{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Aggregate Functions and Group Statistics\n",
    "* Contact: Lachlan Deer, [econgit] @ldeer, [github/twitter] @lachlandeer\n",
    "\n",
    "So far our work with Pandas as been purely about simple transformations of each row or data; whether selecting them or creating new columns out of old ones. This is rarely enough - we typically want some degree of summarization of the data; either of an entire column; or on parts of (groups) of the column in question.\n",
    "\n",
    "This is what we will go after here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv('out_data/state_labour_statistics.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Aggregation\n",
    "\n",
    "Like NumPy, Pandas has some of the standard data aggregations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.618795\n",
       "1    0.591624\n",
       "2    0.888684\n",
       "3    0.891655\n",
       "4    0.457567\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rng = np.random.RandomState(1234567890)\n",
    "series = pd.Series(rng.rand(5))\n",
    "series\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.4483242705353976"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.6896648541070796, 0.61879477158568, 0.89165480011560816)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series.mean(), series.median(), series.max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For a data-frame; these aggregations return results for each column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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>0</th>\n",
       "      <td>0.778188</td>\n",
       "      <td>0.400999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.267064</td>\n",
       "      <td>0.705406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.996106</td>\n",
       "      <td>0.405186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.540095</td>\n",
       "      <td>0.949991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.537522</td>\n",
       "      <td>0.030754</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B\n",
       "0  0.778188  0.400999\n",
       "1  0.267064  0.705406\n",
       "2  0.996106  0.405186\n",
       "3  0.540095  0.949991\n",
       "4  0.537522  0.030754"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame({'A': rng.rand(5),\n",
    "                   'B': rng.rand(5)})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    0.623795\n",
       "B    0.498467\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "if you want the aggregation across a row, you can specify thats what you want:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.589594\n",
       "1    0.486235\n",
       "2    0.700646\n",
       "3    0.745043\n",
       "4    0.284138\n",
       "dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mean(axis='columns')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Often times, we want to see all of the common aggregates at once. Pandas provides a function `.describe()` to do this for us:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>unemployment_rate</th>\n",
       "      <th>qty_unemployed</th>\n",
       "      <th>qty_employed</th>\n",
       "      <th>labour_force</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10608.00000</td>\n",
       "      <td>10608.000000</td>\n",
       "      <td>1.060800e+04</td>\n",
       "      <td>1.060800e+04</td>\n",
       "      <td>1.060800e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2008.00000</td>\n",
       "      <td>5.943194</td>\n",
       "      <td>1.849809e+05</td>\n",
       "      <td>2.751157e+06</td>\n",
       "      <td>2.936138e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.89921</td>\n",
       "      <td>2.261388</td>\n",
       "      <td>2.433025e+05</td>\n",
       "      <td>3.021023e+06</td>\n",
       "      <td>3.242657e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2000.00000</td>\n",
       "      <td>1.700000</td>\n",
       "      <td>6.697000e+03</td>\n",
       "      <td>2.486420e+05</td>\n",
       "      <td>2.619910e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2004.00000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>4.088675e+04</td>\n",
       "      <td>7.359608e+05</td>\n",
       "      <td>7.836765e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2008.00000</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>1.150930e+05</td>\n",
       "      <td>1.837300e+06</td>\n",
       "      <td>1.961558e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2012.00000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>2.212182e+05</td>\n",
       "      <td>3.226836e+06</td>\n",
       "      <td>3.451084e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2016.00000</td>\n",
       "      <td>17.300000</td>\n",
       "      <td>2.316525e+06</td>\n",
       "      <td>1.819380e+07</td>\n",
       "      <td>1.920923e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              year  unemployment_rate  qty_unemployed  qty_employed  \\\n",
       "count  10608.00000       10608.000000    1.060800e+04  1.060800e+04   \n",
       "mean    2008.00000           5.943194    1.849809e+05  2.751157e+06   \n",
       "std        4.89921           2.261388    2.433025e+05  3.021023e+06   \n",
       "min     2000.00000           1.700000    6.697000e+03  2.486420e+05   \n",
       "25%     2004.00000           4.400000    4.088675e+04  7.359608e+05   \n",
       "50%     2008.00000           5.500000    1.150930e+05  1.837300e+06   \n",
       "75%     2012.00000           7.000000    2.212182e+05  3.226836e+06   \n",
       "max     2016.00000          17.300000    2.316525e+06  1.819380e+07   \n",
       "\n",
       "       labour_force  \n",
       "count  1.060800e+04  \n",
       "mean   2.936138e+06  \n",
       "std    3.242657e+06  \n",
       "min    2.619910e+05  \n",
       "25%    7.836765e+05  \n",
       "50%    1.961558e+06  \n",
       "75%    3.451084e+06  \n",
       "max    1.920923e+07  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some useful aggregation functions in pandas are in the table below:\n",
    "\n",
    "[insert table]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Whilst these aggregations can provide some notions of patterns in the data - often we want to go deeper - and compute these summaries at the level of a group (like a state of a year). Pandas has the `groupby` function that will allow us to efficiently looks at aggregate statistics on subsets of the data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GroupBy: The Split, Apply, Combine Paradigm\n",
    "The canonical example of the groupby paradigm  is best represented in a figure:\n",
    "\n",
    "[insert figure]\n",
    "\n",
    "In words, GroupBy does the following:\n",
    "* The *split* step breaks up a DataFrame into subsets depending on the value of a specified key\n",
    "* the *apply* step computes some aggregate functions within an individual group\n",
    "* The *combine* step merges the results of the computations within groups back to a single dataset\n",
    "\n",
    "We could certainly perform all these operations by ourselves, manually - but the tedium of the task combined with a high probability of error makes us immediately want to use a built in function that abstracts away from individual steps and asks the user to rather think of the operation as a whole rather than the individual steps."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a start - let's look at the average unemployment rate by state. As a first step we must specify the name of the column we are looking to split on:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.groupby.DataFrameGroupBy object at 0x7f9deb1cd080>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('state')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Think of this object as an under the hood view of a `DataFrame`. Note that it does not compute anything until an aggregation is applied to it; i.e. it uses 'lazy evaluation'\n",
    "\n",
    "Now lets get those mena unemployment rates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state\n",
       "Alabama                  6.514706\n",
       "Alaska                   7.005392\n",
       "Arizona                  6.381373\n",
       "Arkansas                 5.997059\n",
       "California               7.443627\n",
       "Colorado                 5.453922\n",
       "Connecticut              5.821078\n",
       "Delaware                 5.214216\n",
       "District of Columbia     7.306373\n",
       "Florida                  6.158824\n",
       "Georgia                  6.446078\n",
       "Hawaii                   4.456373\n",
       "Idaho                    5.525000\n",
       "Illinois                 6.936275\n",
       "Indiana                  6.184804\n",
       "Iowa                     4.373039\n",
       "Kansas                   5.084314\n",
       "Kentucky                 6.639216\n",
       "Louisiana                6.197549\n",
       "Maine                    5.470098\n",
       "Maryland                 5.121078\n",
       "Massachusetts            5.521078\n",
       "Michigan                 7.662255\n",
       "Minnesota                4.886765\n",
       "Mississippi              7.285784\n",
       "Missouri                 6.069118\n",
       "Montana                  5.023039\n",
       "Nebraska                 3.629412\n",
       "Nevada                   7.220098\n",
       "New Hampshire            4.205882\n",
       "New Jersey               6.248039\n",
       "New Mexico               5.972059\n",
       "New York                 6.182353\n",
       "North Carolina           6.741176\n",
       "North Dakota             3.279902\n",
       "Ohio                     6.455392\n",
       "Oklahoma                 4.784804\n",
       "Oregon                   7.242647\n",
       "Pennsylvania             5.946569\n",
       "Puerto Rico             12.653922\n",
       "Rhode Island             7.000490\n",
       "South Carolina           7.130882\n",
       "South Dakota             3.579412\n",
       "Tennessee                6.369118\n",
       "Texas                    5.775000\n",
