\n",
       "      <td>-5.132243</td>\n",
       "      <td>-0.705426</td>\n",
       "      <td>-3.785079</td>\n",
       "      <td>0.237396</td>\n",
       "      <td>-2.857058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Franklin County</td>\n",
       "      <td>31704</td>\n",
       "      <td>31709</td>\n",
       "      <td>31734</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.638750</td>\n",
       "      <td>-5.459394</td>\n",
       "      <td>-8.043702</td>\n",
       "      <td>-1.267849</td>\n",
       "      <td>-2.401719</td>\n",
       "      <td>0.063029</td>\n",
       "      <td>-3.471291</td>\n",
       "      <td>-5.700261</td>\n",
       "      <td>1.553115</td>\n",
       "      <td>0.442422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3162</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>129</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Washburn County</td>\n",
       "      <td>15911</td>\n",
       "      <td>15911</td>\n",
       "      <td>15930</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.873936</td>\n",
       "      <td>7.338289</td>\n",
       "      <td>-6.732724</td>\n",
       "      <td>3.510452</td>\n",
       "      <td>-5.123279</td>\n",
       "      <td>-6.747809</td>\n",
       "      <td>7.464811</td>\n",
       "      <td>-6.605691</td>\n",
       "      <td>3.638104</td>\n",
       "      <td>-4.995197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3163</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>131</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Washington County</td>\n",
       "      <td>131887</td>\n",
       "      <td>131885</td>\n",
       "      <td>131967</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.794876</td>\n",
       "      <td>0.785279</td>\n",
       "      <td>-2.215465</td>\n",
       "      <td>1.601149</td>\n",
       "      <td>-0.434498</td>\n",
       "      <td>-0.431504</td>\n",
       "      <td>1.162817</td>\n",
       "      <td>-1.763330</td>\n",
       "      <td>2.104796</td>\n",
       "      <td>0.059931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3164</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>133</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Waukesha County</td>\n",
       "      <td>389891</td>\n",
       "      <td>389938</td>\n",
       "      <td>390076</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.765799</td>\n",
       "      <td>2.128860</td>\n",
       "      <td>0.038132</td>\n",
       "      <td>0.760109</td>\n",
       "      <td>-0.719858</td>\n",
       "      <td>0.102448</td>\n",
       "      <td>3.180527</td>\n",
       "      <td>1.189727</td>\n",
       "      <td>2.077633</td>\n",
       "      <td>0.593567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3165</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>135</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Waupaca County</td>\n",
       "      <td>52410</td>\n",
       "      <td>52410</td>\n",
       "      <td>52422</td>\n",
       "      <td>...</td>\n",
       "      <td>3.111756</td>\n",
       "      <td>-2.241873</td>\n",
       "      <td>6.292687</td>\n",
       "      <td>-0.441031</td>\n",
       "      <td>-0.480617</td>\n",
       "      <td>3.359933</td>\n",
       "      <td>-2.011937</td>\n",
       "      <td>6.561277</td>\n",
       "      <td>-0.134227</td>\n",
       "      <td>-0.173022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3166</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>137</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Waushara County</td>\n",
       "      <td>24496</td>\n",
       "      <td>24496</td>\n",
       "      <td>24506</td>\n",
       "      <td>...</td>\n",
       "      <td>4.930022</td>\n",
       "      <td>-2.404973</td>\n",
       "      <td>-4.097017</td>\n",
       "      <td>-4.906711</td>\n",
       "      <td>-4.397793</td>\n",
       "      <td>5.174486</td>\n",
       "      <td>-2.160399</td>\n",
       "      <td>-3.810226</td>\n",
       "      <td>-4.535615</td>\n",
       "      <td>-4.024395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3167</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>139</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Winnebago County</td>\n",
       "      <td>166994</td>\n",
       "      <td>166994</td>\n",
       "      <td>167059</td>\n",
       "      <td>...</td>\n",
       "      <td>0.316712</td>\n",
       "      <td>2.889873</td>\n",
       "      <td>0.833819</td>\n",
       "      <td>-2.406192</td>\n",
       "      <td>-4.557985</td>\n",
       "      <td>0.842573</td>\n",
       "      <td>3.502335</td>\n",
       "      <td>1.531624</td>\n",
       "      <td>-1.545153</td>\n",
       "      <td>-3.685304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3168</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>141</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Wood County</td>\n",
       "      <td>74749</td>\n",
       "      <td>74749</td>\n",
       "      <td>74807</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.081523</td>\n",
       "      <td>-5.019090</td>\n",
       "      <td>-6.901200</td>\n",
       "      <td>-5.596471</td>\n",
       "      <td>-3.958322</td>\n",
       "      <td>-3.733590</td>\n",
       "      <td>-4.562809</td>\n",
       "      <td>-6.442917</td>\n",
       "      <td>-5.040889</td>\n",
       "      <td>-3.414223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3170</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Albany County</td>\n",
       "      <td>36299</td>\n",
       "      <td>36299</td>\n",
       "      <td>36428</td>\n",
       "      <td>...</td>\n",
       "      <td>3.708956</td>\n",
       "      <td>2.637812</td>\n",
       "      <td>-3.544634</td>\n",
       "      <td>-3.334877</td>\n",
       "      <td>-9.911169</td>\n",
       "      <td>6.736119</td>\n",
       "      <td>6.433032</td>\n",
       "      <td>0.719587</td>\n",
       "      <td>1.429233</td>\n",
       "      <td>-5.166460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3171</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>3</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Big Horn County</td>\n",
       "      <td>11668</td>\n",
       "      <td>11668</td>\n",
       "      <td>11672</td>\n",
       "      <td>...</td>\n",
       "      <td>4.868258</td>\n",
       "      <td>2.804930</td>\n",
       "      <td>16.815908</td>\n",
       "      <td>-8.026420</td>\n",
       "      <td>5.095861</td>\n",
       "      <td>4.868258</td>\n",
       "      <td>3.144921</td>\n",
       "      <td>17.236306</td>\n",
       "      <td>-7.608378</td>\n",
       "      <td>5.513554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3172</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Campbell County</td>\n",
       "      <td>46133</td>\n",
       "      <td>46133</td>\n",
       "      <td>46244</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.843479</td>\n",
       "      <td>15.601020</td>\n",
       "      <td>-5.895711</td>\n",
       "      <td>-8.550911</td>\n",
       "      <td>10.916963</td>\n",
       "      <td>-2.649606</td>\n",
       "      <td>15.558684</td>\n",
       "      <td>-5.916543</td>\n",
       "      <td>-8.509402</td>\n",
       "      <td>10.978525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3173</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>7</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Carbon County</td>\n",
       "      <td>15885</td>\n",
       "      <td>15885</td>\n",
       "      <td>15837</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.581980</td>\n",
       "      <td>-13.081441</td>\n",
       "      <td>3.178134</td>\n",
       "      <td>-2.970641</td>\n",
       "      <td>-23.300971</td>\n",
       "      <td>-7.392431</td>\n",
       "      <td>-12.636926</td>\n",
       "      <td>3.623073</td>\n",
       "      <td>-2.338590</td>\n",
       "      <td>-22.600668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3174</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>9</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Converse County</td>\n",
       "      <td>13833</td>\n",
       "      <td>13833</td>\n",
       "      <td>13826</td>\n",
       "      <td>...</td>\n",
       "      <td>-12.847499</td>\n",
       "      <td>15.493820</td>\n",
       "      <td>19.035533</td>\n",
       "      <td>-20.550587</td>\n",
       "      <td>-0.070403</td>\n",
       "      <td>-12.774915</td>\n",
       "      <td>16.502720</td>\n",
       "      <td>20.093063</td>\n",
       "      <td>-19.358233</td>\n",
       "      <td>1.126443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3175</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>11</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Crook County</td>\n",
       "      <td>7083</td>\n",
       "      <td>7083</td>\n",
       "      <td>7114</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.544618</td>\n",
       "      <td>-4.202564</td>\n",
       "      <td>1.397819</td>\n",
       "      <td>6.378258</td>\n",
       "      <td>18.629317</td>\n",
       "      <td>-0.982939</td>\n",
       "      <td>-3.642222</td>\n",
       "      <td>2.096729</td>\n",
       "      <td>7.071547</td>\n",
       "      <td>19.309219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3176</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>13</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Fremont County</td>\n",
       "      <td>40123</td>\n",
       "      <td>40123</td>\n",
       "      <td>40222</td>\n",
       "      <td>...</td>\n",
       "      <td>2.747083</td>\n",
       "      <td>7.782673</td>\n",
       "      <td>-4.990688</td>\n",
       "      <td>-12.331633</td>\n",
       "      <td>-13.673610</td>\n",
       "      <td>3.093562</td>\n",
       "      <td>8.027411</td>\n",
       "      <td>-4.747240</td>\n",
       "      <td>-12.013555</td>\n",
       "      <td>-13.352750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3177</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>15</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Goshen County</td>\n",
       "      <td>13249</td>\n",
       "      <td>13247</td>\n",
       "      <td>13408</td>\n",
       "      <td>...</td>\n",
       "      <td>14.293649</td>\n",
       "      <td>3.961413</td>\n",
       "      <td>-8.079028</td>\n",
       "      <td>-7.017803</td>\n",
       "      <td>-11.899450</td>\n",
       "      <td>14.886132</td>\n",
       "      <td>4.841727</td>\n",
       "      <td>-6.903896</td>\n",
       "      <td>-5.761986</td>\n",
       "      <td>-10.635133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3178</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>17</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Hot Springs County</td>\n",
       "      <td>4812</td>\n",
       "      <td>4812</td>\n",
       "      <td>4813</td>\n",
       "      <td>...</td>\n",
       "      <td>3.322604</td>\n",
       "      <td>6.208609</td>\n",
       "      <td>3.095336</td>\n",
       "      <td>-6.017222</td>\n",
       "      <td>-5.454164</td>\n",
       "      <td>5.191569</td>\n",
       "      <td>6.001656</td>\n",
       "      <td>2.888981</td>\n",
       "      <td>-6.224712</td>\n",
       "      <td>-5.663940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3179</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>19</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Johnson County</td>\n",
       "      <td>8569</td>\n",
       "      <td>8569</td>\n",
       "      <td>8581</td>\n",
       "      <td>...</td>\n",
       "      <td>4.995063</td>\n",
       "      <td>-4.058912</td>\n",
       "      <td>-0.812583</td>\n",
       "      <td>-10.715742</td>\n",
       "      <td>0.933652</td>\n",
       "      <td>5.227392</td>\n",
       "      <td>-4.058912</td>\n",
       "      <td>-0.812583</td>\n",
       "      <td>-10.715742</td>\n",
       "      <td>0.933652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3180</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>21</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Laramie County</td>\n",
       "      <td>91738</td>\n",
       "      <td>91881</td>\n",
       "      <td>92271</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.200428</td>\n",
       "      <td>15.547274</td>\n",
       "      <td>4.787847</td>\n",
       "      <td>-1.226133</td>\n",
       "      <td>0.278940</td>\n",
       "      <td>-0.973320</td>\n",
       "      <td>17.914554</td>\n",
       "      <td>6.003143</td>\n",
       "      <td>-0.207819</td>\n",
       "      <td>1.673640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3181</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>23</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Lincoln County</td>\n",
       "      <td>18106</td>\n",
       "      <td>18106</td>\n",
       "      <td>18091</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.802564</td>\n",
       "      <td>-11.566801</td>\n",
       "      <td>13.564556</td>\n",
       "      <td>6.125989</td>\n",
       "      <td>1.555544</td>\n",
       "      <td>-9.691801</td>\n",
       "      <td>-11.566801</td>\n",
       "      <td>13.619696</td>\n",
       "      <td>6.234414</td>\n",
       "      <td>1.662823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3182</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>25</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Natrona County</td>\n",
       "      <td>75450</td>\n",
       "      <td>75450</td>\n",
       "      <td>75472</td>\n",
       "      <td>...</td>\n",
       "      <td>7.189319</td>\n",
       "      <td>23.066162</td>\n",
       "      <td>24.322042</td>\n",
       "      <td>-0.958472</td>\n",
       "      <td>-0.061057</td>\n",
       "      <td>7.689674</td>\n",
       "      <td>23.749508</td>\n",
       "      <td>25.085233</td>\n",
       "      <td>-0.110593</td>\n",
       "      <td>0.793743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3183</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>27</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Niobrara County</td>\n",
       "      <td>2484</td>\n",
       "      <td>2484</td>\n",
       "      <td>2492</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.401849</td>\n",
       "      <td>0.806452</td>\n",
       "      <td>29.066295</td>\n",
       "      <td>-12.603387</td>\n",
       "      <td>7.492114</td>\n",
       "      <td>-0.401849</td>\n",
       "      <td>0.806452</td>\n",
       "      <td>29.066295</td>\n",
       "      <td>-12.603387</td>\n",
       "      <td>7.492114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3184</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>29</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Park County</td>\n",
       "      <td>28205</td>\n",
       "      <td>28205</td>\n",
       "      <td>28259</td>\n",
       "      <td>...</td>\n",
       "      <td>4.582951</td>\n",
       "      <td>8.057765</td>\n",
       "      <td>7.641997</td>\n",
       "      <td>-9.252437</td>\n",
       "      <td>-2.878980</td>\n",
       "      <td>6.486639</td>\n",
       "      <td>11.127389</td>\n",
       "      <td>10.877797</td>\n",
       "      <td>-5.585731</td>\n",
       "      <td>0.856839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3185</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>31</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Platte County</td>\n",
       "      <td>8667</td>\n",
       "      <td>8667</td>\n",
       "      <td>8678</td>\n",
       "      <td>...</td>\n",
       "      <td>4.373094</td>\n",
