williamjshipman/StatsSAParseASCIITimeSeries.ipynb

## StatsSAParseASCIITimeSeries.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading Stats SA ASCII-formatted time series data\n",
    "\n",
    "## Introduction\n",
    "\n",
    "Statistics South Africa (Stats SA) is the government statistician here in South Africa. They publish stats about the economy, standard of living, the performance of local government, and lots of other stuff. If you're interested in finding out the state of South Africa in cold hard numbers, head over to [http://www.statssa.gov.za/](http://www.statssa.gov.za/).\n",
    "\n",
    "Most of their data is, unfortunately, locked up in reports that can be downloaded as PDFs - i.e. not that easy to do one's own analyses. Sometimes, they do make time series data available though. When time series data is available for download, its provided in two formats: Excel work books and ASCII files. Working with Excel is easy, but I feel like a challenge and I feel like avoiding Excel. That's why this notebook will focus on making a function to parse the ASCII files made available by Stats SA. I'll be putting this function to use in subsequent notebooks to make some interesting analyses of Stats SA data.\n",
    "\n",
    "This notebook and related data can be downloaded from my repository for Stats SA-related blog posts: [StatsSA-blog](https://bitbucket.org/williamjshipman/statssa-blog)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/wjs/opt/anaconda3/lib/python3.5/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n",
      "  warnings.warn(self.msg_depr % (key, alt_key))\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from os.path import expanduser\n",
    "from datetime import date\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The first stage - ASCII to a data structure\n",
    "\n",
    "My first step is going to be to transform the text file into a list of time series structures. The basic structure of each time series is a sequence of meta-data lines followed by the actual values, one per line.\n",
    "\n",
    "The meta-data lines start with tag Hxx (e.g. H01, H13), which is followed by some text. The actual data follows the meta-data, with each value in the time series printed on a new line. The end of the time series is indicated either by the end of the text file or by the appearance of a new meta-data line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "all_time_series = []\n",
    "with open(expanduser('./data/CPI/ASCII Consumer Price Index - Jan 2008 to Nov 2015.txt'), 'r') as inputfile:\n",
    "    for inputline in inputfile:\n",
    "        if inputline[0] == 'H': # This is a meta-data field.\n",
    "            tag, sep, value = inputline.partition(': ')\n",
    "            if tag == 'H01':\n",
    "                all_time_series += [{'data':[], 'tags':{}}]\n",
    "            all_time_series[-1]['tags'][tag] = value.strip()\n",
    "        else:\n",
    "            all_time_series[-1]['data'] += [float(inputline)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "978"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_time_series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'H01': 'P0141',\n",
       " 'H02': 'Consumer Price Index',\n",
       " 'H03': 'CPA00000',\n",
       " 'H04': 'All Items',\n",
       " 'H05': '',\n",
       " 'H06': '',\n",
       " 'H13': 'Western Cape',\n",
       " 'H14': '',\n",
       " 'H17': 'Index',\n",
       " 'H18': 'Dec 2012 = 100',\n",
       " 'H23': 'RELEASE: 2015 11',\n",
       " 'H24': 'START: 2008 01',\n",
       " 'H25': 'monthly'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_time_series[0]['tags']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The tag H01 gives the publication number, while H02 gives the title associated with that publication. In this case, I'm looking at the Consumer Price Index in South Africa. The data doesn't just give the overall CPI though. It also gives CPI for different baskets of goods in each province. The basket of goods is indicated by the H04 tag, e.g. 'All items', 'Clothing' or 'Tobacco' are some of the baskets for which CPI is calculated. The H13 tag tells us which province the time series applies to, or if it applies to the whole of South Africa."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Making Pandas Series objects\n",
    "\n",
    "Now that each time series has been extracted, the next step is to construct some Pandas Series objects, one for each time series. You'll see that the Stats SA data specifies the start date for a time series and an update frequency e.g. monthly. These need to be turned into a DateRange that can be used as an index into the Series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for tsdata in all_time_series:\n",
    "    if tsdata['tags']['H25'].strip() == 'monthly':\n",
    "        _, start_year, start_month = tsdata['tags']['H24'].split(' ')\n",
    "        index = pd.date_range(start=date(int(start_year), int(start_month), 1), freq='M', periods=len(tsdata['data']))\n",
    "        tsdata['series'] = pd.Series(tsdata['data'],\n",
    "                                     index=index,\n",
    "                                     name='{code:s} {quant:s} ({province:s}) - {detail:s}'.format(\n",
    "                                        code=tsdata['tags']['H01'],\n",
    "                                        quant=tsdata['tags']['H02'],\n",
    "                                        detail=tsdata['tags']['H04'],\n",
    "                                        province=tsdata['tags']['H13']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the data\n",
    "\n",
    "Plotting the data shows that some of the indices have actually suffered deflation since 2008, but I'll look at that in another post. You'll also see that all the series converge at December 2012. That is because I'm plotting Consumper Price Index time series. These indices are all relative to December 2012, which was chosen to be the value 100. What this means is that if in January 2008 the index was at 300 for one of the time series, the price of that basket of goods was three times higher than in December 2015."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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VZh595OD/a6pryL/5NtSlpcdcdyoSZuaxR/Fu24rCZqPkG99ClZd3yDKRkQOM/ccPSYVD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\n/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s8c1QUKBkVqaIr81BTq5AS54WGygwNokchsGcFioei2Owq5hC/RvuSZONPHoWZDJMMH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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3a32dfda90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.plt.figure(figsize=(8,6))\n",
    "for tsdata in all_time_series:\n",
    "    tsdata['series'].plot()\n",
    "sns.plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Putting it into a DataFrame\n",
    "\n",
    "All of these time series have the same date range and frequency, i.e. monthly. Therefore, they can be combined into a single DataFrame. Here I'm going to make each time series into one column of the DataFrame. The column indices will be hierarchichal, using the province and detail, i.e. H13 and H04 tags."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"10\" halign=\"left\">All urban areas</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Western Cape</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Actual rentals for housing</th>\n",
       "      <th>Alcoholic beverages</th>\n",
       "      <th>Alcoholic beverages and tobacco</th>\n",
       "      <th>Analytical series - All urban areas</th>\n",
       "      <th>Appliances, tableware and equipment</th>\n",
       "      <th>Beer</th>\n",
       "      <th>Books, newspapers and stationery</th>\n",
       "      <th>Bread and cereals</th>\n",
       "      <th>CPI Headline</th>\n",
       "      <th>Clothing</th>\n",
       "      <th>...</th>\n",
       "      <th>Restaurants and hotels</th>\n",
       "      <th>Spirits</th>\n",
       "      <th>Sugar, sweets and deserts</th>\n",
       "      <th>Supplies and services</th>\n",
       "      <th>Telecommunication equipment</th>\n",
       "      <th>Tobacco</th>\n",
       "      <th>Transport</th>\n",
       "      <th>Vegetables</th>\n",
       "      <th>Water and other services</th>\n",
       "      <th>Wine</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-01-31</th>\n",
       "      <td>76.4</td>\n",
       "      <td>69.4</td>\n",
       "      <td>67.0</td>\n",
       "      <td>68.3</td>\n",
       "      <td>88.2</td>\n",
       "      <td>67.5</td>\n",
       "      <td>73.1</td>\n",
       "      <td>66.7</td>\n",
       "      <td>75.3</td>\n",
       "      <td>84.5</td>\n",
       "      <td>...</td>\n",
       "      <td>69.1</td>\n",
       "      <td>69.0</td>\n",
       "      <td>63.5</td>\n",
       "      <td>72.4</td>\n",
       "      <td>226.9</td>\n",
       "      <td>64.8</td>\n",
       "      <td>88.4</td>\n",
       "      <td>68.6</td>\n",
       "      <td>68.7</td>\n",
       "      <td>77.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-02-29</th>\n",
       "      <td>76.4</td>\n",
       "      <td>70.8</td>\n",
       "      <td>67.8</td>\n",
       "      <td>68.3</td>\n",
       "      <td>87.4</td>\n",
       "      <td>69.3</td>\n",
       "      <td>72.4</td>\n",
       "      <td>68.8</td>\n",
       "      <td>75.8</td>\n",
       "      <td>84.7</td>\n",
       "      <td>...</td>\n",
       "      <td>69.5</td>\n",
       "      <td>70.5</td>\n",
       "      <td>63.7</td>\n",
       "      <td>72.3</td>\n",
       "      <td>225.5</td>\n",
       "      <td>64.9</td>\n",
       "      <td>88.6</td>\n",
       "      <td>67.5</td>\n",
       "      <td>68.7</td>\n",
       "      <td>77.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-03-31</th>\n",
       "      <td>78.3</td>\n",
       "      <td>73.3</td>\n",
       "      <td>70.6</td>\n",
       "      <td>70.5</td>\n",
       "      <td>88.5</td>\n",
       "      <td>71.2</td>\n",
       "      <td>72.8</td>\n",
       "      <td>70.9</td>\n",
       "      <td>76.9</td>\n",
       "      <td>85.0</td>\n",
       "      <td>...</td>\n",
       "      <td>71.3</td>\n",
       "      <td>73.2</td>\n",
       "      <td>64.2</td>\n",
       "      <td>73.0</td>\n",
       "      <td>225.5</td>\n",
       "      <td>67.4</td>\n",
       "      <td>90.3</td>\n",
       "      <td>68.1</td>\n",
       "      <td>68.7</td>\n",
       "      <td>79.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-30</th>\n",
       "      <td>78.3</td>\n",
       "      <td>73.7</td>\n",
       "      <td>71.1</td>\n",
       "      <td>70.5</td>\n",
       "      <td>87.6</td>\n",
       "      <td>71.3</td>\n",
       "      <td>74.4</td>\n",
       "      <td>71.9</td>\n",
       "      <td>77.3</td>\n",
       "      <td>85.1</td>\n",
       "      <td>...</td>\n",
       "      <td>71.5</td>\n",
       "      <td>75.3</td>\n",
       "      <td>65.4</td>\n",
       "      <td>73.9</td>\n",
       "      <td>225.7</td>\n",
       "      <td>67.6</td>\n",
       "      <td>91.0</td>\n",
       "      <td>70.2</td>\n",
       "      <td>68.7</td>\n",
       "      <td>79.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-05-31</th>\n",
       "      <td>78.3</td>\n",
       "      <td>74.0</td>\n",
       "      <td>71.3</td>\n",
       "      <td>70.5</td>\n",
       "      <td>88.3</td>\n",
       "      <td>71.5</td>\n",
       "      <td>77.2</td>\n",
       "      <td>76.5</td>\n",