       "Utah                     4.716667\n",
       "Vermont                  4.247549\n",
       "Virginia                 4.543137\n",
       "Washington               6.706863\n",
       "West Virginia            6.168137\n",
       "Wisconsin                5.668627\n",
       "Wyoming                  4.399510\n",
       "Name: unemployment_rate, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('state').unemployment_rate.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice if we wanted the aggregation function to be applied to all of the columns, we can skip the part where we specify the column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>unemployment_rate</th>\n",
       "      <th>qty_unemployed</th>\n",
       "      <th>qty_employed</th>\n",
       "      <th>labour_force</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</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>Alabama</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.514706</td>\n",
       "      <td>1.407627e+05</td>\n",
       "      <td>2.016128e+06</td>\n",
       "      <td>2.156891e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.005392</td>\n",
       "      <td>2.449233e+04</td>\n",
       "      <td>3.251195e+05</td>\n",
       "      <td>3.496119e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.381373</td>\n",
       "      <td>1.901428e+05</td>\n",
       "      <td>2.759190e+06</td>\n",
       "      <td>2.949333e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.997059</td>\n",
       "      <td>7.955364e+04</td>\n",
       "      <td>1.244863e+06</td>\n",
       "      <td>1.324416e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.443627</td>\n",
       "      <td>1.347057e+06</td>\n",
       "      <td>1.665503e+07</td>\n",
       "      <td>1.800209e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.453922</td>\n",
       "      <td>1.452646e+05</td>\n",
       "      <td>2.503614e+06</td>\n",
       "      <td>2.648878e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.821078</td>\n",
       "      <td>1.082514e+05</td>\n",
       "      <td>1.736436e+06</td>\n",
       "      <td>1.844688e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.214216</td>\n",
       "      <td>2.292001e+04</td>\n",
       "      <td>4.152155e+05</td>\n",
       "      <td>4.381355e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.306373</td>\n",
       "      <td>2.490122e+04</td>\n",
       "      <td>3.137833e+05</td>\n",
       "      <td>3.386846e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.158824</td>\n",
       "      <td>5.573326e+05</td>\n",
       "      <td>8.397621e+06</td>\n",
       "      <td>8.954954e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.446078</td>\n",
       "      <td>3.016779e+05</td>\n",
       "      <td>4.339163e+06</td>\n",
       "      <td>4.640840e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawaii</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.456373</td>\n",
       "      <td>2.844513e+04</td>\n",
       "      <td>6.090308e+05</td>\n",
       "      <td>6.374759e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.525000</td>\n",
       "      <td>4.104917e+04</td>\n",
       "      <td>7.013501e+05</td>\n",
       "      <td>7.423993e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.936275</td>\n",
       "      <td>4.523743e+05</td>\n",
       "      <td>6.059067e+06</td>\n",
       "      <td>6.511441e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.184804</td>\n",
       "      <td>1.977921e+05</td>\n",
       "      <td>3.002629e+06</td>\n",
       "      <td>3.200421e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.373039</td>\n",
       "      <td>7.248086e+04</td>\n",
       "      <td>1.583003e+06</td>\n",
       "      <td>1.655483e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.084314</td>\n",
       "      <td>7.486110e+04</td>\n",
       "      <td>1.394324e+06</td>\n",
       "      <td>1.469186e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.639216</td>\n",
       "      <td>1.339159e+05</td>\n",
       "      <td>1.874098e+06</td>\n",
       "      <td>2.008013e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.197549</td>\n",
       "      <td>1.283975e+05</td>\n",
       "      <td>1.938786e+06</td>\n",
       "      <td>2.067184e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.470098</td>\n",
       "      <td>3.788920e+04</td>\n",
       "      <td>6.543850e+05</td>\n",
       "      <td>6.922742e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.121078</td>\n",
       "      <td>1.548394e+05</td>\n",
       "      <td>2.847295e+06</td>\n",
       "      <td>3.002135e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.521078</td>\n",
       "      <td>1.911474e+05</td>\n",
       "      <td>3.266176e+06</td>\n",
       "      <td>3.457324e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.662255</td>\n",
       "      <td>3.749323e+05</td>\n",
       "      <td>4.543822e+06</td>\n",
       "      <td>4.918755e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.886765</td>\n",
       "      <td>1.426212e+05</td>\n",
       "      <td>2.771413e+06</td>\n",
       "      <td>2.914034e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.285784</td>\n",
       "      <td>9.449842e+04</td>\n",
       "      <td>1.201615e+06</td>\n",
       "      <td>1.296114e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.069118</td>\n",
       "      <td>1.842034e+05</td>\n",
       "      <td>2.849336e+06</td>\n",
       "      <td>3.033539e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.023039</td>\n",
       "      <td>2.489118e+04</td>\n",
       "      <td>4.706648e+05</td>\n",
       "      <td>4.955559e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>3.629412</td>\n",
       "      <td>3.576543e+04</td>\n",
       "      <td>9.494372e+05</td>\n",
       "      <td>9.852027e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.220098</td>\n",
       "      <td>9.513693e+04</td>\n",
       "      <td>1.193879e+06</td>\n",
       "      <td>1.289016e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.205882</td>\n",
       "      <td>3.072605e+04</td>\n",
       "      <td>6.977644e+05</td>\n",
       "      <td>7.284904e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.248039</td>\n",
       "      <td>2.798071e+05</td>\n",
       "      <td>4.176598e+06</td>\n",
       "      <td>4.456405e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.972059</td>\n",
       "      <td>5.465965e+04</td>\n",
       "      <td>8.586955e+05</td>\n",
       "      <td>9.133552e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.182353</td>\n",
       "      <td>5.869909e+05</td>\n",
       "      <td>8.888198e+06</td>\n",
       "      <td>9.475189e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.741176</td>\n",
       "      <td>3.046283e+05</td>\n",
       "      <td>4.188285e+06</td>\n",
       "      <td>4.492913e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>3.279902</td>\n",
       "      <td>1.220031e+04</td>\n",
       "      <td>3.621385e+05</td>\n",
       "      <td>3.743388e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.455392</td>\n",
       "      <td>3.763495e+05</td>\n",
       "      <td>5.449497e+06</td>\n",
       "      <td>5.825846e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.784804</td>\n",
       "      <td>8.368540e+04</td>\n",
       "      <td>1.661057e+06</td>\n",
       "      <td>1.744743e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.242647</td>\n",
       "      <td>1.389804e+05</td>\n",
       "      <td>1.776049e+06</td>\n",
       "      <td>1.915029e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.946569</td>\n",
       "      <td>3.771446e+05</td>\n",
       "      <td>5.952701e+06</td>\n",
       "      <td>6.329845e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>12.653922</td>\n",
       "      <td>1.603699e+05</td>\n",
       "      <td>1.112528e+06</td>\n",
       "      <td>1.272898e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.000490</td>\n",
       "      <td>3.921885e+04</td>\n",
       "      <td>5.201720e+05</td>\n",
       "      <td>5.593909e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>7.130882</td>\n",
       "      <td>1.517508e+05</td>\n",
       "      <td>1.967512e+06</td>\n",
       "      <td>2.119263e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>3.579412</td>\n",
       "      <td>1.562588e+04</td>\n",
       "      <td>4.203784e+05</td>\n",
       "      <td>4.360043e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.369118</td>\n",
       "      <td>1.926002e+05</td>\n",
       "      <td>2.816181e+06</td>\n",
       "      <td>3.008781e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.775000</td>\n",
       "      <td>6.833513e+05</td>\n",
       "      <td>1.111923e+07</td>\n",
       "      <td>1.180258e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.716667</td>\n",
       "      <td>6.224774e+04</td>\n",
       "      <td>1.261578e+06</td>\n",
       "      <td>1.323826e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.247549</td>\n",
       "      <td>1.492144e+04</td>\n",
       "      <td>3.346937e+05</td>\n",
       "      <td>3.496151e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.543137</td>\n",
       "      <td>1.844006e+05</td>\n",
       "      <td>3.830106e+06</td>\n",
       "      <td>4.014506e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.706863</td>\n",
       "      <td>2.257521e+05</td>\n",
       "      <td>3.132887e+06</td>\n",
       "      <td>3.358639e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>6.168137</td>\n",
       "      <td>4.937335e+04</td>\n",
       "      <td>7.508340e+05</td>\n",
       "      <td>8.002073e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>5.668627</td>\n",
       "      <td>1.737884e+05</td>\n",
       "      <td>2.889477e+06</td>\n",
       "      <td>3.063265e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyoming</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>4.399510</td>\n",
       "      <td>1.283748e+04</td>\n",
       "      <td>2.771341e+05</td>\n",