       "      <td>5.392073</td>\n",
       "      <td>2.634593</td>\n",
       "      <td>6.055759</td>\n",
       "      <td>4.662270</td>\n",
       "      <td>4.373094</td>\n",
       "      <td>4.933173</td>\n",
       "      <td>2.176403</td>\n",
       "      <td>5.598720</td>\n",
       "      <td>4.207414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3186</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>33</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Sheridan County</td>\n",
       "      <td>29116</td>\n",
       "      <td>29116</td>\n",
       "      <td>29146</td>\n",
       "      <td>...</td>\n",
       "      <td>0.958559</td>\n",
       "      <td>8.425487</td>\n",
       "      <td>4.546373</td>\n",
       "      <td>3.678069</td>\n",
       "      <td>-3.298406</td>\n",
       "      <td>2.122524</td>\n",
       "      <td>9.342778</td>\n",
       "      <td>5.523001</td>\n",
       "      <td>4.781489</td>\n",
       "      <td>-2.198937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3187</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>35</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Sublette County</td>\n",
       "      <td>10247</td>\n",
       "      <td>10247</td>\n",
       "      <td>10244</td>\n",
       "      <td>...</td>\n",
       "      <td>-23.741784</td>\n",
       "      <td>15.272374</td>\n",
       "      <td>-40.870074</td>\n",
       "      <td>-16.596273</td>\n",
       "      <td>-22.870900</td>\n",
       "      <td>-21.092907</td>\n",
       "      <td>16.828794</td>\n",
       "      <td>-39.211861</td>\n",
       "      <td>-14.409938</td>\n",
       "      <td>-20.664059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3188</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>37</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Sweetwater County</td>\n",
       "      <td>43806</td>\n",
       "      <td>43806</td>\n",
       "      <td>43593</td>\n",
       "      <td>...</td>\n",
       "      <td>1.072643</td>\n",
       "      <td>16.243199</td>\n",
       "      <td>-5.339774</td>\n",
       "      <td>-14.252889</td>\n",
       "      <td>-14.248864</td>\n",
       "      <td>1.255221</td>\n",
       "      <td>16.243199</td>\n",
       "      <td>-5.295460</td>\n",
       "      <td>-14.075283</td>\n",
       "      <td>-14.070195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3189</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>39</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Teton County</td>\n",
       "      <td>21294</td>\n",
       "      <td>21294</td>\n",
       "      <td>21297</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.589565</td>\n",
       "      <td>0.972695</td>\n",
       "      <td>19.525929</td>\n",
       "      <td>14.143021</td>\n",
       "      <td>-0.564849</td>\n",
       "      <td>0.654527</td>\n",
       "      <td>2.408578</td>\n",
       "      <td>21.160658</td>\n",
       "      <td>16.308671</td>\n",
       "      <td>1.520747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3190</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>41</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Uinta County</td>\n",
       "      <td>21118</td>\n",
       "      <td>21118</td>\n",
       "      <td>21102</td>\n",
       "      <td>...</td>\n",
       "      <td>-17.755986</td>\n",
       "      <td>-4.916350</td>\n",
       "      <td>-6.902954</td>\n",
       "      <td>-14.215862</td>\n",
       "      <td>-12.127022</td>\n",
       "      <td>-18.136812</td>\n",
       "      <td>-5.536861</td>\n",
       "      <td>-7.521840</td>\n",
       "      <td>-14.740608</td>\n",
       "      <td>-12.606351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3191</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>43</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Washakie County</td>\n",
       "      <td>8533</td>\n",
       "      <td>8533</td>\n",
       "      <td>8545</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.637475</td>\n",
       "      <td>-0.827815</td>\n",
       "      <td>-2.013502</td>\n",
       "      <td>-17.781491</td>\n",
       "      <td>1.682288</td>\n",
       "      <td>-11.990126</td>\n",
       "      <td>-1.182592</td>\n",
       "      <td>-2.250385</td>\n",
       "      <td>-18.020168</td>\n",
       "      <td>1.441961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3192</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>45</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Weston County</td>\n",
       "      <td>7208</td>\n",
       "      <td>7208</td>\n",
       "      <td>7181</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.752361</td>\n",
       "      <td>-8.040059</td>\n",
       "      <td>12.372583</td>\n",
       "      <td>1.533635</td>\n",
       "      <td>6.935294</td>\n",
       "      <td>-12.032179</td>\n",
       "      <td>-8.040059</td>\n",
       "      <td>12.372583</td>\n",
       "      <td>1.533635</td>\n",
       "      <td>6.935294</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3142 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      SUMLEV  REGION  DIVISION  STATE  COUNTY   STNAME            CTYNAME  \\\n",
       "1         50       3         6      1       1  Alabama     Autauga County   \n",
       "2         50       3         6      1       3  Alabama     Baldwin County   \n",
       "3         50       3         6      1       5  Alabama     Barbour County   \n",
       "4         50       3         6      1       7  Alabama        Bibb County   \n",
       "5         50       3         6      1       9  Alabama      Blount County   \n",
       "...      ...     ...       ...    ...     ...      ...                ...   \n",
       "3188      50       4         8     56      37  Wyoming  Sweetwater County   \n",
       "3189      50       4         8     56      39  Wyoming       Teton County   \n",
       "3190      50       4         8     56      41  Wyoming       Uinta County   \n",
       "3191      50       4         8     56      43  Wyoming    Washakie County   \n",
       "3192      50       4         8     56      45  Wyoming      Weston County   \n",
       "\n",
       "      CENSUS2010POP  ESTIMATESBASE2010  POPESTIMATE2010  ...  \\\n",
       "1             54571              54571            54660  ...   \n",
       "2            182265             182265           183193  ...   \n",
       "3             27457              27457            27341  ...   \n",
       "4             22915              22919            22861  ...   \n",
       "5             57322              57322            57373  ...   \n",
       "...             ...                ...              ...  ...   \n",
       "3188          43806              43806            43593  ...   \n",
       "3189          21294              21294            21297  ...   \n",
       "3190          21118              21118            21102  ...   \n",
       "3191           8533               8533             8545  ...   \n",
       "3192           7208               7208             7181  ...   \n",
       "\n",
       "      RDOMESTICMIG2011  RDOMESTICMIG2012  RDOMESTICMIG2013  RDOMESTICMIG2014  \\\n",
       "1             7.242091         -2.915927         -3.012349          2.265971   \n",
       "2            14.832960         17.647293         21.845705         19.243287   \n",
       "3            -4.728132         -2.500690         -7.056824         -3.904217   \n",
       "4            -5.527043         -5.068871         -6.201001         -0.177537   \n",
       "5             1.807375         -1.177622         -1.748766         -2.062535   \n",
       "...                ...               ...               ...               ...   \n",
       "3188          1.072643         16.243199         -5.339774        -14.252889   \n",
       "3189         -1.589565          0.972695         19.525929         14.143021   \n",
       "3190        -17.755986         -4.916350         -6.902954        -14.215862   \n",
       "3191        -11.637475         -0.827815         -2.013502        -17.781491   \n",
       "3192        -11.752361         -8.040059         12.372583          1.533635   \n",
       "\n",
       "      RDOMESTICMIG2015  RNETMIG2011  RNETMIG2012  RNETMIG2013  RNETMIG2014  \\\n",
       "1            -2.530799     7.606016    -2.626146    -2.722002     2.592270   \n",
       "2            17.197872    15.844176    18.559627    22.727626    20.317142   \n",
       "3           -10.543299    -4.874741    -2.758113    -7.167664    -3.978583   \n",
       "4             0.177258    -5.088389    -4.363636    -5.403729     0.754533   \n",
       "5            -1.369970     1.859511    -0.848580    -1.402476    -1.577232   \n",
       "...                ...          ...          ...          ...          ...   \n",
       "3188        -14.248864     1.255221    16.243199    -5.295460   -14.075283   \n",
       "3189         -0.564849     0.654527     2.408578    21.160658    16.308671   \n",
       "3190        -12.127022   -18.136812    -5.536861    -7.521840   -14.740608   \n",
       "3191          1.682288   -11.990126    -1.182592    -2.250385   -18.020168   \n",
       "3192          6.935294   -12.032179    -8.040059    12.372583     1.533635   \n",
       "\n",
       "      RNETMIG2015  \n",
       "1       -2.187333  \n",
       "2       18.293499  \n",
       "3      -10.543299  \n",
       "4        1.107861  \n",
       "5       -0.884411  \n",
       "...           ...  \n",
       "3188   -14.070195  \n",
       "3189     1.520747  \n",
       "3190   -12.606351  \n",
       "3191     1.441961  \n",
       "3192     6.935294  \n",
       "\n",
       "[3142 rows x 100 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "df = pd.read_csv('data/census.csv')\n",
    "df = df[df['SUMLEV']==50]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "for state in df['STNAME'].unique():\n",
    "    avg = np.average(df.where(df['STNAME']==state).dropna()['CENSUS2010POP'])\n",
    "    print('Counties in state ' + state + ' have an average population of ' + str(avg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "for group, frame in df.groupby('STNAME'):\n",
    "    avg = np.average(frame['CENSUS2010POP'])\n",
    "    print('Counties in state ' + group + ' have an average population of ' + str(avg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SUMLEV</th>\n",
       "      <th>REGION</th>\n",
       "      <th>DIVISION</th>\n",
       "      <th>STATE</th>\n",
       "      <th>COUNTY</th>\n",
       "      <th>STNAME</th>\n",
       "      <th>CTYNAME</th>\n",
       "      <th>CENSUS2010POP</th>\n",
       "      <th>ESTIMATESBASE2010</th>\n",
       "      <th>POPESTIMATE2010</th>\n",
       "      <th>...</th>\n",
       "      <th>RDOMESTICMIG2011</th>\n",
       "      <th>RDOMESTICMIG2012</th>\n",
       "      <th>RDOMESTICMIG2013</th>\n",
       "      <th>RDOMESTICMIG2014</th>\n",
       "      <th>RDOMESTICMIG2015</th>\n",
       "      <th>RNETMIG2011</th>\n",
       "      <th>RNETMIG2012</th>\n",
       "      <th>RNETMIG2013</th>\n",
       "      <th>RNETMIG2014</th>\n",
       "      <th>RNETMIG2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>54571</td>\n",
       "      <td>54571</td>\n",
       "      <td>54660</td>\n",
       "      <td>...</td>\n",
       "      <td>7.242091</td>\n",
       "      <td>-2.915927</td>\n",
       "      <td>-3.012349</td>\n",
       "      <td>2.265971</td>\n",
       "      <td>-2.530799</td>\n",
       "      <td>7.606016</td>\n",
       "      <td>-2.626146</td>\n",
       "      <td>-2.722002</td>\n",
       "      <td>2.592270</td>\n",
       "      <td>-2.187333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Baldwin County</td>\n",
       "      <td>182265</td>\n",
       "      <td>182265</td>\n",
       "      <td>183193</td>\n",
       "      <td>...</td>\n",
       "      <td>14.832960</td>\n",
       "      <td>17.647293</td>\n",
       "      <td>21.845705</td>\n",
       "      <td>19.243287</td>\n",
       "      <td>17.197872</td>\n",
       "      <td>15.844176</td>\n",
       "      <td>18.559627</td>\n",
       "      <td>22.727626</td>\n",
       "      <td>20.317142</td>\n",
       "      <td>18.293499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Barbour County</td>\n",
       "      <td>27457</td>\n",
       "      <td>27457</td>\n",
       "      <td>27341</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.728132</td>\n",
       "      <td>-2.500690</td>\n",
       "      <td>-7.056824</td>\n",
       "      <td>-3.904217</td>\n",
       "      <td>-10.543299</td>\n",
       "      <td>-4.874741</td>\n",
       "      <td>-2.758113</td>\n",
       "      <td>-7.167664</td>\n",
       "      <td>-3.978583</td>\n",
       "      <td>-10.543299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Bibb County</td>\n",
       "      <td>22915</td>\n",
       "      <td>22919</td>\n",
       "      <td>22861</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.527043</td>\n",
       "      <td>-5.068871</td>\n",
       "      <td>-6.201001</td>\n",
       "      <td>-0.177537</td>\n",
       "      <td>0.177258</td>\n",
       "      <td>-5.088389</td>\n",
       "      <td>-4.363636</td>\n",
       "      <td>-5.403729</td>\n",
       "      <td>0.754533</td>\n",
       "      <td>1.107861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Blount County</td>\n",
       "      <td>57322</td>\n",
       "      <td>57322</td>\n",
       "      <td>57373</td>\n",
       "      <td>...</td>\n",
       "      <td>1.807375</td>\n",
       "      <td>-1.177622</td>\n",
       "      <td>-1.748766</td>\n",
       "      <td>-2.062535</td>\n",
       "      <td>-1.369970</td>\n",
       "      <td>1.859511</td>\n",
       "      <td>-0.848580</td>\n",
       "      <td>-1.402476</td>\n",
       "      <td>-1.577232</td>\n",
       "      <td>-0.884411</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SUMLEV  REGION  DIVISION  STATE  COUNTY   STNAME         CTYNAME  \\\n",
       "1      50       3         6      1       1  Alabama  Autauga County   \n",
       "2      50       3         6      1       3  Alabama  Baldwin County   \n",
       "3      50       3         6      1       5  Alabama  Barbour County   \n",
       "4      50       3         6      1       7  Alabama     Bibb County   \n",
       "5      50       3         6      1       9  Alabama   Blount County   \n",
       "\n",
       "   CENSUS2010POP  ESTIMATESBASE2010  POPESTIMATE2010  ...  RDOMESTICMIG2011  \\\n",
       "1          54571              54571            54660  ...          7.242091   \n",
       "2         182265             182265           183193  ...         14.832960   \n",
       "3          27457              27457            27341  ...         -4.728132   \n",
       "4          22915              22919            22861  ...         -5.527043   \n",
       "5          57322              57322            57373  ...          1.807375   \n",
       "\n",
       "   RDOMESTICMIG2012  RDOMESTICMIG2013  RDOMESTICMIG2014  RDOMESTICMIG2015  \\\n",
       "1         -2.915927         -3.012349          2.265971         -2.530799   \n",
       "2         17.647293         21.845705         19.243287         17.197872   \n",
       "3         -2.500690         -7.056824         -3.904217        -10.543299   \n",
       "4         -5.068871         -6.201001         -0.177537          0.177258   \n",
       "5         -1.177622         -1.748766         -2.062535         -1.369970   \n",
       "\n",
       "   RNETMIG2011  RNETMIG2012  RNETMIG2013  RNETMIG2014  RNETMIG2015  \n",
       "1     7.606016    -2.626146    -2.722002     2.592270    -2.187333  \n",