       "      <td>77.9</td>\n",
       "      <td>85.3</td>\n",
       "      <td>...</td>\n",
       "      <td>71.9</td>\n",
       "      <td>74.8</td>\n",
       "      <td>66.6</td>\n",
       "      <td>74.3</td>\n",
       "      <td>236.6</td>\n",
       "      <td>67.8</td>\n",
       "      <td>92.0</td>\n",
       "      <td>70.3</td>\n",
       "      <td>68.7</td>\n",
       "      <td>79.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-06-30</th>\n",
       "      <td>80.4</td>\n",
       "      <td>74.2</td>\n",
       "      <td>71.4</td>\n",
       "      <td>70.5</td>\n",
       "      <td>88.7</td>\n",
       "      <td>71.5</td>\n",
       "      <td>75.7</td>\n",
       "      <td>79.8</td>\n",
       "      <td>79.0</td>\n",
       "      <td>85.8</td>\n",
       "      <td>...</td>\n",
       "      <td>72.8</td>\n",
       "      <td>75.5</td>\n",
       "      <td>68.5</td>\n",
       "      <td>76.0</td>\n",
       "      <td>234.5</td>\n",
       "      <td>67.9</td>\n",
       "      <td>93.8</td>\n",
       "      <td>69.7</td>\n",
       "      <td>68.7</td>\n",
       "      <td>80.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-07-31</th>\n",
       "      <td>80.4</td>\n",
       "      <td>74.4</td>\n",
       "      <td>71.6</td>\n",
       "      <td>71.5</td>\n",
       "      <td>89.9</td>\n",
       "      <td>71.6</td>\n",
       "      <td>76.5</td>\n",
       "      <td>81.2</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73.9</td>\n",
       "      <td>76.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>76.1</td>\n",
       "      <td>228.7</td>\n",
       "      <td>67.9</td>\n",
       "      <td>95.3</td>\n",
       "      <td>72.0</td>\n",
       "      <td>73.1</td>\n",
       "      <td>81.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-08-31</th>\n",
       "      <td>80.4</td>\n",
       "      <td>74.6</td>\n",
       "      <td>72.6</td>\n",
       "      <td>71.6</td>\n",
       "      <td>91.8</td>\n",
       "      <td>71.5</td>\n",
       "      <td>77.9</td>\n",
       "      <td>83.5</td>\n",
       "      <td>80.5</td>\n",
       "      <td>86.5</td>\n",
       "      <td>...</td>\n",
       "      <td>74.5</td>\n",
       "      <td>76.2</td>\n",
       "      <td>70.2</td>\n",
       "      <td>76.2</td>\n",
       "      <td>229.6</td>\n",
       "      <td>69.0</td>\n",
       "      <td>94.5</td>\n",
       "      <td>74.9</td>\n",
       "      <td>73.1</td>\n",
       "      <td>82.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-30</th>\n",
       "      <td>81.3</td>\n",
       "      <td>75.1</td>\n",
       "      <td>73.4</td>\n",
       "      <td>71.6</td>\n",
       "      <td>92.8</td>\n",
       "      <td>72.2</td>\n",
       "      <td>76.4</td>\n",
       "      <td>85.3</td>\n",
       "      <td>81.0</td>\n",
       "      <td>86.8</td>\n",
       "      <td>...</td>\n",
       "      <td>75.0</td>\n",
       "      <td>76.6</td>\n",
       "      <td>74.6</td>\n",
       "      <td>77.7</td>\n",
       "      <td>211.7</td>\n",
       "      <td>71.6</td>\n",
       "      <td>93.8</td>\n",
       "      <td>73.3</td>\n",
       "      <td>73.1</td>\n",
       "      <td>82.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-31</th>\n",
       "      <td>81.3</td>\n",
       "      <td>75.1</td>\n",
       "      <td>73.6</td>\n",
       "      <td>71.6</td>\n",
       "      <td>93.0</td>\n",
       "      <td>72.1</td>\n",
       "      <td>76.3</td>\n",
       "      <td>85.4</td>\n",
       "      <td>81.1</td>\n",
       "      <td>86.9</td>\n",
       "      <td>...</td>\n",
       "      <td>77.6</td>\n",
       "      <td>76.5</td>\n",
       "      <td>76.3</td>\n",
       "      <td>77.8</td>\n",
       "      <td>223.9</td>\n",
       "      <td>71.6</td>\n",
       "      <td>93.5</td>\n",
       "      <td>78.6</td>\n",
       "      <td>73.1</td>\n",
       "      <td>82.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-11-30</th>\n",
       "      <td>81.3</td>\n",
       "      <td>75.1</td>\n",
       "      <td>73.7</td>\n",
       "      <td>71.6</td>\n",
       "      <td>93.3</td>\n",
       "      <td>72.2</td>\n",
       "      <td>81.4</td>\n",
       "      <td>85.6</td>\n",
       "      <td>81.2</td>\n",
       "      <td>87.0</td>\n",
       "      <td>...</td>\n",
       "      <td>77.6</td>\n",
       "      <td>76.1</td>\n",
       "      <td>76.5</td>\n",
       "      <td>78.0</td>\n",
       "      <td>217.6</td>\n",
       "      <td>71.8</td>\n",
       "      <td>92.3</td>\n",
       "      <td>76.2</td>\n",
       "      <td>73.1</td>\n",
       "      <td>82.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>82.5</td>\n",
       "      <td>75.1</td>\n",
       "      <td>73.8</td>\n",
       "      <td>71.6</td>\n",
       "      <td>93.4</td>\n",
       "      <td>72.2</td>\n",
       "      <td>79.5</td>\n",
       "      <td>85.6</td>\n",
       "      <td>81.1</td>\n",
       "      <td>87.4</td>\n",
       "      <td>...</td>\n",
       "      <td>78.5</td>\n",
       "      <td>77.3</td>\n",
       "      <td>75.4</td>\n",
       "      <td>78.6</td>\n",
       "      <td>222.8</td>\n",
       "      <td>71.8</td>\n",
       "      <td>89.5</td>\n",
       "      <td>82.0</td>\n",
       "      <td>73.1</td>\n",
       "      <td>81.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-31</th>\n",
       "      <td>82.5</td>\n",
       "      <td>75.4</td>\n",
       "      <td>73.9</td>\n",
       "      <td>71.7</td>\n",
       "      <td>97.7</td>\n",
       "      <td>72.2</td>\n",
       "      <td>79.6</td>\n",
       "      <td>85.4</td>\n",
       "      <td>81.4</td>\n",
       "      <td>88.1</td>\n",
       "      <td>...</td>\n",
       "      <td>78.6</td>\n",
       "      <td>77.4</td>\n",
       "      <td>77.2</td>\n",
       "      <td>79.3</td>\n",
       "      <td>230.7</td>\n",
       "      <td>71.8</td>\n",
       "      <td>86.5</td>\n",
       "      <td>83.4</td>\n",
       "      <td>73.1</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-02-28</th>\n",
       "      <td>82.5</td>\n",
       "      <td>76.1</td>\n",
       "      <td>74.7</td>\n",
       "      <td>71.7</td>\n",
       "      <td>100.2</td>\n",
       "      <td>73.2</td>\n",
       "      <td>80.7</td>\n",
       "      <td>85.2</td>\n",
       "      <td>82.3</td>\n",
       "      <td>89.0</td>\n",
       "      <td>...</td>\n",
       "      <td>79.2</td>\n",
       "      <td>77.1</td>\n",
       "      <td>77.0</td>\n",
       "      <td>79.5</td>\n",
       "      <td>227.3</td>\n",
       "      <td>72.3</td>\n",
       "      <td>88.2</td>\n",
       "      <td>80.3</td>\n",
       "      <td>73.1</td>\n",
       "      <td>81.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-03-31</th>\n",
       "      <td>83.4</td>\n",
       "      <td>79.8</td>\n",
       "      <td>78.2</td>\n",
       "      <td>75.3</td>\n",
       "      <td>101.5</td>\n",
       "      <td>77.0</td>\n",
       "      <td>82.3</td>\n",
       "      <td>85.0</td>\n",
       "      <td>83.4</td>\n",
       "      <td>89.5</td>\n",
       "      <td>...</td>\n",
       "      <td>80.3</td>\n",
       "      <td>82.1</td>\n",
       "      <td>78.5</td>\n",
       "      <td>81.3</td>\n",
       "      <td>227.8</td>\n",
       "      <td>75.3</td>\n",
       "      <td>89.2</td>\n",
       "      <td>80.2</td>\n",
       "      <td>73.1</td>\n",
       "      <td>84.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-30</th>\n",
       "      <td>83.4</td>\n",
       "      <td>80.5</td>\n",
       "      <td>78.8</td>\n",
       "      <td>75.4</td>\n",
       "      <td>102.3</td>\n",
       "      <td>77.4</td>\n",
       "      <td>83.7</td>\n",
       "      <td>84.8</td>\n",
       "      <td>83.8</td>\n",
       "      <td>89.9</td>\n",
       "      <td>...</td>\n",
       "      <td>80.7</td>\n",
       "      <td>83.0</td>\n",
       "      <td>79.6</td>\n",
       "      <td>81.3</td>\n",
       "      <td>226.0</td>\n",
       "      <td>75.5</td>\n",
       "      <td>90.2</td>\n",
       "      <td>81.6</td>\n",
       "      <td>73.1</td>\n",
       "      <td>85.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-05-31</th>\n",
       "      <td>83.4</td>\n",
       "      <td>80.7</td>\n",
       "      <td>78.9</td>\n",
       "      <td>75.4</td>\n",
       "      <td>102.5</td>\n",
       "      <td>77.4</td>\n",
       "      <td>83.5</td>\n",
       "      <td>84.7</td>\n",
       "      <td>84.1</td>\n",
       "      <td>90.0</td>\n",
       "      <td>...</td>\n",
       "      <td>80.8</td>\n",
       "      <td>83.8</td>\n",
       "      <td>80.5</td>\n",
       "      <td>81.7</td>\n",
       "      <td>222.3</td>\n",
       "      <td>76.0</td>\n",
       "      <td>90.8</td>\n",
       "      <td>83.4</td>\n",
       "      <td>73.1</td>\n",
       "      <td>86.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-06-30</th>\n",
       "      <td>84.9</td>\n",
       "      <td>80.6</td>\n",
       "      <td>78.9</td>\n",
       "      <td>75.4</td>\n",
       "      <td>102.8</td>\n",
       "      <td>77.2</td>\n",
       "      <td>81.2</td>\n",
       "      <td>84.6</td>\n",
       "      <td>84.5</td>\n",
       "      <td>90.2</td>\n",
       "      <td>...</td>\n",
       "      <td>81.5</td>\n",
       "      <td>84.0</td>\n",
       "      <td>81.1</td>\n",
       "      <td>83.5</td>\n",
       "      <td>215.1</td>\n",
       "      <td>76.1</td>\n",
       "      <td>91.4</td>\n",
       "      <td>82.5</td>\n",
       "      <td>73.1</td>\n",
       "      <td>86.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-07-31</th>\n",
       "      <td>84.9</td>\n",
       "      <td>80.8</td>\n",
       "      <td>79.8</td>\n",
       "      <td>78.2</td>\n",
       "      <td>101.9</td>\n",
       "      <td>77.3</td>\n",
       "      <td>82.3</td>\n",
       "      <td>84.2</td>\n",
       "      <td>85.4</td>\n",
       "      <td>90.7</td>\n",
       "      <td>...</td>\n",
       "      <td>81.5</td>\n",
       "      <td>84.2</td>\n",
       "      <td>80.9</td>\n",
       "      <td>83.8</td>\n",
       "      <td>213.3</td>\n",
       "      <td>78.5</td>\n",
       "      <td>91.5</td>\n",
       "      <td>81.9</td>\n",
       "      <td>80.1</td>\n",
       "      <td>86.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-08-31</th>\n",
       "      <td>84.9</td>\n",
       "      <td>80.8</td>\n",
       "      <td>81.8</td>\n",
       "      <td>78.6</td>\n",
       "      <td>102.1</td>\n",
       "      <td>77.1</td>\n",
       "      <td>82.3</td>\n",
       "      <td>83.8</td>\n",
       "      <td>85.6</td>\n",
       "      <td>91.1</td>\n",
       "      <td>...</td>\n",
       "      <td>81.5</td>\n",
       "      <td>84.1</td>\n",
       "      <td>80.6</td>\n",
       "      <td>83.8</td>\n",
       "      <td>210.4</td>\n",
       "      <td>83.2</td>\n",
       "      <td>91.3</td>\n",
       "      <td>84.0</td>\n",
       "      <td>80.1</td>\n",
       "      <td>86.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-09-30</th>\n",
       "      <td>85.7</td>\n",
       "      <td>81.0</td>\n",
       "      <td>82.1</td>\n",
       "      <td>78.6</td>\n",
       "      <td>101.6</td>\n",
       "      <td>77.2</td>\n",
       "      <td>84.4</td>\n",
       "      <td>83.5</td>\n",
       "      <td>86.0</td>\n",
       "      <td>91.3</td>\n",
       "      <td>...</td>\n",