       "      <td>2.899716e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        year  unemployment_rate  qty_unemployed  qty_employed  \\\n",
       "state                                                                           \n",
       "Alabama               2008.0           6.514706    1.407627e+05  2.016128e+06   \n",
       "Alaska                2008.0           7.005392    2.449233e+04  3.251195e+05   \n",
       "Arizona               2008.0           6.381373    1.901428e+05  2.759190e+06   \n",
       "Arkansas              2008.0           5.997059    7.955364e+04  1.244863e+06   \n",
       "California            2008.0           7.443627    1.347057e+06  1.665503e+07   \n",
       "Colorado              2008.0           5.453922    1.452646e+05  2.503614e+06   \n",
       "Connecticut           2008.0           5.821078    1.082514e+05  1.736436e+06   \n",
       "Delaware              2008.0           5.214216    2.292001e+04  4.152155e+05   \n",
       "District of Columbia  2008.0           7.306373    2.490122e+04  3.137833e+05   \n",
       "Florida               2008.0           6.158824    5.573326e+05  8.397621e+06   \n",
       "Georgia               2008.0           6.446078    3.016779e+05  4.339163e+06   \n",
       "Hawaii                2008.0           4.456373    2.844513e+04  6.090308e+05   \n",
       "Idaho                 2008.0           5.525000    4.104917e+04  7.013501e+05   \n",
       "Illinois              2008.0           6.936275    4.523743e+05  6.059067e+06   \n",
       "Indiana               2008.0           6.184804    1.977921e+05  3.002629e+06   \n",
       "Iowa                  2008.0           4.373039    7.248086e+04  1.583003e+06   \n",
       "Kansas                2008.0           5.084314    7.486110e+04  1.394324e+06   \n",
       "Kentucky              2008.0           6.639216    1.339159e+05  1.874098e+06   \n",
       "Louisiana             2008.0           6.197549    1.283975e+05  1.938786e+06   \n",
       "Maine                 2008.0           5.470098    3.788920e+04  6.543850e+05   \n",
       "Maryland              2008.0           5.121078    1.548394e+05  2.847295e+06   \n",
       "Massachusetts         2008.0           5.521078    1.911474e+05  3.266176e+06   \n",
       "Michigan              2008.0           7.662255    3.749323e+05  4.543822e+06   \n",
       "Minnesota             2008.0           4.886765    1.426212e+05  2.771413e+06   \n",
       "Mississippi           2008.0           7.285784    9.449842e+04  1.201615e+06   \n",
       "Missouri              2008.0           6.069118    1.842034e+05  2.849336e+06   \n",
       "Montana               2008.0           5.023039    2.489118e+04  4.706648e+05   \n",
       "Nebraska              2008.0           3.629412    3.576543e+04  9.494372e+05   \n",
       "Nevada                2008.0           7.220098    9.513693e+04  1.193879e+06   \n",
       "New Hampshire         2008.0           4.205882    3.072605e+04  6.977644e+05   \n",
       "New Jersey            2008.0           6.248039    2.798071e+05  4.176598e+06   \n",
       "New Mexico            2008.0           5.972059    5.465965e+04  8.586955e+05   \n",
       "New York              2008.0           6.182353    5.869909e+05  8.888198e+06   \n",
       "North Carolina        2008.0           6.741176    3.046283e+05  4.188285e+06   \n",
       "North Dakota          2008.0           3.279902    1.220031e+04  3.621385e+05   \n",
       "Ohio                  2008.0           6.455392    3.763495e+05  5.449497e+06   \n",
       "Oklahoma              2008.0           4.784804    8.368540e+04  1.661057e+06   \n",
       "Oregon                2008.0           7.242647    1.389804e+05  1.776049e+06   \n",
       "Pennsylvania          2008.0           5.946569    3.771446e+05  5.952701e+06   \n",
       "Puerto Rico           2008.0          12.653922    1.603699e+05  1.112528e+06   \n",
       "Rhode Island          2008.0           7.000490    3.921885e+04  5.201720e+05   \n",
       "South Carolina        2008.0           7.130882    1.517508e+05  1.967512e+06   \n",
       "South Dakota          2008.0           3.579412    1.562588e+04  4.203784e+05   \n",
       "Tennessee             2008.0           6.369118    1.926002e+05  2.816181e+06   \n",
       "Texas                 2008.0           5.775000    6.833513e+05  1.111923e+07   \n",
       "Utah                  2008.0           4.716667    6.224774e+04  1.261578e+06   \n",
       "Vermont               2008.0           4.247549    1.492144e+04  3.346937e+05   \n",
       "Virginia              2008.0           4.543137    1.844006e+05  3.830106e+06   \n",
       "Washington            2008.0           6.706863    2.257521e+05  3.132887e+06   \n",
       "West Virginia         2008.0           6.168137    4.937335e+04  7.508340e+05   \n",
       "Wisconsin             2008.0           5.668627    1.737884e+05  2.889477e+06   \n",
       "Wyoming               2008.0           4.399510    1.283748e+04  2.771341e+05   \n",
       "\n",
       "                      labour_force  \n",
       "state                               \n",
       "Alabama               2.156891e+06  \n",
       "Alaska                3.496119e+05  \n",
       "Arizona               2.949333e+06  \n",
       "Arkansas              1.324416e+06  \n",
       "California            1.800209e+07  \n",
       "Colorado              2.648878e+06  \n",
       "Connecticut           1.844688e+06  \n",
       "Delaware              4.381355e+05  \n",
       "District of Columbia  3.386846e+05  \n",
       "Florida               8.954954e+06  \n",
       "Georgia               4.640840e+06  \n",
       "Hawaii                6.374759e+05  \n",
       "Idaho                 7.423993e+05  \n",
       "Illinois              6.511441e+06  \n",
       "Indiana               3.200421e+06  \n",
       "Iowa                  1.655483e+06  \n",
       "Kansas                1.469186e+06  \n",
       "Kentucky              2.008013e+06  \n",
       "Louisiana             2.067184e+06  \n",
       "Maine                 6.922742e+05  \n",
       "Maryland              3.002135e+06  \n",
       "Massachusetts         3.457324e+06  \n",
       "Michigan              4.918755e+06  \n",
       "Minnesota             2.914034e+06  \n",
       "Mississippi           1.296114e+06  \n",
       "Missouri              3.033539e+06  \n",
       "Montana               4.955559e+05  \n",
       "Nebraska              9.852027e+05  \n",
       "Nevada                1.289016e+06  \n",
       "New Hampshire         7.284904e+05  \n",
       "New Jersey            4.456405e+06  \n",
       "New Mexico            9.133552e+05  \n",
       "New York              9.475189e+06  \n",
       "North Carolina        4.492913e+06  \n",
       "North Dakota          3.743388e+05  \n",
       "Ohio                  5.825846e+06  \n",
       "Oklahoma              1.744743e+06  \n",
       "Oregon                1.915029e+06  \n",
       "Pennsylvania          6.329845e+06  \n",
       "Puerto Rico           1.272898e+06  \n",
       "Rhode Island          5.593909e+05  \n",
       "South Carolina        2.119263e+06  \n",
       "South Dakota          4.360043e+05  \n",
       "Tennessee             3.008781e+06  \n",
       "Texas                 1.180258e+07  \n",
       "Utah                  1.323826e+06  \n",
       "Vermont               3.496151e+05  \n",
       "Virginia              4.014506e+06  \n",
       "Washington            3.358639e+06  \n",
       "West Virginia         8.002073e+05  \n",
       "Wisconsin             3.063265e+06  \n",
       "Wyoming               2.899716e+05  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('state').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and if we want multiple, but not all columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unemployment_rate</th>\n",
       "      <th>qty_unemployed</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>6.514706</td>\n",
       "      <td>1.407627e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>7.005392</td>\n",
       "      <td>2.449233e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>6.381373</td>\n",
       "      <td>1.901428e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>5.997059</td>\n",
       "      <td>7.955364e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>7.443627</td>\n",
       "      <td>1.347057e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>5.453922</td>\n",
       "      <td>1.452646e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>5.821078</td>\n",
       "      <td>1.082514e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>5.214216</td>\n",
       "      <td>2.292001e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>7.306373</td>\n",
       "      <td>2.490122e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>6.158824</td>\n",
       "      <td>5.573326e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>6.446078</td>\n",
       "      <td>3.016779e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawaii</th>\n",
       "      <td>4.456373</td>\n",
       "      <td>2.844513e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>5.525000</td>\n",
       "      <td>4.104917e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>6.936275</td>\n",
       "      <td>4.523743e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>6.184804</td>\n",
       "      <td>1.977921e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>4.373039</td>\n",
       "      <td>7.248086e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>5.084314</td>\n",
       "      <td>7.486110e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>6.639216</td>\n",
       "      <td>1.339159e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>6.197549</td>\n",
       "      <td>1.283975e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>5.470098</td>\n",
       "      <td>3.788920e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>5.121078</td>\n",
       "      <td>1.548394e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>5.521078</td>\n",
       "      <td>1.911474e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>7.662255</td>\n",
       "      <td>3.749323e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>4.886765</td>\n",