       "2    15.844176    18.559627    22.727626    20.317142    18.293499  \n",
       "3    -4.874741    -2.758113    -7.167664    -3.978583   -10.543299  \n",
       "4    -5.088389    -4.363636    -5.403729     0.754533     1.107861  \n",
       "5     1.859511    -0.848580    -1.402476    -1.577232    -0.884411  \n",
       "\n",
       "[5 rows x 100 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 1177 records in group 0 for processing.\n",
      "There are 1134 records in group 1 for processing.\n",
      "There are 831 records in group 2 for processing.\n"
     ]
    }
   ],
   "source": [
    "df = df.set_index('STNAME')\n",
    "\n",
    "def fun(item):\n",
    "    if item[0]<'M':\n",
    "        return 0\n",
    "    if item[0]<'Q':\n",
    "        return 1\n",
    "    return 2\n",
    "\n",
    "for group, frame in df.groupby(fun):\n",
    "    print('There are ' + str(len(frame)) + ' records in group ' + str(group) + ' for processing.')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SUMLEV</th>\n",
       "      <th>REGION</th>\n",
       "      <th>DIVISION</th>\n",
       "      <th>STATE</th>\n",
       "      <th>COUNTY</th>\n",
       "      <th>STNAME</th>\n",
       "      <th>CTYNAME</th>\n",
       "      <th>CENSUS2010POP</th>\n",
       "      <th>ESTIMATESBASE2010</th>\n",
       "      <th>POPESTIMATE2010</th>\n",
       "      <th>...</th>\n",
       "      <th>RDOMESTICMIG2011</th>\n",
       "      <th>RDOMESTICMIG2012</th>\n",
       "      <th>RDOMESTICMIG2013</th>\n",
       "      <th>RDOMESTICMIG2014</th>\n",
       "      <th>RDOMESTICMIG2015</th>\n",
       "      <th>RNETMIG2011</th>\n",
       "      <th>RNETMIG2012</th>\n",
       "      <th>RNETMIG2013</th>\n",
       "      <th>RNETMIG2014</th>\n",
       "      <th>RNETMIG2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>54571</td>\n",
       "      <td>54571</td>\n",
       "      <td>54660</td>\n",
       "      <td>...</td>\n",
       "      <td>7.242091</td>\n",
       "      <td>-2.915927</td>\n",
       "      <td>-3.012349</td>\n",
       "      <td>2.265971</td>\n",
       "      <td>-2.530799</td>\n",
       "      <td>7.606016</td>\n",
       "      <td>-2.626146</td>\n",
       "      <td>-2.722002</td>\n",
       "      <td>2.592270</td>\n",
       "      <td>-2.187333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Baldwin County</td>\n",
       "      <td>182265</td>\n",
       "      <td>182265</td>\n",
       "      <td>183193</td>\n",
       "      <td>...</td>\n",
       "      <td>14.832960</td>\n",
       "      <td>17.647293</td>\n",
       "      <td>21.845705</td>\n",
       "      <td>19.243287</td>\n",
       "      <td>17.197872</td>\n",
       "      <td>15.844176</td>\n",
       "      <td>18.559627</td>\n",
       "      <td>22.727626</td>\n",
       "      <td>20.317142</td>\n",
       "      <td>18.293499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Barbour County</td>\n",
       "      <td>27457</td>\n",
       "      <td>27457</td>\n",
       "      <td>27341</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.728132</td>\n",
       "      <td>-2.500690</td>\n",
       "      <td>-7.056824</td>\n",
       "      <td>-3.904217</td>\n",
       "      <td>-10.543299</td>\n",
       "      <td>-4.874741</td>\n",
       "      <td>-2.758113</td>\n",
       "      <td>-7.167664</td>\n",
       "      <td>-3.978583</td>\n",
       "      <td>-10.543299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Bibb County</td>\n",
       "      <td>22915</td>\n",
       "      <td>22919</td>\n",
       "      <td>22861</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.527043</td>\n",
       "      <td>-5.068871</td>\n",
       "      <td>-6.201001</td>\n",
       "      <td>-0.177537</td>\n",
       "      <td>0.177258</td>\n",
       "      <td>-5.088389</td>\n",
       "      <td>-4.363636</td>\n",
       "      <td>-5.403729</td>\n",
       "      <td>0.754533</td>\n",
       "      <td>1.107861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Blount County</td>\n",
       "      <td>57322</td>\n",
       "      <td>57322</td>\n",
       "      <td>57373</td>\n",
       "      <td>...</td>\n",
       "      <td>1.807375</td>\n",
       "      <td>-1.177622</td>\n",
       "      <td>-1.748766</td>\n",
       "      <td>-2.062535</td>\n",
       "      <td>-1.369970</td>\n",
       "      <td>1.859511</td>\n",
       "      <td>-0.848580</td>\n",
       "      <td>-1.402476</td>\n",
       "      <td>-1.577232</td>\n",
       "      <td>-0.884411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>Aleutians East Borough</td>\n",
       "      <td>3141</td>\n",
       "      <td>3141</td>\n",
       "      <td>3169</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.604858</td>\n",
       "      <td>-12.221204</td>\n",
       "      <td>-17.257039</td>\n",
       "      <td>-27.748454</td>\n",
       "      <td>-16.221087</td>\n",
       "      <td>19.305620</td>\n",
       "      <td>8.249313</td>\n",
       "      <td>5.752346</td>\n",
       "      <td>-3.920977</td>\n",
       "      <td>7.509763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>Aleutians West Census Area</td>\n",
       "      <td>5561</td>\n",
       "      <td>5561</td>\n",
       "      <td>5546</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.496318</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-13.711875</td>\n",
       "      <td>-11.179039</td>\n",
       "      <td>-26.717891</td>\n",
       "      <td>1.257410</td>\n",
       "      <td>13.314397</td>\n",
       "      <td>0.175793</td>\n",
       "      <td>4.890830</td>\n",
       "      <td>-10.826858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>Anchorage Municipality</td>\n",
       "      <td>291826</td>\n",
       "      <td>291826</td>\n",
       "      <td>293405</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.788123</td>\n",
       "      <td>-7.563712</td>\n",
       "      <td>-3.962343</td>\n",
       "      <td>-18.897015</td>\n",
       "      <td>-19.781254</td>\n",
       "      <td>-0.969922</td>\n",
       "      <td>-2.652342</td>\n",
       "      <td>0.053320</td>\n",
       "      <td>-14.789980</td>\n",
       "      <td>-15.280810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>50</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>Bethel Census Area</td>\n",
       "      <td>17013</td>\n",
       "      <td>17013</td>\n",
       "      <td>17080</td>\n",
       "      <td>...</td>\n",
       "      <td>0.057906</td>\n",
       "      <td>-3.926031</td>\n",
       "      <td>-9.731949</td>\n",
       "      <td>-13.525220</td>\n",
       "      <td>-14.441440</td>\n",
       "      <td>0.173717</td>\n",
       "      <td>-3.300142</td>\n",
       "      <td>-9.056901</td>\n",
       "      <td>-12.798659</td>\n",
       "      <td>-13.716580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>60</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>Bristol Bay Borough</td>\n",
       "      <td>997</td>\n",
       "      <td>997</td>\n",
       "      <td>1002</td>\n",
       "      <td>...</td>\n",
       "      <td>23.529412</td>\n",
       "      <td>-54.401583</td>\n",
       "      <td>-33.023736</td>\n",
       "      <td>-14.736842</td>\n",
       "      <td>-55.495103</td>\n",
       "      <td>23.529412</td>\n",
       "      <td>-54.401583</td>\n",
       "      <td>-33.023736</td>\n",
       "      <td>-14.736842</td>\n",
       "      <td>-55.495103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>Apache County</td>\n",
       "      <td>71518</td>\n",
       "      <td>71518</td>\n",
       "      <td>71766</td>\n",
       "      <td>...</td>\n",
       "      <td>1.775891</td>\n",
       "      <td>1.197250</td>\n",
       "      <td>-20.566049</td>\n",
       "      <td>-5.674114</td>\n",
       "      <td>-11.302431</td>\n",
       "      <td>2.094996</td>\n",
       "      <td>1.500003</td>\n",
       "      <td>-20.220982</td>\n",
       "      <td>-5.326435</td>\n",
       "      <td>-10.939637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>Cochise County</td>\n",
       "      <td>131346</td>\n",
       "      <td>131357</td>\n",
       "      <td>131809</td>\n",
       "      <td>...</td>\n",
       "      <td>3.353411</td>\n",
       "      <td>-15.621933</td>\n",
       "      <td>-22.883978</td>\n",
       "      <td>-23.290753</td>\n",
       "      <td>-13.596166</td>\n",
       "      <td>5.128302</td>\n",
       "      <td>-12.065659</td>\n",
       "      <td>-20.574165</td>\n",
       "      <td>-20.939882</td>\n",
       "      <td>-10.798115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>Coconino County</td>\n",
       "      <td>134421</td>\n",
       "      <td>134437</td>\n",
       "      <td>134626</td>\n",
       "      <td>...</td>\n",
       "      <td>-12.402905</td>\n",
       "      <td>4.908203</td>\n",
       "      <td>-3.154921</td>\n",
       "      <td>-0.809483</td>\n",
       "      <td>2.992043</td>\n",
       "      <td>-11.569596</td>\n",
       "      <td>5.818774</td>\n",
       "      <td>-2.120401</td>\n",
       "      <td>0.444851</td>\n",
       "      <td>4.256795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>Gila County</td>\n",
       "      <td>53597</td>\n",
       "      <td>53597</td>\n",
       "      <td>53544</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.766233</td>\n",
       "      <td>-6.628859</td>\n",
       "      <td>-0.056574</td>\n",
       "      <td>4.125692</td>\n",
       "      <td>1.712168</td>\n",
       "      <td>-0.429838</td>\n",
       "      <td>-6.234508</td>\n",
       "      <td>0.396017</td>\n",
       "      <td>4.615501</td>\n",
       "      <td>2.220173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>Graham County</td>\n",
       "      <td>37220</td>\n",
       "      <td>37220</td>\n",
       "      <td>37137</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.054407</td>\n",
       "      <td>-10.941954</td>\n",
       "      <td>3.659258</td>\n",
       "      <td>5.972606</td>\n",
       "      <td>-17.348990</td>\n",
       "      <td>-8.946617</td>\n",
       "      <td>-10.860902</td>\n",
       "      <td>3.793790</td>\n",
       "      <td>6.264600</td>\n",
       "      <td>-17.031630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Arkansas County</td>\n",
       "      <td>19019</td>\n",
       "      <td>19018</td>\n",
       "      <td>19014</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.544054</td>\n",
       "      <td>2.799271</td>\n",
       "      <td>-10.483124</td>\n",
       "      <td>-15.687324</td>\n",
       "      <td>-7.460064</td>\n",
       "      <td>-5.488561</td>\n",
       "      <td>3.802783</td>\n",
       "      <td>-9.424222</td>\n",
       "      <td>-14.455896</td>\n",
       "      <td>-6.216720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Ashley County</td>\n",
       "      <td>21853</td>\n",
       "      <td>21853</td>\n",
       "      <td>21831</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.785244</td>\n",
       "      <td>-9.410783</td>\n",
       "      <td>-11.842074</td>\n",
       "      <td>-14.846789</td>\n",
       "      <td>-4.453596</td>\n",
       "      <td>-8.831241</td>\n",
       "      <td>-9.457142</td>\n",
       "      <td>-11.888881</td>\n",
       "      <td>-14.846789</td>\n",
       "      <td>-4.453596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Baxter County</td>\n",
       "      <td>41513</td>\n",
       "      <td>41513</td>\n",
       "      <td>41538</td>\n",
       "      <td>...</td>\n",
       "      <td>2.101170</td>\n",
       "      <td>3.230547</td>\n",
       "      <td>4.851824</td>\n",
       "      <td>5.280722</td>\n",
       "      <td>10.696624</td>\n",
       "      <td>2.125322</td>\n",
       "      <td>3.279127</td>\n",
       "      <td>4.900586</td>\n",
       "      <td>5.329617</td>\n",
       "      <td>10.745467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Benton County</td>\n",
       "      <td>221339</td>\n",
       "      <td>221344</td>\n",
       "      <td>223010</td>\n",
       "      <td>...</td>\n",
       "      <td>11.164115</td>\n",
       "      <td>11.786353</td>\n",
       "      <td>9.333699</td>\n",
       "      <td>11.268649</td>\n",
       "      <td>16.254517</td>\n",
       "      <td>13.816535</td>\n",
       "      <td>14.533319</td>\n",
       "      <td>12.296171</td>\n",
       "      <td>14.648828</td>\n",
       "      <td>19.555772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Boone County</td>\n",
       "      <td>36903</td>\n",
       "      <td>36903</td>\n",
       "      <td>36897</td>\n",
       "      <td>...</td>\n",
       "      <td>4.003138</td>\n",
       "      <td>6.050583</td>\n",
       "      <td>0.642441</td>\n",
       "      <td>-6.520077</td>\n",
       "      <td>0.510931</td>\n",
       "      <td>3.976089</td>\n",
       "      <td>5.889234</td>\n",
       "      <td>0.535368</td>\n",
       "      <td>-6.627403</td>\n",
       "      <td>0.430258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>California</td>\n",
       "      <td>Alameda County</td>\n",
       "      <td>1510271</td>\n",
       "      <td>1510261</td>\n",
       "      <td>1513754</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.363660</td>\n",
       "      <td>2.488670</td>\n",
       "      <td>3.743636</td>\n",
       "      <td>4.436457</td>\n",
       "      <td>2.141452</td>\n",
       "      <td>6.535369</td>\n",
       "      <td>9.157917</td>\n",
       "      <td>10.954544</td>\n",
       "      <td>12.487898</td>\n",
       "      <td>10.059473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>California</td>\n",
       "      <td>Alpine County</td>\n",
       "      <td>1175</td>\n",
       "      <td>1175</td>\n",
       "      <td>1159</td>\n",
       "      <td>...</td>\n",
       "      <td>-47.577093</td>\n",
       "      <td>11.622709</td>\n",
       "      <td>15.859031</td>\n",
       "      <td>-32.874278</td>\n",
       "      <td>6.314840</td>\n",
       "      <td>-46.696035</td>\n",
       "      <td>12.516764</td>\n",
       "      <td>16.740088</td>\n",
       "      <td>-31.985784</td>\n",
       "      <td>7.216960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>California</td>\n",
       "      <td>Amador County</td>\n",
       "      <td>38091</td>\n",
       "      <td>38091</td>\n",
       "      <td>37873</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.766029</td>\n",
       "      <td>-8.440854</td>\n",
       "      <td>-9.743520</td>\n",
       "      <td>7.254381</td>\n",
       "      <td>10.034579</td>\n",
       "      <td>-3.527337</td>\n",
       "      <td>-8.065705</td>\n",
       "      <td>-9.254987</td>\n",
       "      <td>7.772551</td>\n",
       "      <td>10.549868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>California</td>\n",
       "      <td>Butte County</td>\n",
       "      <td>220000</td>\n",
       "      <td>220000</td>\n",
       "      <td>219977</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.213647</td>\n",
       "      <td>3.934509</td>\n",
       "      <td>2.711121</td>\n",
       "      <td>6.306773</td>\n",
       "      <td>3.043761</td>\n",
       "      <td>-0.454550</td>\n",
       "      <td>4.782151</td>\n",
       "      <td>3.608814</td>\n",
       "      <td>7.431862</td>\n",
       "      <td>4.205196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>California</td>\n",
       "      <td>Calaveras County</td>\n",
       "      <td>45578</td>\n",
       "      <td>45578</td>\n",
       "      <td>45464</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.050903</td>\n",