       "      <td>81.9</td>\n",
       "      <td>84.3</td>\n",
       "      <td>81.6</td>\n",
       "      <td>84.2</td>\n",
       "      <td>200.2</td>\n",
       "      <td>83.2</td>\n",
       "      <td>91.6</td>\n",
       "      <td>86.3</td>\n",
       "      <td>80.1</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-10-31</th>\n",
       "      <td>85.7</td>\n",
       "      <td>81.0</td>\n",
       "      <td>82.1</td>\n",
       "      <td>78.6</td>\n",
       "      <td>100.9</td>\n",
       "      <td>77.2</td>\n",
       "      <td>85.1</td>\n",
       "      <td>83.3</td>\n",
       "      <td>86.0</td>\n",
       "      <td>91.5</td>\n",
       "      <td>...</td>\n",
       "      <td>83.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>84.4</td>\n",
       "      <td>193.5</td>\n",
       "      <td>83.3</td>\n",
       "      <td>91.0</td>\n",
       "      <td>92.9</td>\n",
       "      <td>80.1</td>\n",
       "      <td>87.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-11-30</th>\n",
       "      <td>85.7</td>\n",
       "      <td>81.0</td>\n",
       "      <td>82.1</td>\n",
       "      <td>78.6</td>\n",
       "      <td>99.9</td>\n",
       "      <td>77.1</td>\n",
       "      <td>86.8</td>\n",
       "      <td>83.1</td>\n",
       "      <td>86.0</td>\n",
       "      <td>91.6</td>\n",
       "      <td>...</td>\n",
       "      <td>83.1</td>\n",
       "      <td>84.0</td>\n",
       "      <td>82.2</td>\n",
       "      <td>84.7</td>\n",
       "      <td>187.8</td>\n",
       "      <td>83.5</td>\n",
       "      <td>90.8</td>\n",
       "      <td>90.0</td>\n",
       "      <td>80.1</td>\n",
       "      <td>87.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>86.5</td>\n",
       "      <td>80.9</td>\n",
       "      <td>82.1</td>\n",
       "      <td>78.6</td>\n",
       "      <td>99.4</td>\n",
       "      <td>77.1</td>\n",
       "      <td>88.4</td>\n",
       "      <td>82.9</td>\n",
       "      <td>86.2</td>\n",
       "      <td>91.7</td>\n",
       "      <td>...</td>\n",
       "      <td>83.7</td>\n",
       "      <td>83.9</td>\n",
       "      <td>80.9</td>\n",
       "      <td>84.9</td>\n",
       "      <td>186.0</td>\n",
       "      <td>83.5</td>\n",
       "      <td>91.1</td>\n",
       "      <td>87.5</td>\n",
       "      <td>80.1</td>\n",
       "      <td>87.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-31</th>\n",
       "      <td>86.5</td>\n",
       "      <td>81.1</td>\n",
       "      <td>82.3</td>\n",
       "      <td>78.6</td>\n",
       "      <td>99.8</td>\n",
       "      <td>77.2</td>\n",
       "      <td>86.4</td>\n",
       "      <td>82.9</td>\n",
       "      <td>86.4</td>\n",
       "      <td>91.8</td>\n",
       "      <td>...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>83.9</td>\n",
       "      <td>82.1</td>\n",
       "      <td>84.9</td>\n",
       "      <td>183.1</td>\n",
       "      <td>83.5</td>\n",
       "      <td>90.8</td>\n",
       "      <td>87.0</td>\n",
       "      <td>80.1</td>\n",
       "      <td>87.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-02-28</th>\n",
       "      <td>86.5</td>\n",
       "      <td>81.2</td>\n",
       "      <td>82.3</td>\n",
       "      <td>78.6</td>\n",
       "      <td>99.0</td>\n",
       "      <td>77.4</td>\n",
       "      <td>85.2</td>\n",
       "      <td>82.7</td>\n",
       "      <td>87.0</td>\n",
       "      <td>91.8</td>\n",
       "      <td>...</td>\n",
       "      <td>85.2</td>\n",
       "      <td>84.2</td>\n",
       "      <td>82.5</td>\n",
       "      <td>85.0</td>\n",
       "      <td>174.7</td>\n",
       "      <td>83.5</td>\n",
       "      <td>91.3</td>\n",
       "      <td>83.3</td>\n",
       "      <td>80.1</td>\n",
       "      <td>87.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-03-31</th>\n",
       "      <td>87.4</td>\n",
       "      <td>85.2</td>\n",
       "      <td>87.0</td>\n",
       "      <td>82.2</td>\n",
       "      <td>99.1</td>\n",
       "      <td>82.3</td>\n",
       "      <td>90.0</td>\n",
       "      <td>82.4</td>\n",
       "      <td>87.7</td>\n",
       "      <td>91.8</td>\n",
       "      <td>...</td>\n",
       "      <td>86.2</td>\n",
       "      <td>86.8</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85.8</td>\n",
       "      <td>167.9</td>\n",
       "      <td>89.8</td>\n",
       "      <td>91.6</td>\n",
       "      <td>82.5</td>\n",
       "      <td>80.1</td>\n",
       "      <td>90.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04-30</th>\n",
       "      <td>87.4</td>\n",
       "      <td>85.5</td>\n",
       "      <td>87.3</td>\n",
       "      <td>82.4</td>\n",
       "      <td>98.7</td>\n",
       "      <td>82.3</td>\n",
       "      <td>85.5</td>\n",
       "      <td>82.3</td>\n",
       "      <td>87.8</td>\n",
       "      <td>91.9</td>\n",
       "      <td>...</td>\n",
       "      <td>85.9</td>\n",
       "      <td>87.7</td>\n",
       "      <td>84.3</td>\n",
       "      <td>85.7</td>\n",
       "      <td>163.7</td>\n",
       "      <td>89.6</td>\n",
       "      <td>92.8</td>\n",
       "      <td>82.7</td>\n",
       "      <td>80.1</td>\n",
       "      <td>91.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-05-31</th>\n",
       "      <td>87.4</td>\n",
       "      <td>85.9</td>\n",
       "      <td>87.6</td>\n",
       "      <td>82.4</td>\n",
       "      <td>98.6</td>\n",
       "      <td>82.7</td>\n",
       "      <td>85.8</td>\n",
       "      <td>82.2</td>\n",
       "      <td>88.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>...</td>\n",
       "      <td>86.2</td>\n",
       "      <td>88.5</td>\n",
       "      <td>85.8</td>\n",
       "      <td>85.8</td>\n",
       "      <td>159.1</td>\n",
       "      <td>89.6</td>\n",
       "      <td>92.9</td>\n",
       "      <td>84.5</td>\n",
       "      <td>80.1</td>\n",
       "      <td>92.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-06-30</th>\n",
       "      <td>88.7</td>\n",
       "      <td>85.7</td>\n",
       "      <td>87.4</td>\n",
       "      <td>82.4</td>\n",
       "      <td>99.0</td>\n",
       "      <td>82.3</td>\n",
       "      <td>84.8</td>\n",
       "      <td>81.6</td>\n",
       "      <td>88.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>...</td>\n",
       "      <td>87.9</td>\n",
       "      <td>88.8</td>\n",
       "      <td>84.3</td>\n",
       "      <td>87.2</td>\n",
       "      <td>155.8</td>\n",
       "      <td>89.6</td>\n",
       "      <td>92.3</td>\n",
       "      <td>85.1</td>\n",
       "      <td>80.1</td>\n",
       "      <td>92.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06-30</th>\n",
       "      <td>102.7</td>\n",
       "      <td>106.3</td>\n",
       "      <td>105.6</td>\n",
       "      <td>106.1</td>\n",
       "      <td>100.4</td>\n",
       "      <td>106.6</td>\n",
       "      <td>103.3</td>\n",
       "      <td>100.7</td>\n",
       "      <td>102.9</td>\n",
       "      <td>101.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100.9</td>\n",
       "      <td>105.6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>103.2</td>\n",
       "      <td>93.4</td>\n",
       "      <td>103.5</td>\n",
       "      <td>102.0</td>\n",
       "      <td>102.9</td>\n",
       "      <td>100.0</td>\n",
       "      <td>105.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-31</th>\n",
       "      <td>102.7</td>\n",
       "      <td>106.8</td>\n",
       "      <td>106.4</td>\n",
       "      <td>107.8</td>\n",
       "      <td>100.7</td>\n",
       "      <td>107.0</td>\n",
       "      <td>101.9</td>\n",
       "      <td>101.4</td>\n",
       "      <td>104.0</td>\n",
       "      <td>101.4</td>\n",
       "      <td>...</td>\n",
       "      <td>101.5</td>\n",
       "      <td>106.1</td>\n",
       "      <td>104.0</td>\n",
       "      <td>103.2</td>\n",
       "      <td>94.6</td>\n",
       "      <td>105.2</td>\n",
       "      <td>105.0</td>\n",
       "      <td>101.4</td>\n",
       "      <td>108.2</td>\n",
       "      <td>105.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-08-31</th>\n",
       "      <td>102.7</td>\n",
       "      <td>106.6</td>\n",
       "      <td>106.4</td>\n",
       "      <td>107.8</td>\n",
       "      <td>101.2</td>\n",
       "      <td>107.2</td>\n",
       "      <td>103.7</td>\n",
       "      <td>102.5</td>\n",
       "      <td>104.3</td>\n",
       "      <td>102.2</td>\n",
       "      <td>...</td>\n",
       "      <td>103.0</td>\n",
       "      <td>105.8</td>\n",
       "      <td>104.5</td>\n",
       "      <td>103.4</td>\n",
       "      <td>93.8</td>\n",
       "      <td>105.5</td>\n",
       "      <td>106.3</td>\n",
       "      <td>101.5</td>\n",
       "      <td>108.2</td>\n",
       "      <td>102.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09-30</th>\n",
       "      <td>103.9</td>\n",
       "      <td>107.0</td>\n",
       "      <td>106.7</td>\n",
       "      <td>107.9</td>\n",
       "      <td>102.1</td>\n",
       "      <td>107.1</td>\n",
       "      <td>105.1</td>\n",
       "      <td>104.0</td>\n",
       "      <td>104.8</td>\n",
       "      <td>102.8</td>\n",
       "      <td>...</td>\n",
       "      <td>105.3</td>\n",
       "      <td>107.0</td>\n",
       "      <td>104.6</td>\n",
       "      <td>104.9</td>\n",
       "      <td>94.3</td>\n",
       "      <td>104.2</td>\n",
       "      <td>106.4</td>\n",
       "      <td>104.0</td>\n",
       "      <td>108.2</td>\n",
       "      <td>105.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10-31</th>\n",
       "      <td>103.9</td>\n",
       "      <td>108.0</td>\n",
       "      <td>107.4</td>\n",
       "      <td>107.9</td>\n",
       "      <td>102.1</td>\n",
       "      <td>108.7</td>\n",
       "      <td>104.9</td>\n",
       "      <td>104.4</td>\n",
       "      <td>105.0</td>\n",
       "      <td>103.1</td>\n",
       "      <td>...</td>\n",
       "      <td>106.7</td>\n",
       "      <td>106.8</td>\n",
       "      <td>104.5</td>\n",
       "      <td>105.2</td>\n",
       "      <td>92.5</td>\n",
       "      <td>103.4</td>\n",
       "      <td>106.0</td>\n",
       "      <td>106.2</td>\n",
       "      <td>108.2</td>\n",
       "      <td>105.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-11-30</th>\n",
       "      <td>103.9</td>\n",
       "      <td>107.6</td>\n",
       "      <td>106.9</td>\n",
       "      <td>107.9</td>\n",
       "      <td>103.1</td>\n",
       "      <td>108.8</td>\n",
       "      <td>105.3</td>\n",
       "      <td>104.1</td>\n",
       "      <td>105.1</td>\n",
       "      <td>103.3</td>\n",
       "      <td>...</td>\n",
       "      <td>109.1</td>\n",
       "      <td>106.3</td>\n",
       "      <td>105.9</td>\n",
       "      <td>105.3</td>\n",
       "      <td>91.8</td>\n",
       "      <td>103.3</td>\n",
       "      <td>105.1</td>\n",
       "      <td>108.9</td>\n",
       "      <td>108.2</td>\n",
       "      <td>102.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>105.0</td>\n",
       "      <td>107.6</td>\n",
       "      <td>107.1</td>\n",
       "      <td>107.9</td>\n",
       "      <td>102.5</td>\n",
       "      <td>109.2</td>\n",
       "      <td>105.8</td>\n",
       "      <td>104.3</td>\n",
       "      <td>105.4</td>\n",
       "      <td>103.6</td>\n",
       "      <td>...</td>\n",
       "      <td>109.5</td>\n",