       "      <td>1.426212e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>7.285784</td>\n",
       "      <td>9.449842e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>6.069118</td>\n",
       "      <td>1.842034e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>5.023039</td>\n",
       "      <td>2.489118e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>3.629412</td>\n",
       "      <td>3.576543e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>7.220098</td>\n",
       "      <td>9.513693e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>4.205882</td>\n",
       "      <td>3.072605e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>6.248039</td>\n",
       "      <td>2.798071e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>5.972059</td>\n",
       "      <td>5.465965e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>6.182353</td>\n",
       "      <td>5.869909e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>6.741176</td>\n",
       "      <td>3.046283e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>3.279902</td>\n",
       "      <td>1.220031e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>6.455392</td>\n",
       "      <td>3.763495e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>4.784804</td>\n",
       "      <td>8.368540e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>7.242647</td>\n",
       "      <td>1.389804e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>5.946569</td>\n",
       "      <td>3.771446e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>12.653922</td>\n",
       "      <td>1.603699e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>7.000490</td>\n",
       "      <td>3.921885e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>7.130882</td>\n",
       "      <td>1.517508e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>3.579412</td>\n",
       "      <td>1.562588e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>6.369118</td>\n",
       "      <td>1.926002e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>5.775000</td>\n",
       "      <td>6.833513e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>4.716667</td>\n",
       "      <td>6.224774e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>4.247549</td>\n",
       "      <td>1.492144e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>4.543137</td>\n",
       "      <td>1.844006e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>6.706863</td>\n",
       "      <td>2.257521e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>6.168137</td>\n",
       "      <td>4.937335e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>5.668627</td>\n",
       "      <td>1.737884e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyoming</th>\n",
       "      <td>4.399510</td>\n",
       "      <td>1.283748e+04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      unemployment_rate  qty_unemployed\n",
       "state                                                  \n",
       "Alabama                        6.514706    1.407627e+05\n",
       "Alaska                         7.005392    2.449233e+04\n",
       "Arizona                        6.381373    1.901428e+05\n",
       "Arkansas                       5.997059    7.955364e+04\n",
       "California                     7.443627    1.347057e+06\n",
       "Colorado                       5.453922    1.452646e+05\n",
       "Connecticut                    5.821078    1.082514e+05\n",
       "Delaware                       5.214216    2.292001e+04\n",
       "District of Columbia           7.306373    2.490122e+04\n",
       "Florida                        6.158824    5.573326e+05\n",
       "Georgia                        6.446078    3.016779e+05\n",
       "Hawaii                         4.456373    2.844513e+04\n",
       "Idaho                          5.525000    4.104917e+04\n",
       "Illinois                       6.936275    4.523743e+05\n",
       "Indiana                        6.184804    1.977921e+05\n",
       "Iowa                           4.373039    7.248086e+04\n",
       "Kansas                         5.084314    7.486110e+04\n",
       "Kentucky                       6.639216    1.339159e+05\n",
       "Louisiana                      6.197549    1.283975e+05\n",
       "Maine                          5.470098    3.788920e+04\n",
       "Maryland                       5.121078    1.548394e+05\n",
       "Massachusetts                  5.521078    1.911474e+05\n",
       "Michigan                       7.662255    3.749323e+05\n",
       "Minnesota                      4.886765    1.426212e+05\n",
       "Mississippi                    7.285784    9.449842e+04\n",
       "Missouri                       6.069118    1.842034e+05\n",
       "Montana                        5.023039    2.489118e+04\n",
       "Nebraska                       3.629412    3.576543e+04\n",
       "Nevada                         7.220098    9.513693e+04\n",
       "New Hampshire                  4.205882    3.072605e+04\n",
       "New Jersey                     6.248039    2.798071e+05\n",
       "New Mexico                     5.972059    5.465965e+04\n",
       "New York                       6.182353    5.869909e+05\n",
       "North Carolina                 6.741176    3.046283e+05\n",
       "North Dakota                   3.279902    1.220031e+04\n",
       "Ohio                           6.455392    3.763495e+05\n",
       "Oklahoma                       4.784804    8.368540e+04\n",
       "Oregon                         7.242647    1.389804e+05\n",
       "Pennsylvania                   5.946569    3.771446e+05\n",
       "Puerto Rico                   12.653922    1.603699e+05\n",
       "Rhode Island                   7.000490    3.921885e+04\n",
       "South Carolina                 7.130882    1.517508e+05\n",
       "South Dakota                   3.579412    1.562588e+04\n",
       "Tennessee                      6.369118    1.926002e+05\n",
       "Texas                          5.775000    6.833513e+05\n",
       "Utah                           4.716667    6.224774e+04\n",
       "Vermont                        4.247549    1.492144e+04\n",
       "Virginia                       4.543137    1.844006e+05\n",
       "Washington                     6.706863    2.257521e+05\n",
       "West Virginia                  6.168137    4.937335e+04\n",
       "Wisconsin                      5.668627    1.737884e+05\n",
       "Wyoming                        4.399510    1.283748e+04"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('state')['unemployment_rate', 'qty_unemployed'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Very Cool!\n",
    "\n",
    "## Challenge\n",
    "\n",
    "Try and compute statistics where the grouping is described by multiple variables:\n",
    "1. Compute the average unemployment rate by state-year\n",
    "2. Compute the average unemployment rate by state-year-month\n",
    "3. Compute the average unemployment rate by state-year for the Carolinas (Hint: use the .filter() function after the computation)\n",
    "4. Compute the average unemployment rate by state-year and use `unstack` to view the data in a way that is different from the default output\n",
    "\n",
    "#### Partial Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state           year\n",
       "North Carolina  2000     3.666667\n",
       "                2001     5.516667\n",
       "                2002     6.658333\n",
       "                2003     6.375000\n",
       "                2004     5.491667\n",
       "                2005     5.233333\n",
       "                2006     4.750000\n",
       "                2007     4.725000\n",
       "                2008     6.100000\n",
       "                2009    10.575000\n",
       "                2010    10.850000\n",
       "                2011    10.275000\n",
       "                2012     9.291667\n",
       "                2013     7.983333\n",
       "                2014     6.300000\n",
       "                2015     5.750000\n",
       "                2016     5.058333\n",
       "South Carolina  2000     3.758333\n",
       "                2001     5.216667\n",
       "                2002     5.808333\n",
       "                2003     6.908333\n",
       "                2004     6.825000\n",
       "                2005     6.725000\n",
       "                2006     6.433333\n",
       "                2007     5.666667\n",
       "                2008     6.791667\n",
       "                2009    11.258333\n",
       "                2010    11.158333\n",
       "                2011    10.558333\n",
       "                2012     9.216667\n",
       "                2013     7.641667\n",
       "                2014     6.441667\n",
       "                2015     5.975000\n",
       "                2016     4.841667\n",
       "Name: unemployment_rate, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(['state', 'year'])['unemployment_rate'].mean().filter(like='Carolina')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>state</th>\n",
       "      <th>Alabama</th>\n",
       "      <th>Alaska</th>\n",
       "      <th>Arizona</th>\n",
       "      <th>Arkansas</th>\n",
       "      <th>California</th>\n",
       "      <th>Colorado</th>\n",
       "      <th>Connecticut</th>\n",
       "      <th>Delaware</th>\n",
       "      <th>District of Columbia</th>\n",
       "      <th>Florida</th>\n",
       "      <th>...</th>\n",
       "      <th>South Dakota</th>\n",
       "      <th>Tennessee</th>\n",
       "      <th>Texas</th>\n",
       "      <th>Utah</th>\n",
       "      <th>Vermont</th>\n",
       "      <th>Virginia</th>\n",
       "      <th>Washington</th>\n",
       "      <th>West Virginia</th>\n",
       "      <th>Wisconsin</th>\n",
       "      <th>Wyoming</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>4.583333</td>\n",
       "      <td>6.375000</td>\n",
       "      <td>3.950000</td>\n",
       "      <td>4.258333</td>\n",
       "      <td>4.941667</td>\n",
       "      <td>2.758333</td>\n",
       "      <td>2.391667</td>\n",
       "      <td>3.733333</td>\n",
       "      <td>5.608333</td>\n",
       "      <td>3.683333</td>\n",