       "      <td>-6.054131</td>\n",
       "      <td>0.604507</td>\n",
       "      <td>3.679234</td>\n",
       "      <td>8.612686</td>\n",
       "      <td>-5.653398</td>\n",
       "      <td>-5.720264</td>\n",
       "      <td>1.052290</td>\n",
       "      <td>4.150355</td>\n",
       "      <td>9.082469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>Adams County</td>\n",
       "      <td>441603</td>\n",
       "      <td>441687</td>\n",
       "      <td>443680</td>\n",
       "      <td>...</td>\n",
       "      <td>5.982917</td>\n",
       "      <td>7.689510</td>\n",
       "      <td>9.494072</td>\n",
       "      <td>10.849385</td>\n",
       "      <td>10.003023</td>\n",
       "      <td>7.605895</td>\n",
       "      <td>9.334759</td>\n",
       "      <td>11.312999</td>\n",
       "      <td>12.975974</td>\n",
       "      <td>12.150054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>Alamosa County</td>\n",
       "      <td>15445</td>\n",
       "      <td>15445</td>\n",
       "      <td>15926</td>\n",
       "      <td>...</td>\n",
       "      <td>5.490906</td>\n",
       "      <td>-5.517156</td>\n",
       "      <td>2.592433</td>\n",
       "      <td>-5.340044</td>\n",
       "      <td>1.706589</td>\n",
       "      <td>6.114872</td>\n",
       "      <td>-4.711279</td>\n",
       "      <td>3.580026</td>\n",
       "      <td>-4.296587</td>\n",
       "      <td>2.742732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>Arapahoe County</td>\n",
       "      <td>572003</td>\n",
       "      <td>572155</td>\n",
       "      <td>574727</td>\n",
       "      <td>...</td>\n",
       "      <td>7.756987</td>\n",
       "      <td>6.256681</td>\n",
       "      <td>8.577457</td>\n",
       "      <td>6.718039</td>\n",
       "      <td>7.128637</td>\n",
       "      <td>11.252972</td>\n",
       "      <td>10.087820</td>\n",
       "      <td>12.627969</td>\n",
       "      <td>11.245590</td>\n",
       "      <td>11.633206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>Archuleta County</td>\n",
       "      <td>12084</td>\n",
       "      <td>12084</td>\n",
       "      <td>12056</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.640156</td>\n",
       "      <td>4.974299</td>\n",
       "      <td>6.091036</td>\n",
       "      <td>0.573912</td>\n",
       "      <td>10.911164</td>\n",
       "      <td>-9.307737</td>\n",
       "      <td>5.223014</td>\n",
       "      <td>6.420282</td>\n",
       "      <td>0.983848</td>\n",
       "      <td>11.318297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>Baca County</td>\n",
       "      <td>3788</td>\n",
       "      <td>3788</td>\n",
       "      <td>3790</td>\n",
       "      <td>...</td>\n",
       "      <td>8.684211</td>\n",
       "      <td>-7.922884</td>\n",
       "      <td>-16.924110</td>\n",
       "      <td>-14.486812</td>\n",
       "      <td>-0.551724</td>\n",
       "      <td>8.947368</td>\n",
       "      <td>-7.658788</td>\n",
       "      <td>-16.655473</td>\n",
       "      <td>-13.666803</td>\n",
       "      <td>0.275862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2852</th>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>Vermont</td>\n",
       "      <td>Addison County</td>\n",
       "      <td>36821</td>\n",
       "      <td>36824</td>\n",
       "      <td>36820</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.705630</td>\n",
       "      <td>-1.437776</td>\n",
       "      <td>-1.328417</td>\n",
       "      <td>0.838348</td>\n",
       "      <td>-3.807209</td>\n",
       "      <td>0.949887</td>\n",
       "      <td>0.352662</td>\n",
       "      <td>0.840427</td>\n",
       "      <td>3.245217</td>\n",
       "      <td>-1.377076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2853</th>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>Vermont</td>\n",
       "      <td>Bennington County</td>\n",
       "      <td>37125</td>\n",
       "      <td>37125</td>\n",
       "      <td>37105</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.868106</td>\n",
       "      <td>-2.203572</td>\n",
       "      <td>1.090186</td>\n",
       "      <td>-4.842019</td>\n",
       "      <td>-0.549987</td>\n",
       "      <td>-3.435311</td>\n",
       "      <td>-1.795503</td>\n",
       "      <td>1.526260</td>\n",
       "      <td>-4.294898</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2854</th>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>5</td>\n",
       "      <td>Vermont</td>\n",
       "      <td>Caledonia County</td>\n",
       "      <td>31227</td>\n",
       "      <td>31232</td>\n",
       "      <td>31181</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.990114</td>\n",
       "      <td>-0.739348</td>\n",
       "      <td>1.735999</td>\n",
       "      <td>-5.413854</td>\n",
       "      <td>-6.059526</td>\n",
       "      <td>-1.572832</td>\n",
       "      <td>-0.450038</td>\n",
       "      <td>2.057481</td>\n",
       "      <td>-5.059375</td>\n",
       "      <td>-5.670679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2855</th>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>Vermont</td>\n",
       "      <td>Chittenden County</td>\n",
       "      <td>156545</td>\n",
       "      <td>156540</td>\n",
       "      <td>156805</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.044508</td>\n",
       "      <td>-0.031596</td>\n",
       "      <td>0.451860</td>\n",
       "      <td>-1.652769</td>\n",
       "      <td>-3.669383</td>\n",
       "      <td>2.549666</td>\n",
       "      <td>2.932088</td>\n",
       "      <td>3.577223</td>\n",
       "      <td>1.927191</td>\n",
       "      <td>-0.068296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2856</th>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>9</td>\n",
       "      <td>Vermont</td>\n",
       "      <td>Essex County</td>\n",
       "      <td>6306</td>\n",
       "      <td>6306</td>\n",
       "      <td>6302</td>\n",
       "      <td>...</td>\n",
       "      <td>1.425178</td>\n",
       "      <td>-15.297586</td>\n",
       "      <td>-2.416432</td>\n",
       "      <td>-10.713416</td>\n",
       "      <td>6.833713</td>\n",
       "      <td>1.425178</td>\n",
       "      <td>-15.297586</td>\n",
       "      <td>-2.255336</td>\n",
       "      <td>-10.551092</td>\n",
       "      <td>6.996420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2867</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>1</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>Accomack County</td>\n",
       "      <td>33164</td>\n",
       "      <td>33164</td>\n",
       "      <td>33165</td>\n",
       "      <td>...</td>\n",
       "      <td>1.625233</td>\n",
       "      <td>-2.312278</td>\n",
       "      <td>-9.650326</td>\n",
       "      <td>-0.090905</td>\n",
       "      <td>-1.606767</td>\n",
       "      <td>3.280563</td>\n",
       "      <td>-0.030030</td>\n",
       "      <td>-7.659947</td>\n",
       "      <td>2.212021</td>\n",
       "      <td>0.848858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2868</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>3</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>Albemarle County</td>\n",
       "      <td>98970</td>\n",
       "      <td>98998</td>\n",
       "      <td>99236</td>\n",
       "      <td>...</td>\n",
       "      <td>5.393263</td>\n",
       "      <td>6.682955</td>\n",
       "      <td>2.841173</td>\n",
       "      <td>6.466120</td>\n",
       "      <td>6.426919</td>\n",
       "      <td>8.415091</td>\n",
       "      <td>9.960268</td>\n",
       "      <td>6.268154</td>\n",
       "      <td>10.384396</td>\n",
       "      <td>10.330677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2869</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>5</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>Alleghany County</td>\n",
       "      <td>16250</td>\n",
       "      <td>16261</td>\n",
       "      <td>16211</td>\n",
       "      <td>...</td>\n",
       "      <td>6.267089</td>\n",
       "      <td>-3.008627</td>\n",
       "      <td>2.898729</td>\n",
       "      <td>-10.910565</td>\n",
       "      <td>-5.386395</td>\n",
       "      <td>6.451415</td>\n",
       "      <td>-2.947226</td>\n",
       "      <td>3.022080</td>\n",
       "      <td>-10.785872</td>\n",
       "      <td>-5.259656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2870</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>7</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>Amelia County</td>\n",
       "      <td>12690</td>\n",
       "      <td>12695</td>\n",
       "      <td>12742</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.117730</td>\n",
       "      <td>-1.098168</td>\n",
       "      <td>-1.729696</td>\n",
       "      <td>4.473571</td>\n",
       "      <td>9.576456</td>\n",
       "      <td>-0.392172</td>\n",
       "      <td>-0.549084</td>\n",
       "      <td>-1.179338</td>\n",
       "      <td>5.101440</td>\n",
       "      <td>10.199315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2871</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>51</td>\n",
       "      <td>9</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>Amherst County</td>\n",
       "      <td>32353</td>\n",
       "      <td>32354</td>\n",
       "      <td>32385</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.658440</td>\n",
       "      <td>10.655433</td>\n",
       "      <td>-6.280260</td>\n",
       "      <td>-3.423592</td>\n",
       "      <td>-3.094911</td>\n",
       "      <td>-7.596428</td>\n",
       "      <td>10.841284</td>\n",
       "      <td>-6.063700</td>\n",
       "      <td>-3.205727</td>\n",
       "      <td>-2.844817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3001</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Adams County</td>\n",
       "      <td>18728</td>\n",
       "      <td>18728</td>\n",
       "      <td>18810</td>\n",
       "      <td>...</td>\n",
       "      <td>-14.962990</td>\n",
       "      <td>-12.524772</td>\n",
       "      <td>-6.093077</td>\n",
       "      <td>-10.807142</td>\n",
       "      <td>-12.120266</td>\n",
       "      <td>-13.901785</td>\n",
       "      <td>-11.943454</td>\n",
       "      <td>-5.305179</td>\n",
       "      <td>-9.397515</td>\n",
       "      <td>-10.507699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3002</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>53</td>\n",
       "      <td>3</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Asotin County</td>\n",
       "      <td>21623</td>\n",
       "      <td>21623</td>\n",
       "      <td>21710</td>\n",
       "      <td>...</td>\n",
       "      <td>8.480403</td>\n",
       "      <td>-1.095940</td>\n",
       "      <td>11.230336</td>\n",
       "      <td>2.799223</td>\n",
       "      <td>-2.618924</td>\n",
       "      <td>8.342883</td>\n",
       "      <td>-1.324261</td>\n",
       "      <td>11.003001</td>\n",
       "      <td>2.573480</td>\n",
       "      <td>-2.844693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3003</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>53</td>\n",
       "      <td>5</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Benton County</td>\n",
       "      <td>175177</td>\n",
       "      <td>175177</td>\n",
       "      <td>176516</td>\n",
       "      <td>...</td>\n",
       "      <td>14.001837</td>\n",
       "      <td>1.955320</td>\n",
       "      <td>2.587738</td>\n",
       "      <td>2.672191</td>\n",
       "      <td>10.239922</td>\n",
       "      <td>15.256402</td>\n",
       "      <td>3.183591</td>\n",
       "      <td>3.987840</td>\n",
       "      <td>4.234560</td>\n",
       "      <td>11.789174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3004</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>53</td>\n",
       "      <td>7</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Chelan County</td>\n",
       "      <td>72453</td>\n",
       "      <td>72456</td>\n",
       "      <td>72743</td>\n",
       "      <td>...</td>\n",
       "      <td>2.628877</td>\n",
       "      <td>0.666522</td>\n",
       "      <td>-0.324838</td>\n",
       "      <td>3.121237</td>\n",
       "      <td>8.413094</td>\n",
       "      <td>3.587321</td>\n",
       "      <td>1.618695</td>\n",
       "      <td>0.812095</td>\n",
       "      <td>4.480052</td>\n",
       "      <td>9.784215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3005</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>53</td>\n",
       "      <td>9</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Clallam County</td>\n",
       "      <td>71404</td>\n",
       "      <td>71404</td>\n",
       "      <td>71533</td>\n",
       "      <td>...</td>\n",
       "      <td>6.280048</td>\n",
       "      <td>3.899531</td>\n",
       "      <td>7.330737</td>\n",
       "      <td>8.282145</td>\n",
       "      <td>13.533670</td>\n",
       "      <td>6.838275</td>\n",
       "      <td>4.665511</td>\n",
       "      <td>8.038820</td>\n",
       "      <td>9.041342</td>\n",
       "      <td>14.395774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3041</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Barbour County</td>\n",
       "      <td>16589</td>\n",
       "      <td>16589</td>\n",
       "      <td>16596</td>\n",
       "      <td>...</td>\n",
       "      <td>1.265251</td>\n",
       "      <td>14.046623</td>\n",
       "      <td>-2.972475</td>\n",
       "      <td>-1.493028</td>\n",
       "      <td>2.274632</td>\n",
       "      <td>1.385751</td>\n",
       "      <td>14.046623</td>\n",
       "      <td>-2.972475</td>\n",
       "      <td>-1.373585</td>\n",
       "      <td>2.394349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3042</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>54</td>\n",
       "      <td>3</td>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Berkeley County</td>\n",
       "      <td>104169</td>\n",
       "      <td>104172</td>\n",
       "      <td>104646</td>\n",
       "      <td>...</td>\n",
       "      <td>4.906062</td>\n",
       "      <td>7.784296</td>\n",
       "      <td>8.403712</td>\n",
       "      <td>11.389012</td>\n",
       "      <td>8.385254</td>\n",
       "      <td>5.600137</td>\n",
       "      <td>8.574007</td>\n",
       "      <td>9.127210</td>\n",
       "      <td>12.220127</td>\n",
       "      <td>9.203986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3043</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>54</td>\n",
       "      <td>5</td>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Boone County</td>\n",
       "      <td>24629</td>\n",
       "      <td>24627</td>\n",
       "      <td>24585</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.997471</td>\n",
       "      <td>-1.556835</td>\n",
       "      <td>-10.980845</td>\n",
       "      <td>-12.925896</td>\n",
       "      <td>-13.713752</td>\n",
       "      <td>-4.038262</td>\n",
       "      <td>-1.597804</td>\n",
       "      <td>-11.022127</td>\n",
       "      <td>-12.967727</td>\n",
       "      <td>-13.756209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3044</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>54</td>\n",
       "      <td>7</td>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Braxton County</td>\n",
       "      <td>14523</td>\n",
       "      <td>14519</td>\n",
       "      <td>14527</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.275198</td>\n",
       "      <td>-2.342404</td>\n",
       "      <td>-2.489368</td>\n",
       "      <td>2.077347</td>\n",
       "      <td>-0.692953</td>\n",