       "      <td>105.5</td>\n",
       "      <td>104.6</td>\n",
       "      <td>105.9</td>\n",
       "      <td>88.3</td>\n",
       "      <td>104.2</td>\n",
       "      <td>105.9</td>\n",
       "      <td>105.4</td>\n",
       "      <td>108.2</td>\n",
       "      <td>102.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-31</th>\n",
       "      <td>105.0</td>\n",
       "      <td>108.5</td>\n",
       "      <td>107.6</td>\n",
       "      <td>108.1</td>\n",
       "      <td>102.9</td>\n",
       "      <td>109.6</td>\n",
       "      <td>110.7</td>\n",
       "      <td>105.3</td>\n",
       "      <td>106.1</td>\n",
       "      <td>104.0</td>\n",
       "      <td>...</td>\n",
       "      <td>112.0</td>\n",
       "      <td>107.1</td>\n",
       "      <td>105.5</td>\n",
       "      <td>105.7</td>\n",
       "      <td>87.2</td>\n",
       "      <td>102.9</td>\n",
       "      <td>107.1</td>\n",
       "      <td>110.5</td>\n",
       "      <td>108.2</td>\n",
       "      <td>104.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-02-28</th>\n",
       "      <td>105.0</td>\n",
       "      <td>108.9</td>\n",
       "      <td>107.9</td>\n",
       "      <td>108.1</td>\n",
       "      <td>103.4</td>\n",
       "      <td>110.3</td>\n",
       "      <td>110.7</td>\n",
       "      <td>107.2</td>\n",
       "      <td>107.3</td>\n",
       "      <td>104.8</td>\n",
       "      <td>...</td>\n",
       "      <td>113.2</td>\n",
       "      <td>106.8</td>\n",
       "      <td>106.4</td>\n",
       "      <td>105.8</td>\n",
       "      <td>87.6</td>\n",
       "      <td>102.9</td>\n",
       "      <td>108.8</td>\n",
       "      <td>109.2</td>\n",
       "      <td>108.2</td>\n",
       "      <td>104.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-03-31</th>\n",
       "      <td>106.4</td>\n",
       "      <td>110.7</td>\n",
       "      <td>110.1</td>\n",
       "      <td>114.1</td>\n",
       "      <td>103.6</td>\n",
       "      <td>110.7</td>\n",
       "      <td>113.2</td>\n",
       "      <td>108.5</td>\n",
       "      <td>108.7</td>\n",
       "      <td>105.3</td>\n",
       "      <td>...</td>\n",
       "      <td>113.9</td>\n",
       "      <td>110.3</td>\n",
       "      <td>109.9</td>\n",
       "      <td>106.9</td>\n",
       "      <td>88.2</td>\n",
       "      <td>106.2</td>\n",
       "      <td>110.8</td>\n",
       "      <td>110.4</td>\n",
       "      <td>108.2</td>\n",
       "      <td>107.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-30</th>\n",
       "      <td>106.4</td>\n",
       "      <td>111.5</td>\n",
       "      <td>110.8</td>\n",
       "      <td>114.2</td>\n",
       "      <td>104.1</td>\n",
       "      <td>111.4</td>\n",
       "      <td>114.6</td>\n",
       "      <td>110.3</td>\n",
       "      <td>109.2</td>\n",
       "      <td>105.8</td>\n",
       "      <td>...</td>\n",
       "      <td>113.4</td>\n",
       "      <td>112.0</td>\n",
       "      <td>110.2</td>\n",
       "      <td>107.2</td>\n",
       "      <td>86.9</td>\n",
       "      <td>106.4</td>\n",
       "      <td>111.1</td>\n",
       "      <td>111.7</td>\n",
       "      <td>108.2</td>\n",
       "      <td>106.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-31</th>\n",
       "      <td>106.4</td>\n",
       "      <td>112.2</td>\n",
       "      <td>111.3</td>\n",
       "      <td>114.2</td>\n",
       "      <td>104.4</td>\n",
       "      <td>111.8</td>\n",
       "      <td>114.6</td>\n",
       "      <td>110.9</td>\n",
       "      <td>109.4</td>\n",
       "      <td>106.2</td>\n",
       "      <td>...</td>\n",
       "      <td>113.5</td>\n",
       "      <td>115.5</td>\n",
       "      <td>110.4</td>\n",
       "      <td>106.9</td>\n",
       "      <td>85.7</td>\n",
       "      <td>106.7</td>\n",
       "      <td>110.8</td>\n",
       "      <td>113.3</td>\n",
       "      <td>108.2</td>\n",
       "      <td>107.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-06-30</th>\n",
       "      <td>108.0</td>\n",
       "      <td>112.5</td>\n",
       "      <td>111.5</td>\n",
       "      <td>114.4</td>\n",
       "      <td>105.1</td>\n",
       "      <td>112.3</td>\n",
       "      <td>114.5</td>\n",
       "      <td>111.3</td>\n",
       "      <td>109.7</td>\n",
       "      <td>106.4</td>\n",
       "      <td>...</td>\n",
       "      <td>111.9</td>\n",
       "      <td>115.9</td>\n",
       "      <td>111.8</td>\n",
       "      <td>108.6</td>\n",
       "      <td>85.9</td>\n",
       "      <td>106.7</td>\n",
       "      <td>110.0</td>\n",
       "      <td>111.9</td>\n",
       "      <td>108.2</td>\n",
       "      <td>107.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-07-31</th>\n",
       "      <td>108.0</td>\n",
       "      <td>112.4</td>\n",
       "      <td>112.6</td>\n",
       "      <td>116.6</td>\n",
       "      <td>104.8</td>\n",
       "      <td>112.2</td>\n",
       "      <td>115.3</td>\n",
       "      <td>110.2</td>\n",
       "      <td>110.6</td>\n",
       "      <td>106.8</td>\n",
       "      <td>...</td>\n",
       "      <td>110.9</td>\n",
       "      <td>116.3</td>\n",
       "      <td>112.1</td>\n",
       "      <td>108.4</td>\n",
       "      <td>86.4</td>\n",
       "      <td>109.8</td>\n",
       "      <td>111.2</td>\n",
       "      <td>112.2</td>\n",
       "      <td>116.4</td>\n",
       "      <td>108.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>108.0</td>\n",
       "      <td>112.6</td>\n",
       "      <td>112.9</td>\n",
       "      <td>116.6</td>\n",
       "      <td>105.3</td>\n",
       "      <td>112.1</td>\n",
       "      <td>114.8</td>\n",
       "      <td>110.4</td>\n",
       "      <td>111.0</td>\n",
       "      <td>107.8</td>\n",
       "      <td>...</td>\n",
       "      <td>112.4</td>\n",
       "      <td>115.4</td>\n",
       "      <td>115.4</td>\n",
       "      <td>108.7</td>\n",
       "      <td>82.1</td>\n",
       "      <td>111.4</td>\n",
       "      <td>111.4</td>\n",
       "      <td>116.3</td>\n",
       "      <td>116.4</td>\n",
       "      <td>108.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-30</th>\n",
       "      <td>109.3</td>\n",
       "      <td>112.7</td>\n",
       "      <td>113.1</td>\n",
       "      <td>116.6</td>\n",
       "      <td>105.5</td>\n",
       "      <td>112.5</td>\n",
       "      <td>115.3</td>\n",
       "      <td>110.1</td>\n",
       "      <td>111.0</td>\n",
       "      <td>108.5</td>\n",
       "      <td>...</td>\n",
       "      <td>114.8</td>\n",
       "      <td>116.3</td>\n",
       "      <td>115.6</td>\n",
       "      <td>109.6</td>\n",
       "      <td>81.5</td>\n",
       "      <td>111.6</td>\n",
       "      <td>109.4</td>\n",
       "      <td>116.8</td>\n",
       "      <td>116.4</td>\n",
       "      <td>108.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-10-31</th>\n",
       "      <td>109.3</td>\n",
       "      <td>114.8</td>\n",
       "      <td>114.6</td>\n",
       "      <td>116.6</td>\n",
       "      <td>105.3</td>\n",
       "      <td>115.4</td>\n",
       "      <td>115.8</td>\n",
       "      <td>109.8</td>\n",
       "      <td>111.2</td>\n",
       "      <td>109.2</td>\n",
       "      <td>...</td>\n",
       "      <td>117.8</td>\n",
       "      <td>116.6</td>\n",
       "      <td>115.8</td>\n",
       "      <td>109.8</td>\n",
       "      <td>80.3</td>\n",
       "      <td>111.5</td>\n",
       "      <td>109.6</td>\n",
       "      <td>115.4</td>\n",
       "      <td>116.4</td>\n",
       "      <td>107.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-11-30</th>\n",
       "      <td>109.3</td>\n",
       "      <td>115.4</td>\n",
       "      <td>115.2</td>\n",
       "      <td>116.6</td>\n",
       "      <td>105.3</td>\n",
       "      <td>116.4</td>\n",
       "      <td>116.6</td>\n",
       "      <td>109.8</td>\n",
       "      <td>111.2</td>\n",
       "      <td>109.9</td>\n",
       "      <td>...</td>\n",
       "      <td>119.5</td>\n",
       "      <td>116.1</td>\n",
       "      <td>116.1</td>\n",
       "      <td>109.9</td>\n",
       "      <td>79.8</td>\n",
       "      <td>111.5</td>\n",
       "      <td>108.1</td>\n",
       "      <td>114.6</td>\n",
       "      <td>116.4</td>\n",
       "      <td>108.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>110.3</td>\n",
       "      <td>115.4</td>\n",
       "      <td>115.2</td>\n",
       "      <td>116.6</td>\n",
       "      <td>104.4</td>\n",
       "      <td>116.6</td>\n",
       "      <td>117.9</td>\n",
       "      <td>109.4</td>\n",
       "      <td>111.0</td>\n",
       "      <td>110.3</td>\n",
       "      <td>...</td>\n",
       "      <td>118.7</td>\n",
       "      <td>116.5</td>\n",
       "      <td>113.7</td>\n",
       "      <td>110.1</td>\n",
       "      <td>79.2</td>\n",
       "      <td>111.8</td>\n",
       "      <td>106.1</td>\n",
       "      <td>110.2</td>\n",
       "      <td>116.4</td>\n",
       "      <td>108.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-31</th>\n",
       "      <td>110.3</td>\n",
       "      <td>116.1</td>\n",
       "      <td>115.6</td>\n",
       "      <td>116.6</td>\n",
       "      <td>105.1</td>\n",
       "      <td>117.2</td>\n",
       "      <td>118.6</td>\n",
       "      <td>110.0</td>\n",
       "      <td>110.8</td>\n",
       "      <td>110.7</td>\n",
       "      <td>...</td>\n",
       "      <td>119.1</td>\n",
       "      <td>117.6</td>\n",
       "      <td>115.6</td>\n",
       "      <td>111.1</td>\n",
       "      <td>77.6</td>\n",
       "      <td>111.8</td>\n",
       "      <td>102.2</td>\n",
       "      <td>109.2</td>\n",
       "      <td>116.4</td>\n",
       "      <td>108.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28</th>\n",
       "      <td>110.3</td>\n",
       "      <td>117.7</td>\n",
       "      <td>116.8</td>\n",
       "      <td>116.6</td>\n",
       "      <td>106.3</td>\n",
       "      <td>119.7</td>\n",
       "      <td>120.4</td>\n",
       "      <td>111.5</td>\n",
       "      <td>111.5</td>\n",
       "      <td>111.2</td>\n",
       "      <td>...</td>\n",
       "      <td>119.0</td>\n",
       "      <td>118.3</td>\n",
       "      <td>116.7</td>\n",
       "      <td>111.4</td>\n",
       "      <td>77.5</td>\n",
       "      <td>111.3</td>\n",
       "      <td>99.2</td>\n",
       "      <td>109.8</td>\n",
       "      <td>116.4</td>\n",
       "      <td>108.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-31</th>\n",
       "      <td>112.0</td>\n",
       "      <td>120.7</td>\n",
       "      <td>120.0</td>\n",
       "      <td>123.6</td>\n",
       "      <td>106.4</td>\n",
       "      <td>122.6</td>\n",
       "      <td>121.0</td>\n",
       "      <td>112.5</td>\n",
       "      <td>113.1</td>\n",
       "      <td>111.6</td>\n",
       "      <td>...</td>\n",
       "      <td>120.8</td>\n",
       "      <td>121.0</td>\n",
       "      <td>119.6</td>\n",
       "      <td>112.3</td>\n",
       "      <td>74.7</td>\n",
       "      <td>114.5</td>\n",
       "      <td>102.9</td>\n",
       "      <td>111.4</td>\n",
       "      <td>116.4</td>\n",
       "      <td>110.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-30</th>\n",
       "      <td>112.0</td>\n",
       "      <td>122.3</td>\n",
       "      <td>121.4</td>\n",
       "      <td>123.8</td>\n",
       "      <td>106.8</td>\n",