       "      <td>...</td>\n",
       "      <td>2.458333</td>\n",
       "      <td>3.866667</td>\n",
       "      <td>4.291667</td>\n",
       "      <td>3.341667</td>\n",
       "      <td>2.808333</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>5.166667</td>\n",
       "      <td>5.483333</td>\n",
       "      <td>3.525000</td>\n",
       "      <td>3.908333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>5.125000</td>\n",
       "      <td>6.433333</td>\n",
       "      <td>4.791667</td>\n",
       "      <td>4.958333</td>\n",
       "      <td>5.433333</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>3.133333</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>6.333333</td>\n",
       "      <td>4.641667</td>\n",
       "      <td>...</td>\n",
       "      <td>3.091667</td>\n",
       "      <td>4.550000</td>\n",
       "      <td>4.941667</td>\n",
       "      <td>4.416667</td>\n",
       "      <td>3.333333</td>\n",
       "      <td>3.233333</td>\n",
       "      <td>6.300000</td>\n",
       "      <td>5.008333</td>\n",
       "      <td>4.525000</td>\n",
       "      <td>3.825000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>5.900000</td>\n",
       "      <td>7.291667</td>\n",
       "      <td>6.083333</td>\n",
       "      <td>5.483333</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>5.533333</td>\n",
       "      <td>4.333333</td>\n",
       "      <td>4.025000</td>\n",
       "      <td>6.408333</td>\n",
       "      <td>5.633333</td>\n",
       "      <td>...</td>\n",
       "      <td>3.183333</td>\n",
       "      <td>5.183333</td>\n",
       "      <td>6.341667</td>\n",
       "      <td>5.800000</td>\n",
       "      <td>3.991667</td>\n",
       "      <td>4.216667</td>\n",
       "      <td>7.408333</td>\n",
       "      <td>5.916667</td>\n",
       "      <td>5.375000</td>\n",
       "      <td>4.041667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>6.016667</td>\n",
       "      <td>7.825000</td>\n",
       "      <td>5.741667</td>\n",
       "      <td>5.933333</td>\n",
       "      <td>6.800000</td>\n",
       "      <td>5.958333</td>\n",
       "      <td>5.391667</td>\n",
       "      <td>4.266667</td>\n",
       "      <td>6.833333</td>\n",
       "      <td>5.208333</td>\n",
       "      <td>...</td>\n",
       "      <td>3.533333</td>\n",
       "      <td>5.633333</td>\n",
       "      <td>6.683333</td>\n",
       "      <td>5.633333</td>\n",
       "      <td>4.266667</td>\n",
       "      <td>4.108333</td>\n",
       "      <td>7.408333</td>\n",
       "      <td>6.050000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>4.275000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>5.683333</td>\n",
       "      <td>7.458333</td>\n",
       "      <td>5.033333</td>\n",
       "      <td>5.708333</td>\n",
       "      <td>6.208333</td>\n",
       "      <td>5.483333</td>\n",
       "      <td>4.966667</td>\n",
       "      <td>3.991667</td>\n",
       "      <td>7.783333</td>\n",
       "      <td>4.633333</td>\n",
       "      <td>...</td>\n",
       "      <td>3.725000</td>\n",
       "      <td>5.333333</td>\n",
       "      <td>5.941667</td>\n",
       "      <td>4.991667</td>\n",
       "      <td>3.675000</td>\n",
       "      <td>3.825000</td>\n",
       "      <td>6.266667</td>\n",
       "      <td>5.325000</td>\n",
       "      <td>5.025000</td>\n",
       "      <td>3.808333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>4.491667</td>\n",
       "      <td>6.883333</td>\n",
       "      <td>4.683333</td>\n",
       "      <td>5.250000</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>5.025000</td>\n",
       "      <td>4.883333</td>\n",
       "      <td>4.141667</td>\n",
       "      <td>6.375000</td>\n",
       "      <td>3.691667</td>\n",
       "      <td>...</td>\n",
       "      <td>3.816667</td>\n",
       "      <td>5.550000</td>\n",
       "      <td>5.408333</td>\n",
       "      <td>4.091667</td>\n",
       "      <td>3.475000</td>\n",
       "      <td>3.566667</td>\n",
       "      <td>5.550000</td>\n",
       "      <td>5.108333</td>\n",
       "      <td>4.741667</td>\n",
       "      <td>3.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>4.033333</td>\n",
       "      <td>6.616667</td>\n",
       "      <td>4.208333</td>\n",
       "      <td>5.158333</td>\n",
       "      <td>4.900000</td>\n",
       "      <td>4.308333</td>\n",
       "      <td>4.333333</td>\n",
       "      <td>3.575000</td>\n",
       "      <td>5.791667</td>\n",
       "      <td>3.225000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.108333</td>\n",
       "      <td>5.200000</td>\n",
       "      <td>4.891667</td>\n",
       "      <td>2.975000</td>\n",
       "      <td>3.683333</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>5.041667</td>\n",
       "      <td>4.941667</td>\n",
       "      <td>4.741667</td>\n",
       "      <td>3.175000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>3.983333</td>\n",
       "      <td>6.333333</td>\n",
       "      <td>3.858333</td>\n",
       "      <td>5.308333</td>\n",
       "      <td>5.375000</td>\n",
       "      <td>3.733333</td>\n",
       "      <td>4.475000</td>\n",
       "      <td>3.441667</td>\n",
       "      <td>5.525000</td>\n",
       "      <td>4.008333</td>\n",
       "      <td>...</td>\n",
       "      <td>2.841667</td>\n",
       "      <td>4.675000</td>\n",
       "      <td>4.291667</td>\n",
       "      <td>2.566667</td>\n",
       "      <td>4.008333</td>\n",
       "      <td>3.033333</td>\n",
       "      <td>4.708333</td>\n",
       "      <td>4.583333</td>\n",
       "      <td>4.900000</td>\n",
       "      <td>2.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>5.658333</td>\n",
       "      <td>6.691667</td>\n",
       "      <td>6.125000</td>\n",
       "      <td>5.466667</td>\n",
       "      <td>7.275000</td>\n",
       "      <td>4.825000</td>\n",
       "      <td>5.683333</td>\n",
       "      <td>4.941667</td>\n",
       "      <td>6.458333</td>\n",
       "      <td>6.283333</td>\n",
       "      <td>...</td>\n",
       "      <td>3.050000</td>\n",
       "      <td>6.575000</td>\n",
       "      <td>4.808333</td>\n",
       "      <td>3.591667</td>\n",
       "      <td>4.683333</td>\n",
       "      <td>3.941667</td>\n",
       "      <td>5.383333</td>\n",
       "      <td>4.358333</td>\n",
       "      <td>4.908333</td>\n",
       "      <td>3.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>11.033333</td>\n",
       "      <td>7.741667</td>\n",
       "      <td>9.933333</td>\n",
       "      <td>7.850000</td>\n",
       "      <td>11.141667</td>\n",
       "      <td>7.283333</td>\n",
       "      <td>7.933333</td>\n",
       "      <td>8.266667</td>\n",
       "      <td>9.275000</td>\n",
       "      <td>10.408333</td>\n",
       "      <td>...</td>\n",
       "      <td>4.925000</td>\n",
       "      <td>10.483333</td>\n",
       "      <td>7.558333</td>\n",
       "      <td>7.325000</td>\n",
       "      <td>6.591667</td>\n",
       "      <td>6.700000</td>\n",
       "      <td>9.141667</td>\n",
       "      <td>7.725000</td>\n",
       "      <td>8.575000</td>\n",
       "      <td>6.325000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>10.541667</td>\n",
       "      <td>7.883333</td>\n",
       "      <td>10.366667</td>\n",
       "      <td>8.191667</td>\n",
       "      <td>12.225000</td>\n",
       "      <td>8.725000</td>\n",
       "      <td>9.108333</td>\n",
       "      <td>8.416667</td>\n",
       "      <td>9.416667</td>\n",
       "      <td>11.041667</td>\n",
       "      <td>...</td>\n",
       "      <td>4.983333</td>\n",
       "      <td>9.675000</td>\n",
       "      <td>8.150000</td>\n",
       "      <td>7.833333</td>\n",
       "      <td>6.091667</td>\n",
       "      <td>7.150000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>8.641667</td>\n",
       "      <td>8.666667</td>\n",
       "      <td>6.458333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>9.641667</td>\n",
       "      <td>7.591667</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>8.308333</td>\n",
       "      <td>11.716667</td>\n",
       "      <td>8.358333</td>\n",
       "      <td>8.808333</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>10.158333</td>\n",
       "      <td>9.991667</td>\n",
       "      <td>...</td>\n",
       "      <td>4.741667</td>\n",
       "      <td>8.991667</td>\n",
       "      <td>7.758333</td>\n",
       "      <td>6.733333</td>\n",
       "      <td>5.475000</td>\n",
       "      <td>6.591667</td>\n",
       "      <td>9.291667</td>\n",
       "      <td>8.058333</td>\n",
       "      <td>7.758333</td>\n",
       "      <td>5.808333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>7.941667</td>\n",
       "      <td>7.141667</td>\n",
       "      <td>8.350000</td>\n",
       "      <td>7.575000</td>\n",
       "      <td>10.375000</td>\n",
       "      <td>7.875000</td>\n",
       "      <td>8.341667</td>\n",
       "      <td>7.200000</td>\n",
       "      <td>9.050000</td>\n",
       "      <td>8.458333</td>\n",
       "      <td>...</td>\n",
       "      <td>4.275000</td>\n",
       "      <td>7.841667</td>\n",
       "      <td>6.725000</td>\n",
       "      <td>5.408333</td>\n",
       "      <td>4.950000</td>\n",
       "      <td>6.033333</td>\n",
       "      <td>8.133333</td>\n",
       "      <td>7.508333</td>\n",
       "      <td>7.041667</td>\n",
       "      <td>5.316667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>7.225000</td>\n",
       "      <td>6.925000</td>\n",
       "      <td>7.741667</td>\n",
       "      <td>7.341667</td>\n",
       "      <td>8.933333</td>\n",
       "      <td>6.825000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>6.716667</td>\n",
       "      <td>8.500000</td>\n",
       "      <td>7.233333</td>\n",
       "      <td>...</td>\n",
       "      <td>3.783333</td>\n",
       "      <td>7.791667</td>\n",
       "      <td>6.225000</td>\n",
       "      <td>4.600000</td>\n",
       "      <td>4.416667</td>\n",
       "      <td>5.716667</td>\n",
       "      <td>7.033333</td>\n",
       "      <td>6.766667</td>\n",