       "      <td>-0.068799</td>\n",
       "      <td>-2.135722</td>\n",
       "      <td>-2.212772</td>\n",
       "      <td>2.354326</td>\n",
       "      <td>-0.415772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3045</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>54</td>\n",
       "      <td>9</td>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Brooke County</td>\n",
       "      <td>24069</td>\n",
       "      <td>24071</td>\n",
       "      <td>24007</td>\n",
       "      <td>...</td>\n",
       "      <td>2.920439</td>\n",
       "      <td>1.340735</td>\n",
       "      <td>1.010186</td>\n",
       "      <td>-2.878855</td>\n",
       "      <td>-1.237228</td>\n",
       "      <td>3.003880</td>\n",
       "      <td>1.466429</td>\n",
       "      <td>1.220641</td>\n",
       "      <td>-2.667175</td>\n",
       "      <td>-1.023913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3097</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>1</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Adams County</td>\n",
       "      <td>20875</td>\n",
       "      <td>20875</td>\n",
       "      <td>20864</td>\n",
       "      <td>...</td>\n",
       "      <td>7.469833</td>\n",
       "      <td>-13.276686</td>\n",
       "      <td>5.510985</td>\n",
       "      <td>-8.701851</td>\n",
       "      <td>2.726687</td>\n",
       "      <td>7.517717</td>\n",
       "      <td>-13.131850</td>\n",
       "      <td>5.754834</td>\n",
       "      <td>-8.357710</td>\n",
       "      <td>3.172872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3098</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>3</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Ashland County</td>\n",
       "      <td>16157</td>\n",
       "      <td>16157</td>\n",
       "      <td>16163</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.210110</td>\n",
       "      <td>-12.316734</td>\n",
       "      <td>8.634714</td>\n",
       "      <td>2.427411</td>\n",
       "      <td>-12.782355</td>\n",
       "      <td>-5.086060</td>\n",
       "      <td>-12.191691</td>\n",
       "      <td>8.759855</td>\n",
       "      <td>2.551894</td>\n",
       "      <td>-12.657038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3099</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>5</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Barron County</td>\n",
       "      <td>45870</td>\n",
       "      <td>45870</td>\n",
       "      <td>45840</td>\n",
       "      <td>...</td>\n",
       "      <td>1.024523</td>\n",
       "      <td>-4.928472</td>\n",
       "      <td>-4.811057</td>\n",
       "      <td>-4.585495</td>\n",
       "      <td>-0.614939</td>\n",
       "      <td>1.504087</td>\n",
       "      <td>-3.859909</td>\n",
       "      <td>-3.630161</td>\n",
       "      <td>-3.225205</td>\n",
       "      <td>0.746711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3100</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>7</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Bayfield County</td>\n",
       "      <td>15014</td>\n",
       "      <td>15014</td>\n",
       "      <td>15011</td>\n",
       "      <td>...</td>\n",
       "      <td>7.172029</td>\n",
       "      <td>-0.927152</td>\n",
       "      <td>4.370282</td>\n",
       "      <td>-8.911352</td>\n",
       "      <td>2.805518</td>\n",
       "      <td>7.636883</td>\n",
       "      <td>-0.463576</td>\n",
       "      <td>4.833797</td>\n",
       "      <td>-8.379331</td>\n",
       "      <td>3.339902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3101</th>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>9</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Brown County</td>\n",
       "      <td>248007</td>\n",
       "      <td>248007</td>\n",
       "      <td>248507</td>\n",
       "      <td>...</td>\n",
       "      <td>0.965796</td>\n",
       "      <td>2.073066</td>\n",
       "      <td>-1.630833</td>\n",
       "      <td>-0.355980</td>\n",
       "      <td>-0.624871</td>\n",
       "      <td>2.372413</td>\n",
       "      <td>3.606022</td>\n",
       "      <td>-0.003939</td>\n",
       "      <td>1.607777</td>\n",
       "      <td>1.319604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3170</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Albany County</td>\n",
       "      <td>36299</td>\n",
       "      <td>36299</td>\n",
       "      <td>36428</td>\n",
       "      <td>...</td>\n",
       "      <td>3.708956</td>\n",
       "      <td>2.637812</td>\n",
       "      <td>-3.544634</td>\n",
       "      <td>-3.334877</td>\n",
       "      <td>-9.911169</td>\n",
       "      <td>6.736119</td>\n",
       "      <td>6.433032</td>\n",
       "      <td>0.719587</td>\n",
       "      <td>1.429233</td>\n",
       "      <td>-5.166460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3171</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>3</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Big Horn County</td>\n",
       "      <td>11668</td>\n",
       "      <td>11668</td>\n",
       "      <td>11672</td>\n",
       "      <td>...</td>\n",
       "      <td>4.868258</td>\n",
       "      <td>2.804930</td>\n",
       "      <td>16.815908</td>\n",
       "      <td>-8.026420</td>\n",
       "      <td>5.095861</td>\n",
       "      <td>4.868258</td>\n",
       "      <td>3.144921</td>\n",
       "      <td>17.236306</td>\n",
       "      <td>-7.608378</td>\n",
       "      <td>5.513554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3172</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Campbell County</td>\n",
       "      <td>46133</td>\n",
       "      <td>46133</td>\n",
       "      <td>46244</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.843479</td>\n",
       "      <td>15.601020</td>\n",
       "      <td>-5.895711</td>\n",
       "      <td>-8.550911</td>\n",
       "      <td>10.916963</td>\n",
       "      <td>-2.649606</td>\n",
       "      <td>15.558684</td>\n",
       "      <td>-5.916543</td>\n",
       "      <td>-8.509402</td>\n",
       "      <td>10.978525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3173</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>7</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Carbon County</td>\n",
       "      <td>15885</td>\n",
       "      <td>15885</td>\n",
       "      <td>15837</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.581980</td>\n",
       "      <td>-13.081441</td>\n",
       "      <td>3.178134</td>\n",
       "      <td>-2.970641</td>\n",
       "      <td>-23.300971</td>\n",
       "      <td>-7.392431</td>\n",
       "      <td>-12.636926</td>\n",
       "      <td>3.623073</td>\n",
       "      <td>-2.338590</td>\n",
       "      <td>-22.600668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3174</th>\n",
       "      <td>50</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "      <td>9</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Converse County</td>\n",
       "      <td>13833</td>\n",
       "      <td>13833</td>\n",
       "      <td>13826</td>\n",
       "      <td>...</td>\n",
       "      <td>-12.847499</td>\n",
       "      <td>15.493820</td>\n",
       "      <td>19.035533</td>\n",
       "      <td>-20.550587</td>\n",
       "      <td>-0.070403</td>\n",
       "      <td>-12.774915</td>\n",
       "      <td>16.502720</td>\n",
       "      <td>20.093063</td>\n",
       "      <td>-19.358233</td>\n",
       "      <td>1.126443</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>249 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      SUMLEV  REGION  DIVISION  STATE  COUNTY   STNAME          CTYNAME  \\\n",
       "1         50       3         6      1       1  Alabama   Autauga County   \n",
       "2         50       3         6      1       3  Alabama   Baldwin County   \n",
       "3         50       3         6      1       5  Alabama   Barbour County   \n",
       "4         50       3         6      1       7  Alabama      Bibb County   \n",
       "5         50       3         6      1       9  Alabama    Blount County   \n",
       "...      ...     ...       ...    ...     ...      ...              ...   \n",
       "3170      50       4         8     56       1  Wyoming    Albany County   \n",
       "3171      50       4         8     56       3  Wyoming  Big Horn County   \n",
       "3172      50       4         8     56       5  Wyoming  Campbell County   \n",
       "3173      50       4         8     56       7  Wyoming    Carbon County   \n",
       "3174      50       4         8     56       9  Wyoming  Converse County   \n",
       "\n",
       "      CENSUS2010POP  ESTIMATESBASE2010  POPESTIMATE2010  ...  \\\n",
       "1             54571              54571            54660  ...   \n",
       "2            182265             182265           183193  ...   \n",
       "3             27457              27457            27341  ...   \n",
       "4             22915              22919            22861  ...   \n",
       "5             57322              57322            57373  ...   \n",
       "...             ...                ...              ...  ...   \n",
       "3170          36299              36299            36428  ...   \n",
       "3171          11668              11668            11672  ...   \n",
       "3172          46133              46133            46244  ...   \n",
       "3173          15885              15885            15837  ...   \n",
       "3174          13833              13833            13826  ...   \n",
       "\n",
       "      RDOMESTICMIG2011  RDOMESTICMIG2012  RDOMESTICMIG2013  RDOMESTICMIG2014  \\\n",
       "1             7.242091         -2.915927         -3.012349          2.265971   \n",
       "2            14.832960         17.647293         21.845705         19.243287   \n",
       "3            -4.728132         -2.500690         -7.056824         -3.904217   \n",
       "4            -5.527043         -5.068871         -6.201001         -0.177537   \n",
       "5             1.807375         -1.177622         -1.748766         -2.062535   \n",
       "...                ...               ...               ...               ...   \n",
       "3170          3.708956          2.637812         -3.544634         -3.334877   \n",
       "3171          4.868258          2.804930         16.815908         -8.026420   \n",
       "3172         -2.843479         15.601020         -5.895711         -8.550911   \n",
       "3173         -7.581980        -13.081441          3.178134         -2.970641   \n",
       "3174        -12.847499         15.493820         19.035533        -20.550587   \n",
       "\n",
       "      RDOMESTICMIG2015  RNETMIG2011  RNETMIG2012  RNETMIG2013  RNETMIG2014  \\\n",
       "1            -2.530799     7.606016    -2.626146    -2.722002     2.592270   \n",
       "2            17.197872    15.844176    18.559627    22.727626    20.317142   \n",
       "3           -10.543299    -4.874741    -2.758113    -7.167664    -3.978583   \n",
       "4             0.177258    -5.088389    -4.363636    -5.403729     0.754533   \n",
       "5            -1.369970     1.859511    -0.848580    -1.402476    -1.577232   \n",
       "...                ...          ...          ...          ...          ...   \n",
       "3170         -9.911169     6.736119     6.433032     0.719587     1.429233   \n",
       "3171          5.095861     4.868258     3.144921    17.236306    -7.608378   \n",
       "3172         10.916963    -2.649606    15.558684    -5.916543    -8.509402   \n",
       "3173        -23.300971    -7.392431   -12.636926     3.623073    -2.338590   \n",
       "3174         -0.070403   -12.774915    16.502720    20.093063   -19.358233   \n",
       "\n",
       "      RNETMIG2015  \n",
       "1       -2.187333  \n",
       "2       18.293499  \n",
       "3      -10.543299  \n",
       "4        1.107861  \n",
       "5       -0.884411  \n",
       "...           ...  \n",
       "3170    -5.166460  \n",
       "3171     5.513554  \n",
       "3172    10.978525  \n",
       "3173   -22.600668  \n",
       "3174     1.126443  \n",
       "\n",
       "[249 rows x 100 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/census.csv')\n",
    "df = df[df['SUMLEV']==50]\n",
    "df1 = df.groupby('STNAME')\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CENSUS2010POP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STNAME</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>71339.343284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>24490.724138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>426134.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>38878.906667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>642309.586207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>78581.187500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>446762.125000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>299311.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>601723.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>280616.567164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>60928.635220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawaii</th>\n",
       "      <td>272060.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>35626.863636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>125790.509804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>70476.108696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>30771.262626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>27172.552381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>36161.391667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>70833.937500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>83022.562500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>240564.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>467687.785714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>119080.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>60964.655172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>36186.548780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>52077.626087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>17668.125000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>19638.075269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>158855.941176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>131647.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>418661.619048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>62399.363636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>312550.032258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>95354.830000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>12690.396226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>131096.636364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>48718.844156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>106418.722222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>189587.746269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>210513.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>100551.391304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>12336.060606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>66801.105263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>98998.271654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>95306.379310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>44695.785714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>60111.293233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>172424.102564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>33690.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>78985.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyoming</th>\n",