       "      <td>124.4</td>\n",
       "      <td>121.2</td>\n",
       "      <td>113.0</td>\n",
       "      <td>114.1</td>\n",
       "      <td>111.9</td>\n",
       "      <td>...</td>\n",
       "      <td>118.1</td>\n",
       "      <td>123.3</td>\n",
       "      <td>121.2</td>\n",
       "      <td>112.5</td>\n",
       "      <td>75.2</td>\n",
       "      <td>115.0</td>\n",
       "      <td>108.6</td>\n",
       "      <td>113.3</td>\n",
       "      <td>116.4</td>\n",
       "      <td>113.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05-31</th>\n",
       "      <td>112.0</td>\n",
       "      <td>123.2</td>\n",
       "      <td>122.1</td>\n",
       "      <td>123.8</td>\n",
       "      <td>107.7</td>\n",
       "      <td>125.1</td>\n",
       "      <td>122.8</td>\n",
       "      <td>115.1</td>\n",
       "      <td>114.4</td>\n",
       "      <td>112.2</td>\n",
       "      <td>...</td>\n",
       "      <td>117.2</td>\n",
       "      <td>125.0</td>\n",
       "      <td>122.4</td>\n",
       "      <td>112.7</td>\n",
       "      <td>73.2</td>\n",
       "      <td>114.9</td>\n",
       "      <td>108.7</td>\n",
       "      <td>112.9</td>\n",
       "      <td>116.4</td>\n",
       "      <td>114.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-30</th>\n",
       "      <td>113.2</td>\n",
       "      <td>123.5</td>\n",
       "      <td>122.3</td>\n",
       "      <td>123.9</td>\n",
       "      <td>107.8</td>\n",
       "      <td>125.6</td>\n",
       "      <td>124.2</td>\n",
       "      <td>114.9</td>\n",
       "      <td>114.9</td>\n",
       "      <td>112.6</td>\n",
       "      <td>...</td>\n",
       "      <td>116.7</td>\n",
       "      <td>124.8</td>\n",
       "      <td>123.0</td>\n",
       "      <td>114.5</td>\n",
       "      <td>74.1</td>\n",
       "      <td>115.3</td>\n",
       "      <td>110.6</td>\n",
       "      <td>111.0</td>\n",
       "      <td>116.4</td>\n",
       "      <td>114.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-07-31</th>\n",
       "      <td>113.2</td>\n",
       "      <td>123.8</td>\n",
       "      <td>122.6</td>\n",
       "      <td>126.5</td>\n",
       "      <td>107.7</td>\n",
       "      <td>125.7</td>\n",
       "      <td>123.1</td>\n",
       "      <td>115.5</td>\n",
       "      <td>116.1</td>\n",
       "      <td>113.0</td>\n",
       "      <td>...</td>\n",
       "      <td>117.1</td>\n",
       "      <td>124.7</td>\n",
       "      <td>121.2</td>\n",
       "      <td>114.5</td>\n",
       "      <td>71.0</td>\n",
       "      <td>115.4</td>\n",
       "      <td>112.3</td>\n",
       "      <td>112.0</td>\n",
       "      <td>127.4</td>\n",
       "      <td>114.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08-31</th>\n",
       "      <td>113.2</td>\n",
       "      <td>124.1</td>\n",
       "      <td>122.8</td>\n",
       "      <td>126.5</td>\n",
       "      <td>108.5</td>\n",
       "      <td>126.1</td>\n",
       "      <td>124.5</td>\n",
       "      <td>116.9</td>\n",
       "      <td>116.1</td>\n",
       "      <td>113.6</td>\n",
       "      <td>...</td>\n",
       "      <td>117.5</td>\n",
       "      <td>124.8</td>\n",
       "      <td>123.4</td>\n",
       "      <td>114.7</td>\n",
       "      <td>68.5</td>\n",
       "      <td>115.4</td>\n",
       "      <td>110.5</td>\n",
       "      <td>112.5</td>\n",
       "      <td>127.4</td>\n",
       "      <td>115.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-30</th>\n",
       "      <td>114.7</td>\n",
       "      <td>124.3</td>\n",
       "      <td>122.9</td>\n",
       "      <td>126.5</td>\n",
       "      <td>107.9</td>\n",
       "      <td>126.2</td>\n",
       "      <td>125.7</td>\n",
       "      <td>117.1</td>\n",
       "      <td>116.1</td>\n",
       "      <td>114.1</td>\n",
       "      <td>...</td>\n",
       "      <td>119.8</td>\n",
       "      <td>124.8</td>\n",
       "      <td>124.0</td>\n",
       "      <td>114.8</td>\n",
       "      <td>67.8</td>\n",
       "      <td>115.4</td>\n",
       "      <td>108.3</td>\n",
       "      <td>113.5</td>\n",
       "      <td>127.4</td>\n",
       "      <td>115.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-31</th>\n",
       "      <td>114.7</td>\n",
       "      <td>124.5</td>\n",
       "      <td>123.1</td>\n",
       "      <td>126.5</td>\n",
       "      <td>108.7</td>\n",
       "      <td>126.4</td>\n",
       "      <td>126.7</td>\n",
       "      <td>117.6</td>\n",
       "      <td>116.4</td>\n",
       "      <td>114.5</td>\n",
       "      <td>...</td>\n",
       "      <td>121.8</td>\n",
       "      <td>124.8</td>\n",
       "      <td>125.2</td>\n",
       "      <td>115.1</td>\n",
       "      <td>67.7</td>\n",
       "      <td>115.3</td>\n",
       "      <td>108.7</td>\n",
       "      <td>116.6</td>\n",
       "      <td>127.4</td>\n",
       "      <td>114.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-30</th>\n",
       "      <td>114.7</td>\n",
       "      <td>124.6</td>\n",
       "      <td>123.3</td>\n",
       "      <td>126.6</td>\n",
       "      <td>109.1</td>\n",
       "      <td>126.5</td>\n",
       "      <td>126.8</td>\n",
       "      <td>117.8</td>\n",
       "      <td>116.5</td>\n",
       "      <td>115.0</td>\n",
       "      <td>...</td>\n",
       "      <td>124.8</td>\n",
       "      <td>124.2</td>\n",
       "      <td>125.5</td>\n",
       "      <td>115.1</td>\n",
       "      <td>67.6</td>\n",
       "      <td>116.2</td>\n",
       "      <td>108.1</td>\n",
       "      <td>114.7</td>\n",
       "      <td>127.4</td>\n",
       "      <td>116.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>95 rows × 849 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      All urban areas                      \\\n",
       "           Actual rentals for housing Alcoholic beverages   \n",
       "2008-01-31                       76.4                69.4   \n",
       "2008-02-29                       76.4                70.8   \n",
       "2008-03-31                       78.3                73.3   \n",
       "2008-04-30                       78.3                73.7   \n",
       "2008-05-31                       78.3                74.0   \n",
       "2008-06-30                       80.4                74.2   \n",
       "2008-07-31                       80.4                74.4   \n",
       "2008-08-31                       80.4                74.6   \n",
       "2008-09-30                       81.3                75.1   \n",
       "2008-10-31                       81.3                75.1   \n",
       "2008-11-30                       81.3                75.1   \n",
       "2008-12-31                       82.5                75.1   \n",
       "2009-01-31                       82.5                75.4   \n",
       "2009-02-28                       82.5                76.1   \n",
       "2009-03-31                       83.4                79.8   \n",
       "2009-04-30                       83.4                80.5   \n",
       "2009-05-31                       83.4                80.7   \n",
       "2009-06-30                       84.9                80.6   \n",
       "2009-07-31                       84.9                80.8   \n",
       "2009-08-31                       84.9                80.8   \n",
       "2009-09-30                       85.7                81.0   \n",
       "2009-10-31                       85.7                81.0   \n",
       "2009-11-30                       85.7                81.0   \n",
       "2009-12-31                       86.5                80.9   \n",
       "2010-01-31                       86.5                81.1   \n",
       "2010-02-28                       86.5                81.2   \n",
       "2010-03-31                       87.4                85.2   \n",
       "2010-04-30                       87.4                85.5   \n",
       "2010-05-31                       87.4                85.9   \n",
       "2010-06-30                       88.7                85.7   \n",
       "...                               ...                 ...   \n",
       "2013-06-30                      102.7               106.3   \n",
       "2013-07-31                      102.7               106.8   \n",
       "2013-08-31                      102.7               106.6   \n",
       "2013-09-30                      103.9               107.0   \n",
       "2013-10-31                      103.9               108.0   \n",
       "2013-11-30                      103.9               107.6   \n",
       "2013-12-31                      105.0               107.6   \n",
       "2014-01-31                      105.0               108.5   \n",
       "2014-02-28                      105.0               108.9   \n",
       "2014-03-31                      106.4               110.7   \n",
       "2014-04-30                      106.4               111.5   \n",
       "2014-05-31                      106.4               112.2   \n",
       "2014-06-30                      108.0               112.5   \n",
       "2014-07-31                      108.0               112.4   \n",
       "2014-08-31                      108.0               112.6   \n",
       "2014-09-30                      109.3               112.7   \n",
       "2014-10-31                      109.3               114.8   \n",
       "2014-11-30                      109.3               115.4   \n",
       "2014-12-31                      110.3               115.4   \n",
       "2015-01-31                      110.3               116.1   \n",
       "2015-02-28                      110.3               117.7   \n",
       "2015-03-31                      112.0               120.7   \n",
       "2015-04-30                      112.0               122.3   \n",
       "2015-05-31                      112.0               123.2   \n",
       "2015-06-30                      113.2               123.5   \n",
       "2015-07-31                      113.2               123.8   \n",
       "2015-08-31                      113.2               124.1   \n",
       "2015-09-30                      114.7               124.3   \n",
       "2015-10-31                      114.7               124.5   \n",
       "2015-11-30                      114.7               124.6   \n",
       "\n",
       "                                            \\\n",
       "           Alcoholic beverages and tobacco   \n",
       "2008-01-31                            67.0   \n",
       "2008-02-29                            67.8   \n",
       "2008-03-31                            70.6   \n",
       "2008-04-30                            71.1   \n",
       "2008-05-31                            71.3   \n",
       "2008-06-30                            71.4   \n",
       "2008-07-31                            71.6   \n",
       "2008-08-31                            72.6   \n",
       "2008-09-30                            73.4   \n",
       "2008-10-31                            73.6   \n",
       "2008-11-30                            73.7   \n",
       "2008-12-31                            73.8   \n",
       "2009-01-31                            73.9   \n",
       "2009-02-28                            74.7   \n",
       "2009-03-31                            78.2   \n",
       "2009-04-30                            78.8   \n",
       "2009-05-31                            78.9   \n",
       "2009-06-30                            78.9   \n",