       "      <td>6.741667</td>\n",
       "      <td>4.708333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>6.791667</td>\n",
       "      <td>6.841667</td>\n",
       "      <td>6.775000</td>\n",
       "      <td>6.091667</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>6.608333</td>\n",
       "      <td>5.708333</td>\n",
       "      <td>7.775000</td>\n",
       "      <td>6.266667</td>\n",
       "      <td>...</td>\n",
       "      <td>3.433333</td>\n",
       "      <td>6.516667</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>3.816667</td>\n",
       "      <td>3.950000</td>\n",
       "      <td>5.241667</td>\n",
       "      <td>6.125000</td>\n",
       "      <td>6.633333</td>\n",
       "      <td>5.416667</td>\n",
       "      <td>4.158333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>6.108333</td>\n",
       "      <td>6.441667</td>\n",
       "      <td>6.033333</td>\n",
       "      <td>5.075000</td>\n",
       "      <td>6.216667</td>\n",
       "      <td>3.908333</td>\n",
       "      <td>5.733333</td>\n",
       "      <td>4.833333</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>5.416667</td>\n",
       "      <td>...</td>\n",
       "      <td>3.075000</td>\n",
       "      <td>5.600000</td>\n",
       "      <td>4.441667</td>\n",
       "      <td>3.633333</td>\n",
       "      <td>3.566667</td>\n",
       "      <td>4.466667</td>\n",
       "      <td>5.625000</td>\n",
       "      <td>6.750000</td>\n",
       "      <td>4.575000</td>\n",
       "      <td>4.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>5.991667</td>\n",
       "      <td>6.616667</td>\n",
       "      <td>5.308333</td>\n",
       "      <td>3.991667</td>\n",
       "      <td>5.433333</td>\n",
       "      <td>3.316667</td>\n",
       "      <td>5.083333</td>\n",
       "      <td>4.383333</td>\n",
       "      <td>6.016667</td>\n",
       "      <td>4.875000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.825000</td>\n",
       "      <td>4.808333</td>\n",
       "      <td>4.616667</td>\n",
       "      <td>3.425000</td>\n",
       "      <td>3.241667</td>\n",
       "      <td>4.008333</td>\n",
       "      <td>5.433333</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.150000</td>\n",
       "      <td>5.283333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "state    Alabama    Alaska    Arizona  Arkansas  California  Colorado  \\\n",
       "year                                                                    \n",
       "2000    4.583333  6.375000   3.950000  4.258333    4.941667  2.758333   \n",
       "2001    5.125000  6.433333   4.791667  4.958333    5.433333  3.800000   \n",
       "2002    5.900000  7.291667   6.083333  5.483333    6.666667  5.533333   \n",
       "2003    6.016667  7.825000   5.741667  5.933333    6.800000  5.958333   \n",
       "2004    5.683333  7.458333   5.033333  5.708333    6.208333  5.483333   \n",
       "2005    4.491667  6.883333   4.683333  5.250000    5.400000  5.025000   \n",
       "2006    4.033333  6.616667   4.208333  5.158333    4.900000  4.308333   \n",
       "2007    3.983333  6.333333   3.858333  5.308333    5.375000  3.733333   \n",
       "2008    5.658333  6.691667   6.125000  5.466667    7.275000  4.825000   \n",
       "2009   11.033333  7.741667   9.933333  7.850000   11.141667  7.283333   \n",
       "2010   10.541667  7.883333  10.366667  8.191667   12.225000  8.725000   \n",
       "2011    9.641667  7.591667   9.500000  8.308333   11.716667  8.358333   \n",
       "2012    7.941667  7.141667   8.350000  7.575000   10.375000  7.875000   \n",
       "2013    7.225000  6.925000   7.741667  7.341667    8.933333  6.825000   \n",
       "2014    6.791667  6.841667   6.775000  6.091667    7.500000  5.000000   \n",
       "2015    6.108333  6.441667   6.033333  5.075000    6.216667  3.908333   \n",
       "2016    5.991667  6.616667   5.308333  3.991667    5.433333  3.316667   \n",
       "\n",
       "state  Connecticut  Delaware  District of Columbia    Florida    ...     \\\n",
       "year                                                             ...      \n",
       "2000      2.391667  3.733333              5.608333   3.683333    ...      \n",
       "2001      3.133333  3.500000              6.333333   4.641667    ...      \n",
       "2002      4.333333  4.025000              6.408333   5.633333    ...      \n",
       "2003      5.391667  4.266667              6.833333   5.208333    ...      \n",
       "2004      4.966667  3.991667              7.783333   4.633333    ...      \n",
       "2005      4.883333  4.141667              6.375000   3.691667    ...      \n",
       "2006      4.333333  3.575000              5.791667   3.225000    ...      \n",
       "2007      4.475000  3.441667              5.525000   4.008333    ...      \n",
       "2008      5.683333  4.941667              6.458333   6.283333    ...      \n",
       "2009      7.933333  8.266667              9.275000  10.408333    ...      \n",
       "2010      9.108333  8.416667              9.416667  11.041667    ...      \n",
       "2011      8.808333  7.500000             10.158333   9.991667    ...      \n",
       "2012      8.341667  7.200000              9.050000   8.458333    ...      \n",
       "2013      7.750000  6.716667              8.500000   7.233333    ...      \n",
       "2014      6.608333  5.708333              7.775000   6.266667    ...      \n",
       "2015      5.733333  4.833333              6.900000   5.416667    ...      \n",
       "2016      5.083333  4.383333              6.016667   4.875000    ...      \n",
       "\n",
       "state  South Dakota  Tennessee     Texas      Utah   Vermont  Virginia  \\\n",
       "year                                                                     \n",
       "2000       2.458333   3.866667  4.291667  3.341667  2.808333  2.300000   \n",
       "2001       3.091667   4.550000  4.941667  4.416667  3.333333  3.233333   \n",
       "2002       3.183333   5.183333  6.341667  5.800000  3.991667  4.216667   \n",
       "2003       3.533333   5.633333  6.683333  5.633333  4.266667  4.108333   \n",
       "2004       3.725000   5.333333  5.941667  4.991667  3.675000  3.825000   \n",
       "2005       3.816667   5.550000  5.408333  4.091667  3.475000  3.566667   \n",
       "2006       3.108333   5.200000  4.891667  2.975000  3.683333  3.100000   \n",
       "2007       2.841667   4.675000  4.291667  2.566667  4.008333  3.033333   \n",
       "2008       3.050000   6.575000  4.808333  3.591667  4.683333  3.941667   \n",
       "2009       4.925000  10.483333  7.558333  7.325000  6.591667  6.700000   \n",
       "2010       4.983333   9.675000  8.150000  7.833333  6.091667  7.150000   \n",
       "2011       4.741667   8.991667  7.758333  6.733333  5.475000  6.591667   \n",
       "2012       4.275000   7.841667  6.725000  5.408333  4.950000  6.033333   \n",
       "2013       3.783333   7.791667  6.225000  4.600000  4.416667  5.716667   \n",
       "2014       3.433333   6.516667  5.100000  3.816667  3.950000  5.241667   \n",
       "2015       3.075000   5.600000  4.441667  3.633333  3.566667  4.466667   \n",
       "2016       2.825000   4.808333  4.616667  3.425000  3.241667  4.008333   \n",
       "\n",
       "state  Washington  West Virginia  Wisconsin   Wyoming  \n",
       "year                                                   \n",
       "2000     5.166667       5.483333   3.525000  3.908333  \n",
       "2001     6.300000       5.008333   4.525000  3.825000  \n",
       "2002     7.408333       5.916667   5.375000  4.041667  \n",
       "2003     7.408333       6.050000   5.700000  4.275000  \n",
       "2004     6.266667       5.325000   5.025000  3.808333  \n",
       "2005     5.550000       5.108333   4.741667  3.583333  \n",
       "2006     5.041667       4.941667   4.741667  3.175000  \n",
       "2007     4.708333       4.583333   4.900000  2.816667  \n",
       "2008     5.383333       4.358333   4.908333  3.050000  \n",
       "2009     9.141667       7.725000   8.575000  6.325000  \n",
       "2010    10.000000       8.641667   8.666667  6.458333  \n",
       "2011     9.291667       8.058333   7.758333  5.808333  \n",
       "2012     8.133333       7.508333   7.041667  5.316667  \n",
       "2013     7.033333       6.766667   6.741667  4.708333  \n",
       "2014     6.125000       6.633333   5.416667  4.158333  \n",
       "2015     5.625000       6.750000   4.575000  4.250000  \n",
       "2016     5.433333       6.000000   4.150000  5.283333  \n",
       "\n",
       "[17 rows x 52 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(['state', 'year'])['unemployment_rate'].mean().unstack(level=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## More useful GroupBy functionality\n",
    "\n",
    "Often we want more than one aggregate statistic, for example we may want the min, mean and max by State. We can use the `.aggregate()` function to get these:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>amin</th>\n",
       "      <th>mean</th>\n",
       "      <th>amax</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>3.3</td>\n",
       "      <td>6.514706</td>\n",
       "      <td>12.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>5.2</td>\n",
       "      <td>7.005392</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>3.4</td>\n",
       "      <td>6.381373</td>\n",
       "      <td>11.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>3.4</td>\n",
       "      <td>5.997059</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>4.4</td>\n",
       "      <td>7.443627</td>\n",
       "      <td>12.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>2.4</td>\n",
       "      <td>5.453922</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>1.7</td>\n",
       "      <td>5.821078</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>2.9</td>\n",
       "      <td>5.214216</td>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>4.7</td>\n",
       "      <td>7.306373</td>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>2.8</td>\n",
       "      <td>6.158824</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6.446078</td>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawaii</th>\n",