       "      <td>24505.478261</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      CENSUS2010POP\n",
       "STNAME                             \n",
       "Alabama                71339.343284\n",
       "Alaska                 24490.724138\n",
       "Arizona               426134.466667\n",
       "Arkansas               38878.906667\n",
       "California            642309.586207\n",
       "Colorado               78581.187500\n",
       "Connecticut           446762.125000\n",
       "Delaware              299311.333333\n",
       "District of Columbia  601723.000000\n",
       "Florida               280616.567164\n",
       "Georgia                60928.635220\n",
       "Hawaii                272060.200000\n",
       "Idaho                  35626.863636\n",
       "Illinois              125790.509804\n",
       "Indiana                70476.108696\n",
       "Iowa                   30771.262626\n",
       "Kansas                 27172.552381\n",
       "Kentucky               36161.391667\n",
       "Louisiana              70833.937500\n",
       "Maine                  83022.562500\n",
       "Maryland              240564.666667\n",
       "Massachusetts         467687.785714\n",
       "Michigan              119080.000000\n",
       "Minnesota              60964.655172\n",
       "Mississippi            36186.548780\n",
       "Missouri               52077.626087\n",
       "Montana                17668.125000\n",
       "Nebraska               19638.075269\n",
       "Nevada                158855.941176\n",
       "New Hampshire         131647.000000\n",
       "New Jersey            418661.619048\n",
       "New Mexico             62399.363636\n",
       "New York              312550.032258\n",
       "North Carolina         95354.830000\n",
       "North Dakota           12690.396226\n",
       "Ohio                  131096.636364\n",
       "Oklahoma               48718.844156\n",
       "Oregon                106418.722222\n",
       "Pennsylvania          189587.746269\n",
       "Rhode Island          210513.400000\n",
       "South Carolina        100551.391304\n",
       "South Dakota           12336.060606\n",
       "Tennessee              66801.105263\n",
       "Texas                  98998.271654\n",
       "Utah                   95306.379310\n",
       "Vermont                44695.785714\n",
       "Virginia               60111.293233\n",
       "Washington            172424.102564\n",
       "West Virginia          33690.800000\n",
       "Wisconsin              78985.916667\n",
       "Wyoming                24505.478261"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('STNAME').agg({'CENSUS2010POP': np.average})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2['CENSUS2010POP'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SUMLEV</th>\n",
       "      <th>REGION</th>\n",
       "      <th>DIVISION</th>\n",
       "      <th>STATE</th>\n",
       "      <th>COUNTY</th>\n",
       "      <th>STNAME</th>\n",
       "      <th>CTYNAME</th>\n",
       "      <th>CENSUS2010POP</th>\n",
       "      <th>ESTIMATESBASE2010</th>\n",
       "      <th>POPESTIMATE2010</th>\n",
       "      <th>...</th>\n",
       "      <th>RDOMESTICMIG2011</th>\n",
       "      <th>RDOMESTICMIG2012</th>\n",
       "      <th>RDOMESTICMIG2013</th>\n",
       "      <th>RDOMESTICMIG2014</th>\n",
       "      <th>RDOMESTICMIG2015</th>\n",
       "      <th>RNETMIG2011</th>\n",
       "      <th>RNETMIG2012</th>\n",
       "      <th>RNETMIG2013</th>\n",
       "      <th>RNETMIG2014</th>\n",
       "      <th>RNETMIG2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Autauga County</td>\n",
       "      <td>1</td>\n",
       "      <td>54571</td>\n",
       "      <td>54660</td>\n",
       "      <td>...</td>\n",
       "      <td>7.242091</td>\n",
       "      <td>-2.915927</td>\n",
       "      <td>-3.012349</td>\n",
       "      <td>2.265971</td>\n",
       "      <td>-2.530799</td>\n",
       "      <td>7.606016</td>\n",
       "      <td>-2.626146</td>\n",
       "      <td>-2.722002</td>\n",
       "      <td>2.592270</td>\n",
       "      <td>-2.187333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Baldwin County</td>\n",
       "      <td>1</td>\n",
       "      <td>182265</td>\n",
       "      <td>183193</td>\n",
       "      <td>...</td>\n",
       "      <td>14.832960</td>\n",
       "      <td>17.647293</td>\n",
       "      <td>21.845705</td>\n",
       "      <td>19.243287</td>\n",
       "      <td>17.197872</td>\n",
       "      <td>15.844176</td>\n",
       "      <td>18.559627</td>\n",
       "      <td>22.727626</td>\n",
       "      <td>20.317142</td>\n",
       "      <td>18.293499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Barbour County</td>\n",
       "      <td>1</td>\n",
       "      <td>27457</td>\n",
       "      <td>27341</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.728132</td>\n",
       "      <td>-2.500690</td>\n",
       "      <td>-7.056824</td>\n",
       "      <td>-3.904217</td>\n",
       "      <td>-10.543299</td>\n",
       "      <td>-4.874741</td>\n",
       "      <td>-2.758113</td>\n",
       "      <td>-7.167664</td>\n",
       "      <td>-3.978583</td>\n",
       "      <td>-10.543299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Bibb County</td>\n",
       "      <td>1</td>\n",
       "      <td>22919</td>\n",
       "      <td>22861</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.527043</td>\n",
       "      <td>-5.068871</td>\n",
       "      <td>-6.201001</td>\n",
       "      <td>-0.177537</td>\n",
       "      <td>0.177258</td>\n",
       "      <td>-5.088389</td>\n",
       "      <td>-4.363636</td>\n",
       "      <td>-5.403729</td>\n",
       "      <td>0.754533</td>\n",
       "      <td>1.107861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Blount County</td>\n",
       "      <td>1</td>\n",
       "      <td>57322</td>\n",
       "      <td>57373</td>\n",
       "      <td>...</td>\n",
       "      <td>1.807375</td>\n",
       "      <td>-1.177622</td>\n",
       "      <td>-1.748766</td>\n",
       "      <td>-2.062535</td>\n",
       "      <td>-1.369970</td>\n",
       "      <td>1.859511</td>\n",
       "      <td>-0.848580</td>\n",
       "      <td>-1.402476</td>\n",
       "      <td>-1.577232</td>\n",
       "      <td>-0.884411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Bullock County</td>\n",
       "      <td>1</td>\n",
       "      <td>10915</td>\n",
       "      <td>10887</td>\n",
       "      <td>...</td>\n",
       "      <td>-30.953709</td>\n",
       "      <td>-5.180127</td>\n",
       "      <td>-1.130263</td>\n",
       "      <td>14.354290</td>\n",
       "      <td>-16.167247</td>\n",
       "      <td>-29.001673</td>\n",
       "      <td>-2.825524</td>\n",
       "      <td>1.507017</td>\n",
       "      <td>17.243790</td>\n",
       "      <td>-13.193961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Butler County</td>\n",
       "      <td>1</td>\n",
       "      <td>20946</td>\n",
       "      <td>20944</td>\n",
       "      <td>...</td>\n",
       "      <td>-14.032727</td>\n",
       "      <td>-11.684234</td>\n",
       "      <td>-5.655413</td>\n",
       "      <td>1.085428</td>\n",
       "      <td>-6.529805</td>\n",
       "      <td>-13.936612</td>\n",
       "      <td>-11.586865</td>\n",
       "      <td>-5.557058</td>\n",
       "      <td>1.184103</td>\n",
       "      <td>-6.430868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Calhoun County</td>\n",
       "      <td>1</td>\n",
       "      <td>118586</td>\n",
       "      <td>118437</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.155670</td>\n",
       "      <td>-4.611706</td>\n",
       "      <td>-5.524649</td>\n",
       "      <td>-4.463211</td>\n",
       "      <td>-3.376322</td>\n",
       "      <td>-5.791579</td>\n",
       "      <td>-4.092677</td>\n",
       "      <td>-5.062836</td>\n",
       "      <td>-3.912834</td>\n",
       "      <td>-2.806406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Chambers County</td>\n",
       "      <td>1</td>\n",
       "      <td>34170</td>\n",
       "      <td>34098</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.731639</td>\n",
       "      <td>3.849092</td>\n",
       "      <td>2.872721</td>\n",
       "      <td>-2.287222</td>\n",
       "      <td>1.349468</td>\n",
       "      <td>-1.821092</td>\n",
       "      <td>4.701181</td>\n",
       "      <td>3.781439</td>\n",
       "      <td>-1.290228</td>\n",
       "      <td>2.346901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Cherokee County</td>\n",
       "      <td>1</td>\n",
       "      <td>25986</td>\n",
       "      <td>25976</td>\n",
       "      <td>...</td>\n",
       "      <td>6.339327</td>\n",
       "      <td>1.113180</td>\n",
       "      <td>5.488706</td>\n",
       "      <td>-0.076806</td>\n",
       "      <td>-3.239866</td>\n",
       "      <td>6.416167</td>\n",
       "      <td>1.420264</td>\n",
       "      <td>5.757384</td>\n",
       "      <td>0.230419</td>\n",
       "      <td>-2.931307</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    SUMLEV  REGION  DIVISION  STATE  COUNTY   STNAME          CTYNAME  \\\n",
       "1       50       3         6      1       1  Alabama   Autauga County   \n",
       "2       50       3         6      1       3  Alabama   Baldwin County   \n",
       "3       50       3         6      1       5  Alabama   Barbour County   \n",
       "4       50       3         6      1       7  Alabama      Bibb County   \n",
       "5       50       3         6      1       9  Alabama    Blount County   \n",
       "6       50       3         6      1      11  Alabama   Bullock County   \n",
       "7       50       3         6      1      13  Alabama    Butler County   \n",
       "8       50       3         6      1      15  Alabama   Calhoun County   \n",
       "9       50       3         6      1      17  Alabama  Chambers County   \n",
       "10      50       3         6      1      19  Alabama  Cherokee County   \n",
       "\n",
       "    CENSUS2010POP  ESTIMATESBASE2010  POPESTIMATE2010  ...  RDOMESTICMIG2011  \\\n",
       "1               1              54571            54660  ...          7.242091   \n",
       "2               1             182265           183193  ...         14.832960   \n",
       "3               1              27457            27341  ...         -4.728132   \n",
       "4               1              22919            22861  ...         -5.527043   \n",
       "5               1              57322            57373  ...          1.807375   \n",
       "6               1              10915            10887  ...        -30.953709   \n",
       "7               1              20946            20944  ...        -14.032727   \n",
       "8               1             118586           118437  ...         -6.155670   \n",
       "9               1              34170            34098  ...         -2.731639   \n",
       "10              1              25986            25976  ...          6.339327   \n",
       "\n",
       "    RDOMESTICMIG2012  RDOMESTICMIG2013  RDOMESTICMIG2014  RDOMESTICMIG2015  \\\n",
       "1          -2.915927         -3.012349          2.265971         -2.530799   \n",
       "2          17.647293         21.845705         19.243287         17.197872   \n",
       "3          -2.500690         -7.056824         -3.904217        -10.543299   \n",
       "4          -5.068871         -6.201001         -0.177537          0.177258   \n",
       "5          -1.177622         -1.748766         -2.062535         -1.369970   \n",
       "6          -5.180127         -1.130263         14.354290        -16.167247   \n",
       "7         -11.684234         -5.655413          1.085428         -6.529805   \n",
       "8          -4.611706         -5.524649         -4.463211         -3.376322   \n",
       "9           3.849092          2.872721         -2.287222          1.349468   \n",
       "10          1.113180          5.488706         -0.076806         -3.239866   \n",
       "\n",
       "    RNETMIG2011  RNETMIG2012  RNETMIG2013  RNETMIG2014  RNETMIG2015  \n",
       "1      7.606016    -2.626146    -2.722002     2.592270    -2.187333  \n",
       "2     15.844176    18.559627    22.727626    20.317142    18.293499  \n",
       "3     -4.874741    -2.758113    -7.167664    -3.978583   -10.543299  \n",
       "4     -5.088389    -4.363636    -5.403729     0.754533     1.107861  \n",
       "5      1.859511    -0.848580    -1.402476    -1.577232    -0.884411  \n",
       "6    -29.001673    -2.825524     1.507017    17.243790   -13.193961  \n",
       "7    -13.936612   -11.586865    -5.557058     1.184103    -6.430868  \n",
       "8     -5.791579    -4.092677    -5.062836    -3.912834    -2.806406  \n",
       "9     -1.821092     4.701181     3.781439    -1.290228     2.346901  \n",
       "10     6.416167     1.420264     5.757384     0.230419    -2.931307  \n",
       "\n",
       "[10 rows x 100 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = df2.groupby('STNAME').agg({'CENSUS2010POP': np.sum})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3142"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(df3['CENSUS2010POP'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: using a dict on a Series for aggregation\n",
      "is deprecated and will be removed in a future version. Use                 named aggregation instead.\n",
      "\n",
      "    >>> grouper.agg(name_1=func_1, name_2=func_2)\n",
      "\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>avg</th>\n",
       "      <th>sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STNAME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>1</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>1</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>1</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>1</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>1</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawaii</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>1</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>1</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>1</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>1</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>1</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>1</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>1</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>1</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>1</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>1</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>1</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>1</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>1</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>1</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>1</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>1</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>1</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>1</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>1</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>1</td>\n",
       "      <td>254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>1</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>1</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyoming</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      avg  sum\n",
       "STNAME                        \n",
       "Alabama                 1   67\n",
       "Alaska                  1   29\n",
       "Arizona                 1   15\n",
       "Arkansas                1   75\n",