       "2009-07-31                            79.8   \n",
       "2009-08-31                            81.8   \n",
       "2009-09-30                            82.1   \n",
       "2009-10-31                            82.1   \n",
       "2009-11-30                            82.1   \n",
       "2009-12-31                            82.1   \n",
       "2010-01-31                            82.3   \n",
       "2010-02-28                            82.3   \n",
       "2010-03-31                            87.0   \n",
       "2010-04-30                            87.3   \n",
       "2010-05-31                            87.6   \n",
       "2010-06-30                            87.4   \n",
       "...                                    ...   \n",
       "2013-06-30                           105.6   \n",
       "2013-07-31                           106.4   \n",
       "2013-08-31                           106.4   \n",
       "2013-09-30                           106.7   \n",
       "2013-10-31                           107.4   \n",
       "2013-11-30                           106.9   \n",
       "2013-12-31                           107.1   \n",
       "2014-01-31                           107.6   \n",
       "2014-02-28                           107.9   \n",
       "2014-03-31                           110.1   \n",
       "2014-04-30                           110.8   \n",
       "2014-05-31                           111.3   \n",
       "2014-06-30                           111.5   \n",
       "2014-07-31                           112.6   \n",
       "2014-08-31                           112.9   \n",
       "2014-09-30                           113.1   \n",
       "2014-10-31                           114.6   \n",
       "2014-11-30                           115.2   \n",
       "2014-12-31                           115.2   \n",
       "2015-01-31                           115.6   \n",
       "2015-02-28                           116.8   \n",
       "2015-03-31                           120.0   \n",
       "2015-04-30                           121.4   \n",
       "2015-05-31                           122.1   \n",
       "2015-06-30                           122.3   \n",
       "2015-07-31                           122.6   \n",
       "2015-08-31                           122.8   \n",
       "2015-09-30                           122.9   \n",
       "2015-10-31                           123.1   \n",
       "2015-11-30                           123.3   \n",
       "\n",
       "                                                \\\n",
       "           Analytical series - All urban areas   \n",
       "2008-01-31                                68.3   \n",
       "2008-02-29                                68.3   \n",
       "2008-03-31                                70.5   \n",
       "2008-04-30                                70.5   \n",
       "2008-05-31                                70.5   \n",
       "2008-06-30                                70.5   \n",
       "2008-07-31                                71.5   \n",
       "2008-08-31                                71.6   \n",
       "2008-09-30                                71.6   \n",
       "2008-10-31                                71.6   \n",
       "2008-11-30                                71.6   \n",
       "2008-12-31                                71.6   \n",
       "2009-01-31                                71.7   \n",
       "2009-02-28                                71.7   \n",
       "2009-03-31                                75.3   \n",
       "2009-04-30                                75.4   \n",
       "2009-05-31                                75.4   \n",
       "2009-06-30                                75.4   \n",
       "2009-07-31                                78.2   \n",
       "2009-08-31                                78.6   \n",
       "2009-09-30                                78.6   \n",
       "2009-10-31                                78.6   \n",
       "2009-11-30                                78.6   \n",
       "2009-12-31                                78.6   \n",
       "2010-01-31                                78.6   \n",
       "2010-02-28                                78.6   \n",
       "2010-03-31                                82.2   \n",
       "2010-04-30                                82.4   \n",
       "2010-05-31                                82.4   \n",
       "2010-06-30                                82.4   \n",
       "...                                        ...   \n",
       "2013-06-30                               106.1   \n",
       "2013-07-31                               107.8   \n",
       "2013-08-31                               107.8   \n",
       "2013-09-30                               107.9   \n",
       "2013-10-31                               107.9   \n",
       "2013-11-30                               107.9   \n",
       "2013-12-31                               107.9   \n",
       "2014-01-31                               108.1   \n",
       "2014-02-28                               108.1   \n",
       "2014-03-31                               114.1   \n",
       "2014-04-30                               114.2   \n",
       "2014-05-31                               114.2   \n",
       "2014-06-30                               114.4   \n",
       "2014-07-31                               116.6   \n",
       "2014-08-31                               116.6   \n",
       "2014-09-30                               116.6   \n",
       "2014-10-31                               116.6   \n",
       "2014-11-30                               116.6   \n",
       "2014-12-31                               116.6   \n",
       "2015-01-31                               116.6   \n",
       "2015-02-28                               116.6   \n",
       "2015-03-31                               123.6   \n",
       "2015-04-30                               123.8   \n",
       "2015-05-31                               123.8   \n",
       "2015-06-30                               123.9   \n",
       "2015-07-31                               126.5   \n",
       "2015-08-31                               126.5   \n",
       "2015-09-30                               126.5   \n",
       "2015-10-31                               126.5   \n",
       "2015-11-30                               126.6   \n",
       "\n",
       "                                                       \\\n",
       "           Appliances, tableware and equipment   Beer   \n",
       "2008-01-31                                88.2   67.5   \n",
       "2008-02-29                                87.4   69.3   \n",
       "2008-03-31                                88.5   71.2   \n",
       "2008-04-30                                87.6   71.3   \n",
       "2008-05-31                                88.3   71.5   \n",
       "2008-06-30                                88.7   71.5   \n",
       "2008-07-31                                89.9   71.6   \n",
       "2008-08-31                                91.8   71.5   \n",
       "2008-09-30                                92.8   72.2   \n",
       "2008-10-31                                93.0   72.1   \n",
       "2008-11-30                                93.3   72.2   \n",
       "2008-12-31                                93.4   72.2   \n",
       "2009-01-31                                97.7   72.2   \n",
       "2009-02-28                               100.2   73.2   \n",
       "2009-03-31                               101.5   77.0   \n",
       "2009-04-30                               102.3   77.4   \n",
       "2009-05-31                               102.5   77.4   \n",
       "2009-06-30                               102.8   77.2   \n",
       "2009-07-31                               101.9   77.3   \n",
       "2009-08-31                               102.1   77.1   \n",
       "2009-09-30                               101.6   77.2   \n",
       "2009-10-31                               100.9   77.2   \n",
       "2009-11-30                                99.9   77.1   \n",
       "2009-12-31                                99.4   77.1   \n",
       "2010-01-31                                99.8   77.2   \n",
       "2010-02-28                                99.0   77.4   \n",
       "2010-03-31                                99.1   82.3   \n",
       "2010-04-30                                98.7   82.3   \n",
       "2010-05-31                                98.6   82.7   \n",
       "2010-06-30                                99.0   82.3   \n",
       "...                                        ...    ...   \n",
       "2013-06-30                               100.4  106.6   \n",
       "2013-07-31                               100.7  107.0   \n",
       "2013-08-31                               101.2  107.2   \n",
       "2013-09-30                               102.1  107.1   \n",
       "2013-10-31                               102.1  108.7   \n",
       "2013-11-30                               103.1  108.8   \n",
       "2013-12-31                               102.5  109.2   \n",
       "2014-01-31                               102.9  109.6   \n",
       "2014-02-28                               103.4  110.3   \n",
       "2014-03-31                               103.6  110.7   \n",
       "2014-04-30                               104.1  111.4   \n",
       "2014-05-31                               104.4  111.8   \n",
       "2014-06-30                               105.1  112.3   \n",
       "2014-07-31                               104.8  112.2   \n",
       "2014-08-31                               105.3  112.1   \n",
       "2014-09-30                               105.5  112.5   \n",
       "2014-10-31                               105.3  115.4   \n",
       "2014-11-30                               105.3  116.4   \n",
       "2014-12-31                               104.4  116.6   \n",
       "2015-01-31                               105.1  117.2   \n",
       "2015-02-28                               106.3  119.7   \n",
       "2015-03-31                               106.4  122.6   \n",
       "2015-04-30                               106.8  124.4   \n",
       "2015-05-31                               107.7  125.1   \n",
       "2015-06-30                               107.8  125.6   \n",
       "2015-07-31                               107.7  125.7   \n",
       "2015-08-31                               108.5  126.1   \n",
       "2015-09-30                               107.9  126.2   \n",
       "2015-10-31                               108.7  126.4   \n",
       "2015-11-30                               109.1  126.5   \n",
       "\n",
       "                                                                            \\\n",
       "           Books, newspapers and stationery Bread and cereals CPI Headline   \n",
       "2008-01-31                             73.1              66.7         75.3   \n",
       "2008-02-29                             72.4              68.8         75.8   \n",
       "2008-03-31                             72.8              70.9         76.9   \n",
       "2008-04-30                             74.4              71.9         77.3   \n",
       "2008-05-31                             77.2              76.5         77.9   \n",
       "2008-06-30                             75.7              79.8         79.0   \n",
       "2008-07-31                             76.5              81.2         80.0   \n",
       "2008-08-31                             77.9              83.5         80.5   \n",