       "      <td>1.9</td>\n",
       "      <td>4.456373</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>2.2</td>\n",
       "      <td>5.525000</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>3.6</td>\n",
       "      <td>6.936275</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>2.2</td>\n",
       "      <td>6.184804</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>2.3</td>\n",
       "      <td>4.373039</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>3.2</td>\n",
       "      <td>5.084314</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>3.7</td>\n",
       "      <td>6.639216</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>3.6</td>\n",
       "      <td>6.197549</td>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>2.6</td>\n",
       "      <td>5.470098</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>3.1</td>\n",
       "      <td>5.121078</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>2.1</td>\n",
       "      <td>5.521078</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>2.9</td>\n",
       "      <td>7.662255</td>\n",
       "      <td>15.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>2.7</td>\n",
       "      <td>4.886765</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>4.6</td>\n",
       "      <td>7.285784</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6.069118</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>2.7</td>\n",
       "      <td>5.023039</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>2.6</td>\n",
       "      <td>3.629412</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>3.7</td>\n",
       "      <td>7.220098</td>\n",
       "      <td>13.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>2.3</td>\n",
       "      <td>4.205882</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>3.3</td>\n",
       "      <td>6.248039</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>3.4</td>\n",
       "      <td>5.972059</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>3.9</td>\n",
       "      <td>6.182353</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6.741176</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.279902</td>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>3.4</td>\n",
       "      <td>6.455392</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>2.6</td>\n",
       "      <td>4.784804</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>4.2</td>\n",
       "      <td>7.242647</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>3.6</td>\n",
       "      <td>5.946569</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>8.9</td>\n",
       "      <td>12.653922</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>3.6</td>\n",
       "      <td>7.000490</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>3.2</td>\n",
       "      <td>7.130882</td>\n",
       "      <td>12.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.579412</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>3.3</td>\n",
       "      <td>6.369118</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>3.5</td>\n",
       "      <td>5.775000</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>2.1</td>\n",
       "      <td>4.716667</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>2.3</td>\n",
       "      <td>4.247549</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>1.8</td>\n",
       "      <td>4.543137</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>4.2</td>\n",
       "      <td>6.706863</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>3.6</td>\n",
       "      <td>6.168137</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>2.8</td>\n",
       "      <td>5.668627</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyoming</th>\n",
       "      <td>2.4</td>\n",
       "      <td>4.399510</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      amin       mean  amax\n",
       "state                                      \n",
       "Alabama                3.3   6.514706  12.3\n",
       "Alaska                 5.2   7.005392   9.1\n",
       "Arizona                3.4   6.381373  11.1\n",
       "Arkansas               3.4   5.997059   9.5\n",
       "California             4.4   7.443627  12.7\n",
       "Colorado               2.4   5.453922   9.2\n",
       "Connecticut            1.7   5.821078   9.8\n",
       "Delaware               2.9   5.214216   9.4\n",
       "District of Columbia   4.7   7.306373  10.9\n",
       "Florida                2.8   6.158824  11.5\n",
       "Georgia                3.0   6.446078  10.9\n",
       "Hawaii                 1.9   4.456373   7.9\n",
       "Idaho                  2.2   5.525000  10.5\n",
       "Illinois               3.6   6.936275  12.2\n",
       "Indiana                2.2   6.184804  11.8\n",
       "Iowa                   2.3   4.373039   7.3\n",
       "Kansas                 3.2   5.084314   7.9\n",
       "Kentucky               3.7   6.639216  11.9\n",
       "Louisiana              3.6   6.197549  10.9\n",
       "Maine                  2.6   5.470098   9.5\n",
       "Maryland               3.1   5.121078   8.3\n",
       "Massachusetts          2.1   5.521078   9.6\n",
       "Michigan               2.9   7.662255  15.4\n",
       "Minnesota              2.7   4.886765   8.6\n",
       "Mississippi            4.6   7.285784  11.7\n",
       "Missouri               3.0   6.069118  10.5\n",
       "Montana                2.7   5.023039   8.6\n",
       "Nebraska               2.6   3.629412   5.4\n",
       "Nevada                 3.7   7.220098  13.9\n",
       "New Hampshire          2.3   4.205882   7.0\n",
       "New Jersey             3.3   6.248039  10.3\n",
       "New Mexico             3.4   5.972059   9.0\n",
       "New York               3.9   6.182353   9.6\n",
       "North Carolina         3.0   6.741176  12.0\n",
       "North Dakota           2.0   3.279902   5.1\n",
       "Ohio                   3.4   6.455392  12.0\n",
       "Oklahoma               2.6   4.784804   7.6\n",
       "Oregon                 4.2   7.242647  12.6\n",
       "Pennsylvania           3.6   5.946569   9.5\n",
       "Puerto Rico            8.9  12.653922  17.3\n",
       "Rhode Island           3.6   7.000490  12.2\n",
       "South Carolina         3.2   7.130882  12.4\n",
       "South Dakota           2.0   3.579412   5.9\n",
       "Tennessee              3.3   6.369118  11.3\n",
       "Texas                  3.5   5.775000   8.6\n",
       "Utah                   2.1   4.716667   8.4\n",
       "Vermont                2.3   4.247549   7.6\n",
       "Virginia               1.8   4.543137   7.9\n",
       "Washington             4.2   6.706863  11.3\n",
       "West Virginia          3.6   6.168137  10.0\n",
       "Wisconsin              2.8   5.668627  10.4\n",
       "Wyoming                2.4   4.399510   8.1"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('state')['unemployment_rate'].aggregate([np.min, np.mean, np.max])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can dress it up a little too if we like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Mean Unemploy.</th>\n",
       "      <th>Min. Unemploy.</th>\n",
       "      <th>Max. Unemploy.</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>6.514706</td>\n",
       "      <td>3.3</td>\n",
       "      <td>12.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>7.005392</td>\n",
       "      <td>5.2</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>6.381373</td>\n",
       "      <td>3.4</td>\n",
       "      <td>11.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>5.997059</td>\n",
       "      <td>3.4</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>7.443627</td>\n",
       "      <td>4.4</td>\n",
       "      <td>12.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>5.453922</td>\n",
       "      <td>2.4</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>5.821078</td>\n",
       "      <td>1.7</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>5.214216</td>\n",
       "      <td>2.9</td>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>7.306373</td>\n",
       "      <td>4.7</td>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>6.158824</td>\n",
       "      <td>2.8</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>6.446078</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawaii</th>\n",
       "      <td>4.456373</td>\n",
       "      <td>1.9</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>5.525000</td>\n",
       "      <td>2.2</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>6.936275</td>\n",
       "      <td>3.6</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>6.184804</td>\n",
       "      <td>2.2</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>4.373039</td>\n",
       "      <td>2.3</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>5.084314</td>\n",
       "      <td>3.2</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>6.639216</td>\n",
       "      <td>3.7</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>6.197549</td>\n",
       "      <td>3.6</td>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>5.470098</td>\n",
       "      <td>2.6</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>5.121078</td>\n",
       "      <td>3.1</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>5.521078</td>\n",
       "      <td>2.1</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>7.662255</td>\n",
       "      <td>2.9</td>\n",
       "      <td>15.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>4.886765</td>\n",
       "      <td>2.7</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>7.285784</td>\n",
       "      <td>4.6</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>6.069118</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>5.023039</td>\n",
       "      <td>2.7</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>3.629412</td>\n",
       "      <td>2.6</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>7.220098</td>\n",
       "      <td>3.7</td>\n",
       "      <td>13.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>4.205882</td>\n",
       "      <td>2.3</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>6.248039</td>\n",