       "California              1   58\n",
       "Colorado                1   64\n",
       "Connecticut             1    8\n",
       "Delaware                1    3\n",
       "District of Columbia    1    1\n",
       "Florida                 1   67\n",
       "Georgia                 1  159\n",
       "Hawaii                  1    5\n",
       "Idaho                   1   44\n",
       "Illinois                1  102\n",
       "Indiana                 1   92\n",
       "Iowa                    1   99\n",
       "Kansas                  1  105\n",
       "Kentucky                1  120\n",
       "Louisiana               1   64\n",
       "Maine                   1   16\n",
       "Maryland                1   24\n",
       "Massachusetts           1   14\n",
       "Michigan                1   83\n",
       "Minnesota               1   87\n",
       "Mississippi             1   82\n",
       "Missouri                1  115\n",
       "Montana                 1   56\n",
       "Nebraska                1   93\n",
       "Nevada                  1   17\n",
       "New Hampshire           1   10\n",
       "New Jersey              1   21\n",
       "New Mexico              1   33\n",
       "New York                1   62\n",
       "North Carolina          1  100\n",
       "North Dakota            1   53\n",
       "Ohio                    1   88\n",
       "Oklahoma                1   77\n",
       "Oregon                  1   36\n",
       "Pennsylvania            1   67\n",
       "Rhode Island            1    5\n",
       "South Carolina          1   46\n",
       "South Dakota            1   66\n",
       "Tennessee               1   95\n",
       "Texas                   1  254\n",
       "Utah                    1   29\n",
       "Vermont                 1   14\n",
       "Virginia                1  133\n",
       "Washington              1   39\n",
       "West Virginia           1   55\n",
       "Wisconsin               1   72\n",
       "Wyoming                 1   23"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.set_index('STNAME').groupby(level=0)['CENSUS2010POP']\n",
    "    .agg({'avg': np.average, 'sum': np.sum}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            0\n",
      "excellent  A+\n",
      "excellent   A\n",
      "excellent  A-\n",
      "good       B+\n",
      "good        B\n",
      "good       B-\n",
      "ok         C+\n",
      "ok          C\n",
      "ok         C-\n",
      "poor       D+\n",
      "poor        D\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Grades</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>excellent</th>\n",
       "      <td>A+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>excellent</th>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>excellent</th>\n",
       "      <td>A-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>good</th>\n",
       "      <td>B+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>good</th>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>good</th>\n",
       "      <td>B-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ok</th>\n",
       "      <td>C+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ok</th>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ok</th>\n",
       "      <td>C-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>poor</th>\n",
       "      <td>D+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>poor</th>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Grades\n",
       "excellent     A+\n",
       "excellent      A\n",
       "excellent     A-\n",
       "good          B+\n",
       "good           B\n",
       "good          B-\n",
       "ok            C+\n",
       "ok             C\n",
       "ok            C-\n",
       "poor          D+\n",
       "poor           D"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(['A+', 'A', 'A-', 'B+', 'B', 'B-', 'C+', 'C', 'C-', 'D+', 'D'],\n",
    "                  index=['excellent', 'excellent', 'excellent', 'good', 'good', 'good', 'ok', 'ok', 'ok', 'poor', 'poor'])\n",
    "print(df)\n",
    "df.rename(columns={0: 'Grades'}, inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "excellent    A+\n",
       "excellent     A\n",
       "excellent    A-\n",
       "good         B+\n",
       "good          B\n",
       "Name: Grades, dtype: category\n",
       "Categories (11, object): [A, A+, A-, B, ..., C+, C-, D, D+]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Grades'].astype('category').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "excellent    A+\n",
       "excellent     A\n",
       "excellent    A-\n",
       "good         B+\n",
       "good          B\n",
       "good         B-\n",
       "ok           C+\n",
       "ok            C\n",
       "ok           C-\n",
       "poor         D+\n",
       "poor          D\n",
       "Name: Grades, dtype: category\n",
       "Categories (11, object): [A, A+, A-, B, ..., C+, C-, D, D+]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Grades'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.api.types import CategoricalDtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "excellent    A+\n",
       "excellent     A\n",
       "excellent    A-\n",
       "good         B+\n",
       "good          B\n",
       "Name: Grades, dtype: category\n",
       "Categories (11, object): [D < D+ < C- < C ... B+ < A- < A < A+]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "\n",
    "cat_type = CategoricalDtype(categories=['D', 'D+', 'C-', 'C', 'C+', 'B-', 'B', 'B+', 'A-', 'A', 'A+'],\n",
    "                             ordered=True)\n",
    "grades = df['Grades'].astype(cat_type)\n",
    "grades.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "excellent     True\n",
       "excellent     True\n",
       "excellent     True\n",
       "good          True\n",
       "good          True\n",
       "good          True\n",
       "ok            True\n",
       "ok           False\n",
       "ok           False\n",
       "poor         False\n",
       "poor         False\n",
       "Name: Grades, dtype: bool"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grades > 'C'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/site-packages/ipykernel_launcher.py:3: FutureWarning: using a dict on a Series for aggregation\n",
      "is deprecated and will be removed in a future version. Use                 named aggregation instead.\n",
      "\n",
      "    >>> grouper.agg(name_1=func_1, name_2=func_2)\n",
      "\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "STNAME\n",
       "Alabama                   (11706.087, 75333.413]\n",
       "Alaska                    (11706.087, 75333.413]\n",
       "Arizona                 (390320.176, 453317.529]\n",
       "Arkansas                  (11706.087, 75333.413]\n",
       "California              (579312.234, 642309.586]\n",
       "Colorado                 (75333.413, 138330.766]\n",
       "Connecticut             (390320.176, 453317.529]\n",
       "Delaware                (264325.471, 327322.823]\n",
       "District of Columbia    (579312.234, 642309.586]\n",
       "Florida                 (264325.471, 327322.823]\n",
       "Georgia                   (11706.087, 75333.413]\n",
       "Hawaii                  (264325.471, 327322.823]\n",
       "Idaho                     (11706.087, 75333.413]\n",
       "Illinois                 (75333.413, 138330.766]\n",
       "Indiana                   (11706.087, 75333.413]\n",
       "Iowa                      (11706.087, 75333.413]\n",
       "Kansas                    (11706.087, 75333.413]\n",
       "Kentucky                  (11706.087, 75333.413]\n",
       "Louisiana                 (11706.087, 75333.413]\n",
       "Maine                    (75333.413, 138330.766]\n",
       "Maryland                (201328.118, 264325.471]\n",
       "Massachusetts           (453317.529, 516314.881]\n",
       "Michigan                 (75333.413, 138330.766]\n",
       "Minnesota                 (11706.087, 75333.413]\n",
       "Mississippi               (11706.087, 75333.413]\n",
       "Missouri                  (11706.087, 75333.413]\n",
       "Montana                   (11706.087, 75333.413]\n",
       "Nebraska                  (11706.087, 75333.413]\n",
       "Nevada                  (138330.766, 201328.118]\n",
       "New Hampshire            (75333.413, 138330.766]\n",
       "New Jersey              (390320.176, 453317.529]\n",
       "New Mexico                (11706.087, 75333.413]\n",
       "New York                (264325.471, 327322.823]\n",
       "North Carolina           (75333.413, 138330.766]\n",
       "North Dakota              (11706.087, 75333.413]\n",
       "Ohio                     (75333.413, 138330.766]\n",
       "Oklahoma                  (11706.087, 75333.413]\n",
       "Oregon                   (75333.413, 138330.766]\n",
       "Pennsylvania            (138330.766, 201328.118]\n",
       "Rhode Island            (201328.118, 264325.471]\n",
       "South Carolina           (75333.413, 138330.766]\n",
       "South Dakota              (11706.087, 75333.413]\n",
       "Tennessee                 (11706.087, 75333.413]\n",
       "Texas                    (75333.413, 138330.766]\n",
       "Utah                     (75333.413, 138330.766]\n",
       "Vermont                   (11706.087, 75333.413]\n",
       "Virginia                  (11706.087, 75333.413]\n",
       "Washington              (138330.766, 201328.118]\n",
       "West Virginia             (11706.087, 75333.413]\n",
       "Wisconsin                (75333.413, 138330.766]\n",
       "Wyoming                   (11706.087, 75333.413]\n",
       "Name: avg, dtype: category\n",
       "Categories (10, interval[float64]): [(11706.087, 75333.413] < (75333.413, 138330.766] < (138330.766, 201328.118] < (201328.118, 264325.471] ... (390320.176, 453317.529] < (453317.529, 516314.881] < (516314.881, 579312.234] < (579312.234, 642309.586]]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/census.csv')\n",
    "df = df[df['SUMLEV']==50]\n",
    "df = df.set_index('STNAME').groupby(level=0)['CENSUS2010POP'].agg({'avg': np.average})\n",
    "pd.cut(df['avg'],10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pivot Tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/cars.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YEAR</th>\n",
       "      <th>Make</th>\n",
       "      <th>Model</th>\n",
       "      <th>Size</th>\n",
       "      <th>(kW)</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>CITY (kWh/100 km)</th>\n",
       "      <th>HWY (kWh/100 km)</th>\n",
       "      <th>COMB (kWh/100 km)</th>\n",
       "      <th>CITY (Le/100 km)</th>\n",
       "      <th>HWY (Le/100 km)</th>\n",
       "      <th>COMB (Le/100 km)</th>\n",
       "      <th>(g/km)</th>\n",
       "      <th>RATING</th>\n",
       "      <th>(km)</th>\n",
       "      <th>TIME (h)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012</td>\n",
       "      <td>MITSUBISHI</td>\n",
       "      <td>i-MiEV</td>\n",
       "      <td>SUBCOMPACT</td>\n",
       "      <td>49</td>\n",
       "      <td>A1</td>\n",
       "      <td>B</td>\n",
       "      <td>16.9</td>\n",
       "      <td>21.4</td>\n",
       "      <td>18.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>LEAF</td>\n",
       "      <td>MID-SIZE</td>\n",
       "      <td>80</td>\n",
       "      <td>A1</td>\n",
       "      <td>B</td>\n",
       "      <td>19.3</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>117</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>FORD</td>\n",
       "      <td>FOCUS ELECTRIC</td>\n",
       "      <td>COMPACT</td>\n",
       "      <td>107</td>\n",
       "      <td>A1</td>\n",
       "      <td>B</td>\n",
       "      <td>19.0</td>\n",
       "      <td>21.1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>122</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>MITSUBISHI</td>\n",
       "      <td>i-MiEV</td>\n",
       "      <td>SUBCOMPACT</td>\n",
       "      <td>49</td>\n",
       "      <td>A1</td>\n",
       "      <td>B</td>\n",
       "      <td>16.9</td>\n",
       "      <td>21.4</td>\n",
       "      <td>18.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>LEAF</td>\n",
       "      <td>MID-SIZE</td>\n",
       "      <td>80</td>\n",
       "      <td>A1</td>\n",
       "      <td>B</td>\n",
       "      <td>19.3</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>117</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   YEAR        Make           Model        Size  (kW) Unnamed: 5 TYPE  \\\n",
       "0  2012  MITSUBISHI          i-MiEV  SUBCOMPACT    49         A1    B   \n",
       "1  2012      NISSAN            LEAF    MID-SIZE    80         A1    B   \n",
       "2  2013        FORD  FOCUS ELECTRIC     COMPACT   107         A1    B   \n",
       "3  2013  MITSUBISHI          i-MiEV  SUBCOMPACT    49         A1    B   \n",
       "4  2013      NISSAN            LEAF    MID-SIZE    80         A1    B   \n",
       "\n",
       "   CITY (kWh/100 km)  HWY (kWh/100 km)  COMB (kWh/100 km)  CITY (Le/100 km)  \\\n",
       "0               16.9              21.4               18.7               1.9   \n",
       "1               19.3              23.0               21.1               2.2   \n",
       "2               19.0              21.1               20.0               2.1   \n",
       "3               16.9              21.4               18.7               1.9   \n",
       "4               19.3              23.0               21.1               2.2   \n",
       "\n",
       "   HWY (Le/100 km)  COMB (Le/100 km)  (g/km)  RATING  (km)  TIME (h)  \n",
       "0              2.4               2.1       0     NaN   100         7  \n",
       "1              2.6               2.4       0     NaN   117         7  \n",
       "2              2.4               2.2       0     NaN   122         4  \n",
       "3              2.4               2.1       0     NaN   100         7  \n",
       "4              2.6               2.4       0     NaN   117         7  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Make</th>\n",
       "      <th>BMW</th>\n",
       "      <th>CHEVROLET</th>\n",
       "      <th>FORD</th>\n",
       "      <th>KIA</th>\n",
       "      <th>MITSUBISHI</th>\n",
       "      <th>NISSAN</th>\n",
       "      <th>SMART</th>\n",
       "      <th>TESLA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YEAR</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>280.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>NaN</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>268.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>125.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>320.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>125.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>409.700000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Make    BMW  CHEVROLET   FORD   KIA  MITSUBISHI  NISSAN  SMART       TESLA\n",
       "YEAR                                                                      \n",
       "2012    NaN        NaN    NaN   NaN        49.0    80.0    NaN         NaN\n",
       "2013    NaN        NaN  107.0   NaN        49.0    80.0   35.0  280.000000\n",
       "2014    NaN      104.0  107.0   NaN        49.0    80.0   35.0  268.333333\n",
       "2015  125.0      104.0  107.0  81.0        49.0    80.0   35.0  320.666667\n",
       "2016  125.0      104.0  107.0  81.0        49.0    80.0   35.0  409.700000"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.pivot_table(values='(kW)', index='YEAR', columns='Make', aggfunc=np.mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"9\" halign=\"left\">mean</th>\n",
       "      <th colspan=\"9\" halign=\"left\">amin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Make</th>\n",