       "2008-09-30                             76.4              85.3         81.0   \n",
       "2008-10-31                             76.3              85.4         81.1   \n",
       "2008-11-30                             81.4              85.6         81.2   \n",
       "2008-12-31                             79.5              85.6         81.1   \n",
       "2009-01-31                             79.6              85.4         81.4   \n",
       "2009-02-28                             80.7              85.2         82.3   \n",
       "2009-03-31                             82.3              85.0         83.4   \n",
       "2009-04-30                             83.7              84.8         83.8   \n",
       "2009-05-31                             83.5              84.7         84.1   \n",
       "2009-06-30                             81.2              84.6         84.5   \n",
       "2009-07-31                             82.3              84.2         85.4   \n",
       "2009-08-31                             82.3              83.8         85.6   \n",
       "2009-09-30                             84.4              83.5         86.0   \n",
       "2009-10-31                             85.1              83.3         86.0   \n",
       "2009-11-30                             86.8              83.1         86.0   \n",
       "2009-12-31                             88.4              82.9         86.2   \n",
       "2010-01-31                             86.4              82.9         86.4   \n",
       "2010-02-28                             85.2              82.7         87.0   \n",
       "2010-03-31                             90.0              82.4         87.7   \n",
       "2010-04-30                             85.5              82.3         87.8   \n",
       "2010-05-31                             85.8              82.2         88.0   \n",
       "2010-06-30                             84.8              81.6         88.0   \n",
       "...                                     ...               ...          ...   \n",
       "2013-06-30                            103.3             100.7        102.9   \n",
       "2013-07-31                            101.9             101.4        104.0   \n",
       "2013-08-31                            103.7             102.5        104.3   \n",
       "2013-09-30                            105.1             104.0        104.8   \n",
       "2013-10-31                            104.9             104.4        105.0   \n",
       "2013-11-30                            105.3             104.1        105.1   \n",
       "2013-12-31                            105.8             104.3        105.4   \n",
       "2014-01-31                            110.7             105.3        106.1   \n",
       "2014-02-28                            110.7             107.2        107.3   \n",
       "2014-03-31                            113.2             108.5        108.7   \n",
       "2014-04-30                            114.6             110.3        109.2   \n",
       "2014-05-31                            114.6             110.9        109.4   \n",
       "2014-06-30                            114.5             111.3        109.7   \n",
       "2014-07-31                            115.3             110.2        110.6   \n",
       "2014-08-31                            114.8             110.4        111.0   \n",
       "2014-09-30                            115.3             110.1        111.0   \n",
       "2014-10-31                            115.8             109.8        111.2   \n",
       "2014-11-30                            116.6             109.8        111.2   \n",
       "2014-12-31                            117.9             109.4        111.0   \n",
       "2015-01-31                            118.6             110.0        110.8   \n",
       "2015-02-28                            120.4             111.5        111.5   \n",
       "2015-03-31                            121.0             112.5        113.1   \n",
       "2015-04-30                            121.2             113.0        114.1   \n",
       "2015-05-31                            122.8             115.1        114.4   \n",
       "2015-06-30                            124.2             114.9        114.9   \n",
       "2015-07-31                            123.1             115.5        116.1   \n",
       "2015-08-31                            124.5             116.9        116.1   \n",
       "2015-09-30                            125.7             117.1        116.1   \n",
       "2015-10-31                            126.7             117.6        116.4   \n",
       "2015-11-30                            126.8             117.8        116.5   \n",
       "\n",
       "                     ...             Western Cape          \\\n",
       "           Clothing  ...   Restaurants and hotels Spirits   \n",
       "2008-01-31     84.5  ...                     69.1    69.0   \n",
       "2008-02-29     84.7  ...                     69.5    70.5   \n",
       "2008-03-31     85.0  ...                     71.3    73.2   \n",
       "2008-04-30     85.1  ...                     71.5    75.3   \n",
       "2008-05-31     85.3  ...                     71.9    74.8   \n",
       "2008-06-30     85.8  ...                     72.8    75.5   \n",
       "2008-07-31     86.0  ...                     73.9    76.0   \n",
       "2008-08-31     86.5  ...                     74.5    76.2   \n",
       "2008-09-30     86.8  ...                     75.0    76.6   \n",
       "2008-10-31     86.9  ...                     77.6    76.5   \n",
       "2008-11-30     87.0  ...                     77.6    76.1   \n",
       "2008-12-31     87.4  ...                     78.5    77.3   \n",
       "2009-01-31     88.1  ...                     78.6    77.4   \n",
       "2009-02-28     89.0  ...                     79.2    77.1   \n",
       "2009-03-31     89.5  ...                     80.3    82.1   \n",
       "2009-04-30     89.9  ...                     80.7    83.0   \n",
       "2009-05-31     90.0  ...                     80.8    83.8   \n",
       "2009-06-30     90.2  ...                     81.5    84.0   \n",
       "2009-07-31     90.7  ...                     81.5    84.2   \n",
       "2009-08-31     91.1  ...                     81.5    84.1   \n",
       "2009-09-30     91.3  ...                     81.9    84.3   \n",
       "2009-10-31     91.5  ...                     83.0    84.0   \n",
       "2009-11-30     91.6  ...                     83.1    84.0   \n",
       "2009-12-31     91.7  ...                     83.7    83.9   \n",
       "2010-01-31     91.8  ...                     85.0    83.9   \n",
       "2010-02-28     91.8  ...                     85.2    84.2   \n",
       "2010-03-31     91.8  ...                     86.2    86.8   \n",
       "2010-04-30     91.9  ...                     85.9    87.7   \n",
       "2010-05-31     92.0  ...                     86.2    88.5   \n",
       "2010-06-30     92.0  ...                     87.9    88.8   \n",
       "...             ...  ...                      ...     ...   \n",
       "2013-06-30    101.0  ...                    100.9   105.6   \n",
       "2013-07-31    101.4  ...                    101.5   106.1   \n",
       "2013-08-31    102.2  ...                    103.0   105.8   \n",
       "2013-09-30    102.8  ...                    105.3   107.0   \n",
       "2013-10-31    103.1  ...                    106.7   106.8   \n",
       "2013-11-30    103.3  ...                    109.1   106.3   \n",
       "2013-12-31    103.6  ...                    109.5   105.5   \n",
       "2014-01-31    104.0  ...                    112.0   107.1   \n",
       "2014-02-28    104.8  ...                    113.2   106.8   \n",
       "2014-03-31    105.3  ...                    113.9   110.3   \n",
       "2014-04-30    105.8  ...                    113.4   112.0   \n",
       "2014-05-31    106.2  ...                    113.5   115.5   \n",
       "2014-06-30    106.4  ...                    111.9   115.9   \n",
       "2014-07-31    106.8  ...                    110.9   116.3   \n",
       "2014-08-31    107.8  ...                    112.4   115.4   \n",
       "2014-09-30    108.5  ...                    114.8   116.3   \n",
       "2014-10-31    109.2  ...                    117.8   116.6   \n",
       "2014-11-30    109.9  ...                    119.5   116.1   \n",
       "2014-12-31    110.3  ...                    118.7   116.5   \n",
       "2015-01-31    110.7  ...                    119.1   117.6   \n",
       "2015-02-28    111.2  ...                    119.0   118.3   \n",
       "2015-03-31    111.6  ...                    120.8   121.0   \n",
       "2015-04-30    111.9  ...                    118.1   123.3   \n",
       "2015-05-31    112.2  ...                    117.2   125.0   \n",
       "2015-06-30    112.6  ...                    116.7   124.8   \n",
       "2015-07-31    113.0  ...                    117.1   124.7   \n",
       "2015-08-31    113.6  ...                    117.5   124.8   \n",
       "2015-09-30    114.1  ...                    119.8   124.8   \n",
       "2015-10-31    114.5  ...                    121.8   124.8   \n",
       "2015-11-30    115.0  ...                    124.8   124.2   \n",
       "\n",
       "                                                            \\\n",
       "           Sugar, sweets and deserts Supplies and services   \n",
       "2008-01-31                      63.5                  72.4   \n",
       "2008-02-29                      63.7                  72.3   \n",
       "2008-03-31                      64.2                  73.0   \n",
       "2008-04-30                      65.4                  73.9   \n",
       "2008-05-31                      66.6                  74.3   \n",
       "2008-06-30                      68.5                  76.0   \n",
       "2008-07-31                      70.0                  76.1   \n",
       "2008-08-31                      70.2                  76.2   \n",
       "2008-09-30                      74.6                  77.7   \n",
       "2008-10-31                      76.3                  77.8   \n",
       "2008-11-30                      76.5                  78.0   \n",
       "2008-12-31                      75.4                  78.6   \n",
       "2009-01-31                      77.2                  79.3   \n",
       "2009-02-28                      77.0                  79.5   \n",
       "2009-03-31                      78.5                  81.3   \n",
       "2009-04-30                      79.6                  81.3   \n",
       "2009-05-31                      80.5                  81.7   \n",
       "2009-06-30                      81.1                  83.5   \n",
       "2009-07-31                      80.9                  83.8   \n",
       "2009-08-31                      80.6                  83.8   \n",
       "2009-09-30                      81.6                  84.2   \n",
       "2009-10-31                      82.0                  84.4   \n",
       "2009-11-30                      82.2                  84.7   \n",
       "2009-12-31                      80.9                  84.9   \n",
       "2010-01-31                      82.1                  84.9   \n",
       "2010-02-28                      82.5                  85.0   \n",
       "2010-03-31                      85.0                  85.8   \n",
       "2010-04-30                      84.3                  85.7   \n",