       "      <td>3.3</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>5.972059</td>\n",
       "      <td>3.4</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>6.182353</td>\n",
       "      <td>3.9</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>6.741176</td>\n",
       "      <td>3.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>3.279902</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>6.455392</td>\n",
       "      <td>3.4</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>4.784804</td>\n",
       "      <td>2.6</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>7.242647</td>\n",
       "      <td>4.2</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>5.946569</td>\n",
       "      <td>3.6</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>12.653922</td>\n",
       "      <td>8.9</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>7.000490</td>\n",
       "      <td>3.6</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>7.130882</td>\n",
       "      <td>3.2</td>\n",
       "      <td>12.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>3.579412</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>6.369118</td>\n",
       "      <td>3.3</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>5.775000</td>\n",
       "      <td>3.5</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>4.716667</td>\n",
       "      <td>2.1</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>4.247549</td>\n",
       "      <td>2.3</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>4.543137</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>6.706863</td>\n",
       "      <td>4.2</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>6.168137</td>\n",
       "      <td>3.6</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>5.668627</td>\n",
       "      <td>2.8</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyoming</th>\n",
       "      <td>4.399510</td>\n",
       "      <td>2.4</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Mean Unemploy.  Min. Unemploy.  Max. Unemploy.\n",
       "state                                                               \n",
       "Alabama                     6.514706             3.3            12.3\n",
       "Alaska                      7.005392             5.2             9.1\n",
       "Arizona                     6.381373             3.4            11.1\n",
       "Arkansas                    5.997059             3.4             9.5\n",
       "California                  7.443627             4.4            12.7\n",
       "Colorado                    5.453922             2.4             9.2\n",
       "Connecticut                 5.821078             1.7             9.8\n",
       "Delaware                    5.214216             2.9             9.4\n",
       "District of Columbia        7.306373             4.7            10.9\n",
       "Florida                     6.158824             2.8            11.5\n",
       "Georgia                     6.446078             3.0            10.9\n",
       "Hawaii                      4.456373             1.9             7.9\n",
       "Idaho                       5.525000             2.2            10.5\n",
       "Illinois                    6.936275             3.6            12.2\n",
       "Indiana                     6.184804             2.2            11.8\n",
       "Iowa                        4.373039             2.3             7.3\n",
       "Kansas                      5.084314             3.2             7.9\n",
       "Kentucky                    6.639216             3.7            11.9\n",
       "Louisiana                   6.197549             3.6            10.9\n",
       "Maine                       5.470098             2.6             9.5\n",
       "Maryland                    5.121078             3.1             8.3\n",
       "Massachusetts               5.521078             2.1             9.6\n",
       "Michigan                    7.662255             2.9            15.4\n",
       "Minnesota                   4.886765             2.7             8.6\n",
       "Mississippi                 7.285784             4.6            11.7\n",
       "Missouri                    6.069118             3.0            10.5\n",
       "Montana                     5.023039             2.7             8.6\n",
       "Nebraska                    3.629412             2.6             5.4\n",
       "Nevada                      7.220098             3.7            13.9\n",
       "New Hampshire               4.205882             2.3             7.0\n",
       "New Jersey                  6.248039             3.3            10.3\n",
       "New Mexico                  5.972059             3.4             9.0\n",
       "New York                    6.182353             3.9             9.6\n",
       "North Carolina              6.741176             3.0            12.0\n",
       "North Dakota                3.279902             2.0             5.1\n",
       "Ohio                        6.455392             3.4            12.0\n",
       "Oklahoma                    4.784804             2.6             7.6\n",
       "Oregon                      7.242647             4.2            12.6\n",
       "Pennsylvania                5.946569             3.6             9.5\n",
       "Puerto Rico                12.653922             8.9            17.3\n",
       "Rhode Island                7.000490             3.6            12.2\n",
       "South Carolina              7.130882             3.2            12.4\n",
       "South Dakota                3.579412             2.0             5.9\n",
       "Tennessee                   6.369118             3.3            11.3\n",
       "Texas                       5.775000             3.5             8.6\n",
       "Utah                        4.716667             2.1             8.4\n",
       "Vermont                     4.247549             2.3             7.6\n",
       "Virginia                    4.543137             1.8             7.9\n",
       "Washington                  6.706863             4.2            11.3\n",
       "West Virginia               6.168137             3.6            10.0\n",
       "Wisconsin                   5.668627             2.8            10.4\n",
       "Wyoming                     4.399510             2.4             8.1"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('state')['unemployment_rate'] \\\n",
    "        .aggregate({'Min. Unemploy.' : np.min,\n",
    "                    'Mean Unemploy.' : np.mean,\n",
    "                    'Max. Unemploy.' : np.max})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the challenge above, we used filter to select out states based on a string, but there are more uses of filter than this simple one. For example, we can filter based on the group properties:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def filter_func(x):\n",
    "    return x['unemployment_rate'].min() > 5\n",
    "\n",
    "problem_states = data.groupby('state').filter(filter_func)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Alaska', 'Puerto Rico'], dtype=object)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "problem_states.state.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>state</th>\n",
       "      <th>Alaska</th>\n",
       "      <th>Puerto Rico</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>6.375000</td>\n",
       "      <td>10.125000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>6.433333</td>\n",
       "      <td>11.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>7.291667</td>\n",
       "      <td>12.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>7.825000</td>\n",
       "      <td>11.966667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>7.458333</td>\n",
       "      <td>10.575000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>6.883333</td>\n",
       "      <td>11.325000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>6.616667</td>\n",
       "      <td>10.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>6.333333</td>\n",
       "      <td>11.183333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>6.691667</td>\n",
       "      <td>11.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>7.741667</td>\n",
       "      <td>15.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>7.883333</td>\n",
       "      <td>16.358333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>7.591667</td>\n",
       "      <td>15.941667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>7.141667</td>\n",
       "      <td>14.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>6.925000</td>\n",
       "      <td>14.291667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>6.841667</td>\n",
       "      <td>13.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>6.441667</td>\n",
       "      <td>11.991667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>6.616667</td>\n",
       "      <td>11.791667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "state    Alaska  Puerto Rico\n",
       "year                        \n",
       "2000   6.375000    10.125000\n",
       "2001   6.433333    11.350000\n",
       "2002   7.291667    12.250000\n",
       "2003   7.825000    11.966667\n",
       "2004   7.458333    10.575000\n",
       "2005   6.883333    11.325000\n",
       "2006   6.616667    10.500000\n",
       "2007   6.333333    11.183333\n",
       "2008   6.691667    11.766667\n",
       "2009   7.741667    15.333333\n",
       "2010   7.883333    16.358333\n",
       "2011   7.591667    15.941667\n",
       "2012   7.141667    14.466667\n",
       "2013   6.925000    14.291667\n",
       "2014   6.841667    13.900000\n",
       "2015   6.441667    11.991667\n",
       "2016   6.616667    11.791667"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "problem_states.groupby(['state', 'year']).unemployment_rate.mean().unstack(level=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Other useful functions:\n",
    "\n",
    "GroupBy also works alongside the following functions:\n",
    "* `transform()`\n",
    "* `apply()`\n",
    "\n",
    "For lack of time we leave these for you to explore."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}