       "      <th>BMW</th>\n",
       "      <th>CHEVROLET</th>\n",
       "      <th>FORD</th>\n",
       "      <th>KIA</th>\n",
       "      <th>MITSUBISHI</th>\n",
       "      <th>NISSAN</th>\n",
       "      <th>SMART</th>\n",
       "      <th>TESLA</th>\n",
       "      <th>All</th>\n",
       "      <th>BMW</th>\n",
       "      <th>CHEVROLET</th>\n",
       "      <th>FORD</th>\n",
       "      <th>KIA</th>\n",
       "      <th>MITSUBISHI</th>\n",
       "      <th>NISSAN</th>\n",
       "      <th>SMART</th>\n",
       "      <th>TESLA</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YEAR</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>158.444444</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>NaN</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>268.333333</td>\n",
       "      <td>135.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>125.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>320.666667</td>\n",
       "      <td>181.428571</td>\n",
       "      <td>125.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>125.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>409.700000</td>\n",
       "      <td>252.263158</td>\n",
       "      <td>125.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>283.0</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>125.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>345.478261</td>\n",
       "      <td>190.622642</td>\n",
       "      <td>125.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       mean                                                             \\\n",
       "Make    BMW CHEVROLET   FORD   KIA MITSUBISHI NISSAN SMART       TESLA   \n",
       "YEAR                                                                     \n",
       "2012    NaN       NaN    NaN   NaN       49.0   80.0   NaN         NaN   \n",
       "2013    NaN       NaN  107.0   NaN       49.0   80.0  35.0  280.000000   \n",
       "2014    NaN     104.0  107.0   NaN       49.0   80.0  35.0  268.333333   \n",
       "2015  125.0     104.0  107.0  81.0       49.0   80.0  35.0  320.666667   \n",
       "2016  125.0     104.0  107.0  81.0       49.0   80.0  35.0  409.700000   \n",
       "All   125.0     104.0  107.0  81.0       49.0   80.0  35.0  345.478261   \n",
       "\n",
       "                   amin                                                        \\\n",
       "Make         All    BMW CHEVROLET   FORD   KIA MITSUBISHI NISSAN SMART  TESLA   \n",
       "YEAR                                                                            \n",
       "2012   64.500000    NaN       NaN    NaN   NaN       49.0   80.0   NaN    NaN   \n",
       "2013  158.444444    NaN       NaN  107.0   NaN       49.0   80.0  35.0  270.0   \n",
       "2014  135.000000    NaN     104.0  107.0   NaN       49.0   80.0  35.0  225.0   \n",
       "2015  181.428571  125.0     104.0  107.0  81.0       49.0   80.0  35.0  280.0   \n",
       "2016  252.263158  125.0     104.0  107.0  81.0       49.0   80.0  35.0  283.0   \n",
       "All   190.622642  125.0     104.0  107.0  81.0       49.0   80.0  35.0  225.0   \n",
       "\n",
       "          \n",
       "Make All  \n",
       "YEAR      \n",
       "2012  49  \n",
       "2013  35  \n",
       "2014  35  \n",
       "2015  35  \n",
       "2016  35  \n",
       "All   35  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.pivot_table(values='(kW)', index='YEAR', columns='Make', aggfunc=[np.mean,np.min], margins=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Date Functionality in Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2016-09-01 10:05:00')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timestamp('9/1/2016 10:05AM')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Period('2016-01', 'M')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Period('1/2016')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Period('2016-03-05', 'D')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Period('3/5/2016')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DatetimeIndex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2016-09-01    a\n",
       "2016-09-02    b\n",
       "2016-09-03    c\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1 = pd.Series(list('abc'), [pd.Timestamp('2016-09-01'), pd.Timestamp('2016-09-02'), pd.Timestamp('2016-09-03')])\n",
    "t1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.datetimes.DatetimeIndex"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(t1.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### PeriodIndex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2016-09    d\n",
       "2016-10    e\n",
       "2016-11    f\n",
       "Freq: M, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t2 = pd.Series(list('def'), [pd.Period('2016-09'), pd.Period('2016-10'), pd.Period('2016-11')])\n",
    "t2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.period.PeriodIndex"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(t2.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2 June 2013</th>\n",
       "      <td>66</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aug 29, 2014</th>\n",
       "      <td>75</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-26</th>\n",
       "      <td>26</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/12/16</th>\n",
       "      <td>16</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               a   b\n",
       "2 June 2013   66  36\n",
       "Aug 29, 2014  75  87\n",
       "2015-06-26    26  87\n",
       "7/12/16       16  15"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Converting to Datetime\n",
    "\n",
    "d1 = ['2 June 2013', 'Aug 29, 2014', '2015-06-26', '7/12/16']\n",
    "ts3 = pd.DataFrame(np.random.randint(10, 100, (4,2)), index=d1, columns=list('ab'))\n",
    "ts3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-06-02</th>\n",
       "      <td>66</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>75</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-26</th>\n",
       "      <td>26</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-07</th>\n",
       "      <td>16</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             a   b\n",
       "2013-06-02  66  36\n",
       "2014-08-29  75  87\n",
       "2015-06-26  26  87\n",
       "2016-12-07  16  15"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts3.index = pd.to_datetime(ts3.index, dayfirst=True)\n",
    "ts3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2012-07-04 00:00:00')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_datetime('4.7.12', dayfirst=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('2 days 00:00:00')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Timedeltas\n",
    "pd.Timestamp('9/3/2016')-pd.Timestamp('9/1/2016')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2016-09-14 11:10:00')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Timestamp('9/2/2016 8:10AM') + pd.Timedelta('12D 3H')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working with Dates in a Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2020-01-05', '2020-01-19', '2020-02-02', '2020-02-16',\n",
       "               '2020-03-01', '2020-03-15', '2020-03-29', '2020-04-12',\n",
       "               '2020-04-26'],\n",
       "              dtype='datetime64[ns]', freq='2W-SUN')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates = pd.date_range('01-01-2020', periods=9, freq='2W-SUN')\n",
    "dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count 1</th>\n",
       "      <th>Count 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-19</th>\n",
       "      <td>105</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-02</th>\n",
       "      <td>100</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-16</th>\n",
       "      <td>106</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-01</th>\n",
       "      <td>108</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-15</th>\n",
       "      <td>107</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-29</th>\n",
       "      <td>116</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-12</th>\n",
       "      <td>119</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-26</th>\n",
       "      <td>116</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Count 1  Count 2\n",
       "2020-01-05      100      123\n",
       "2020-01-19      105      121\n",
       "2020-02-02      100      127\n",
       "2020-02-16      106      121\n",
       "2020-03-01      108      115\n",
       "2020-03-15      107      129\n",
       "2020-03-29      116      115\n",
       "2020-04-12      119      129\n",
       "2020-04-26      116      126"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({'Count 1': 100 + np.random.randint(-5, 10, 9).cumsum(),\n",
    "                  'Count 2': 120 + np.random.randint(-5, 10, 9)}, index=dates)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Sunday', 'Sunday', 'Sunday', 'Sunday', 'Sunday', 'Sunday', 'Sunday',\n",
       "       'Sunday', 'Sunday'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index.weekday_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count 1</th>\n",
       "      <th>Count 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-19</th>\n",
       "      <td>5.0</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-02</th>\n",
       "      <td>-5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-16</th>\n",
       "      <td>6.0</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-01</th>\n",
       "      <td>2.0</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-15</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-29</th>\n",
       "      <td>9.0</td>\n",
       "      <td>-14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-12</th>\n",
       "      <td>3.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-26</th>\n",
       "      <td>-3.0</td>\n",
       "      <td>-3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Count 1  Count 2\n",
       "2020-01-05      NaN      NaN\n",
       "2020-01-19      5.0     -2.0\n",
       "2020-02-02     -5.0      6.0\n",
       "2020-02-16      6.0     -6.0\n",
       "2020-03-01      2.0     -6.0\n",
       "2020-03-15     -1.0     14.0\n",
       "2020-03-29      9.0    -14.0\n",
       "2020-04-12      3.0     14.0\n",
       "2020-04-26     -3.0     -3.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.diff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.resample.DatetimeIndexResampler object at 0x1117f65d0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('M')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count 1</th>\n",
       "      <th>Count 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-31</th>\n",
       "      <td>102.500000</td>\n",
       "      <td>122.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>103.000000</td>\n",
       "      <td>124.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>110.333333</td>\n",
       "      <td>119.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-30</th>\n",
       "      <td>117.500000</td>\n",
       "      <td>127.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Count 1     Count 2\n",
       "2020-01-31  102.500000  122.000000\n",
       "2020-02-29  103.000000  124.000000\n",
       "2020-03-31  110.333333  119.666667\n",
       "2020-04-30  117.500000  127.500000"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('M').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count 1</th>\n",
       "      <th>Count 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-19</th>\n",
       "      <td>105</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-02</th>\n",
       "      <td>100</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-16</th>\n",
       "      <td>106</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-01</th>\n",
       "      <td>108</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-15</th>\n",
       "      <td>107</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-29</th>\n",
       "      <td>116</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-12</th>\n",
       "      <td>119</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-26</th>\n",
       "      <td>116</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Count 1  Count 2\n",
       "2020-01-05      100      123\n",
       "2020-01-19      105      121\n",
       "2020-02-02      100      127\n",
       "2020-02-16      106      121\n",
       "2020-03-01      108      115\n",
       "2020-03-15      107      129\n",
       "2020-03-29      116      115\n",
       "2020-04-12      119      129\n",
       "2020-04-26      116      126"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count 1</th>\n",
       "      <th>Count 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-04-12</th>\n",
       "      <td>119</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-26</th>\n",
       "      <td>116</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Count 1  Count 2\n",
       "2020-04-12      119      129\n",
       "2020-04-26      116      126"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['2020-04']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count 1</th>\n",
       "      <th>Count 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-05</th>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-12</th>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-19</th>\n",
       "      <td>105</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-26</th>\n",
       "      <td>105</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-02</th>\n",
       "      <td>100</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-09</th>\n",
       "      <td>100</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-16</th>\n",
       "      <td>106</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-23</th>\n",
       "      <td>106</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-01</th>\n",
       "      <td>108</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-08</th>\n",
       "      <td>108</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-15</th>\n",
       "      <td>107</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-22</th>\n",
       "      <td>107</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-29</th>\n",
       "      <td>116</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-05</th>\n",
       "      <td>116</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-12</th>\n",
       "      <td>119</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-19</th>\n",
       "      <td>119</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-26</th>\n",
       "      <td>116</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Count 1  Count 2\n",
       "2020-01-05      100      123\n",
       "2020-01-12      100      123\n",
       "2020-01-19      105      121\n",
       "2020-01-26      105      121\n",
       "2020-02-02      100      127\n",
       "2020-02-09      100      127\n",
       "2020-02-16      106      121\n",
       "2020-02-23      106      121\n",
       "2020-03-01      108      115\n",
       "2020-03-08      108      115\n",
       "2020-03-15      107      129\n",
       "2020-03-22      107      129\n",
       "2020-03-29      116      115\n",
       "2020-04-05      116      115\n",
       "2020-04-12      119      129\n",
       "2020-04-19      119      129\n",
       "2020-04-26      116      126"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.asfreq('W', method='ffill')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1120ff550>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "df.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}