       "2010-05-31                      85.8                  85.8   \n",
       "2010-06-30                      84.3                  87.2   \n",
       "...                              ...                   ...   \n",
       "2013-06-30                     106.0                 103.2   \n",
       "2013-07-31                     104.0                 103.2   \n",
       "2013-08-31                     104.5                 103.4   \n",
       "2013-09-30                     104.6                 104.9   \n",
       "2013-10-31                     104.5                 105.2   \n",
       "2013-11-30                     105.9                 105.3   \n",
       "2013-12-31                     104.6                 105.9   \n",
       "2014-01-31                     105.5                 105.7   \n",
       "2014-02-28                     106.4                 105.8   \n",
       "2014-03-31                     109.9                 106.9   \n",
       "2014-04-30                     110.2                 107.2   \n",
       "2014-05-31                     110.4                 106.9   \n",
       "2014-06-30                     111.8                 108.6   \n",
       "2014-07-31                     112.1                 108.4   \n",
       "2014-08-31                     115.4                 108.7   \n",
       "2014-09-30                     115.6                 109.6   \n",
       "2014-10-31                     115.8                 109.8   \n",
       "2014-11-30                     116.1                 109.9   \n",
       "2014-12-31                     113.7                 110.1   \n",
       "2015-01-31                     115.6                 111.1   \n",
       "2015-02-28                     116.7                 111.4   \n",
       "2015-03-31                     119.6                 112.3   \n",
       "2015-04-30                     121.2                 112.5   \n",
       "2015-05-31                     122.4                 112.7   \n",
       "2015-06-30                     123.0                 114.5   \n",
       "2015-07-31                     121.2                 114.5   \n",
       "2015-08-31                     123.4                 114.7   \n",
       "2015-09-30                     124.0                 114.8   \n",
       "2015-10-31                     125.2                 115.1   \n",
       "2015-11-30                     125.5                 115.1   \n",
       "\n",
       "                                                                     \\\n",
       "           Telecommunication equipment Tobacco Transport Vegetables   \n",
       "2008-01-31                       226.9    64.8      88.4       68.6   \n",
       "2008-02-29                       225.5    64.9      88.6       67.5   \n",
       "2008-03-31                       225.5    67.4      90.3       68.1   \n",
       "2008-04-30                       225.7    67.6      91.0       70.2   \n",
       "2008-05-31                       236.6    67.8      92.0       70.3   \n",
       "2008-06-30                       234.5    67.9      93.8       69.7   \n",
       "2008-07-31                       228.7    67.9      95.3       72.0   \n",
       "2008-08-31                       229.6    69.0      94.5       74.9   \n",
       "2008-09-30                       211.7    71.6      93.8       73.3   \n",
       "2008-10-31                       223.9    71.6      93.5       78.6   \n",
       "2008-11-30                       217.6    71.8      92.3       76.2   \n",
       "2008-12-31                       222.8    71.8      89.5       82.0   \n",
       "2009-01-31                       230.7    71.8      86.5       83.4   \n",
       "2009-02-28                       227.3    72.3      88.2       80.3   \n",
       "2009-03-31                       227.8    75.3      89.2       80.2   \n",
       "2009-04-30                       226.0    75.5      90.2       81.6   \n",
       "2009-05-31                       222.3    76.0      90.8       83.4   \n",
       "2009-06-30                       215.1    76.1      91.4       82.5   \n",
       "2009-07-31                       213.3    78.5      91.5       81.9   \n",
       "2009-08-31                       210.4    83.2      91.3       84.0   \n",
       "2009-09-30                       200.2    83.2      91.6       86.3   \n",
       "2009-10-31                       193.5    83.3      91.0       92.9   \n",
       "2009-11-30                       187.8    83.5      90.8       90.0   \n",
       "2009-12-31                       186.0    83.5      91.1       87.5   \n",
       "2010-01-31                       183.1    83.5      90.8       87.0   \n",
       "2010-02-28                       174.7    83.5      91.3       83.3   \n",
       "2010-03-31                       167.9    89.8      91.6       82.5   \n",
       "2010-04-30                       163.7    89.6      92.8       82.7   \n",
       "2010-05-31                       159.1    89.6      92.9       84.5   \n",
       "2010-06-30                       155.8    89.6      92.3       85.1   \n",
       "...                                ...     ...       ...        ...   \n",
       "2013-06-30                        93.4   103.5     102.0      102.9   \n",
       "2013-07-31                        94.6   105.2     105.0      101.4   \n",
       "2013-08-31                        93.8   105.5     106.3      101.5   \n",
       "2013-09-30                        94.3   104.2     106.4      104.0   \n",
       "2013-10-31                        92.5   103.4     106.0      106.2   \n",
       "2013-11-30                        91.8   103.3     105.1      108.9   \n",
       "2013-12-31                        88.3   104.2     105.9      105.4   \n",
       "2014-01-31                        87.2   102.9     107.1      110.5   \n",
       "2014-02-28                        87.6   102.9     108.8      109.2   \n",
       "2014-03-31                        88.2   106.2     110.8      110.4   \n",
       "2014-04-30                        86.9   106.4     111.1      111.7   \n",
       "2014-05-31                        85.7   106.7     110.8      113.3   \n",
       "2014-06-30                        85.9   106.7     110.0      111.9   \n",
       "2014-07-31                        86.4   109.8     111.2      112.2   \n",
       "2014-08-31                        82.1   111.4     111.4      116.3   \n",
       "2014-09-30                        81.5   111.6     109.4      116.8   \n",
       "2014-10-31                        80.3   111.5     109.6      115.4   \n",
       "2014-11-30                        79.8   111.5     108.1      114.6   \n",
       "2014-12-31                        79.2   111.8     106.1      110.2   \n",
       "2015-01-31                        77.6   111.8     102.2      109.2   \n",
       "2015-02-28                        77.5   111.3      99.2      109.8   \n",
       "2015-03-31                        74.7   114.5     102.9      111.4   \n",
       "2015-04-30                        75.2   115.0     108.6      113.3   \n",
       "2015-05-31                        73.2   114.9     108.7      112.9   \n",
       "2015-06-30                        74.1   115.3     110.6      111.0   \n",
       "2015-07-31                        71.0   115.4     112.3      112.0   \n",
       "2015-08-31                        68.5   115.4     110.5      112.5   \n",
       "2015-09-30                        67.8   115.4     108.3      113.5   \n",
       "2015-10-31                        67.7   115.3     108.7      116.6   \n",
       "2015-11-30                        67.6   116.2     108.1      114.7   \n",
       "\n",
       "                                            \n",
       "           Water and other services   Wine  \n",
       "2008-01-31                     68.7   77.5  \n",
       "2008-02-29                     68.7   77.2  \n",
       "2008-03-31                     68.7   79.1  \n",
       "2008-04-30                     68.7   79.5  \n",
       "2008-05-31                     68.7   79.7  \n",
       "2008-06-30                     68.7   80.6  \n",
       "2008-07-31                     73.1   81.2  \n",
       "2008-08-31                     73.1   82.4  \n",
       "2008-09-30                     73.1   82.7  \n",
       "2008-10-31                     73.1   82.4  \n",
       "2008-11-30                     73.1   82.2  \n",
       "2008-12-31                     73.1   81.9  \n",
       "2009-01-31                     73.1   82.0  \n",
       "2009-02-28                     73.1   81.7  \n",
       "2009-03-31                     73.1   84.7  \n",
       "2009-04-30                     73.1   85.7  \n",
       "2009-05-31                     73.1   86.4  \n",
       "2009-06-30                     73.1   86.1  \n",
       "2009-07-31                     80.1   86.4  \n",
       "2009-08-31                     80.1   86.6  \n",
       "2009-09-30                     80.1   87.0  \n",
       "2009-10-31                     80.1   87.1  \n",
       "2009-11-30                     80.1   87.6  \n",
       "2009-12-31                     80.1   87.4  \n",
       "2010-01-31                     80.1   87.8  \n",
       "2010-02-28                     80.1   87.8  \n",
       "2010-03-31                     80.1   90.4  \n",
       "2010-04-30                     80.1   91.8  \n",
       "2010-05-31                     80.1   92.4  \n",
       "2010-06-30                     80.1   92.5  \n",
       "...                             ...    ...  \n",
       "2013-06-30                    100.0  105.6  \n",
       "2013-07-31                    108.2  105.7  \n",
       "2013-08-31                    108.2  102.8  \n",
       "2013-09-30                    108.2  105.1  \n",
       "2013-10-31                    108.2  105.5  \n",
       "2013-11-30                    108.2  102.9  \n",
       "2013-12-31                    108.2  102.6  \n",
       "2014-01-31                    108.2  104.7  \n",
       "2014-02-28                    108.2  104.4  \n",
       "2014-03-31                    108.2  107.0  \n",
       "2014-04-30                    108.2  106.9  \n",
       "2014-05-31                    108.2  107.9  \n",
       "2014-06-30                    108.2  107.2  \n",
       "2014-07-31                    116.4  108.8  \n",
       "2014-08-31                    116.4  108.7  \n",
       "2014-09-30                    116.4  108.5  \n",
       "2014-10-31                    116.4  107.5  \n",
       "2014-11-30                    116.4  108.7  \n",
       "2014-12-31                    116.4  108.5  \n",
       "2015-01-31                    116.4  108.2  \n",
       "2015-02-28                    116.4  108.2  \n",
       "2015-03-31                    116.4  110.3  \n",
       "2015-04-30                    116.4  113.3  \n",
       "2015-05-31                    116.4  114.5  \n",
       "2015-06-30                    116.4  114.1  \n",
       "2015-07-31                    127.4  114.9  \n",
       "2015-08-31                    127.4  115.1  \n",
       "2015-09-30                    127.4  115.5  \n",
       "2015-10-31                    127.4  114.7  \n",
       "2015-11-30                    127.4  116.2  \n",
       "\n",
       "[95 rows x 849 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_data = {(tsdata['tags']['H13'], tsdata['tags']['H04']): tsdata['series'] for tsdata in all_time_series}\n",
    "df = pd.DataFrame(data=df_data)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What's next\n",
    "\n",
    "Now that I can load the CPI data, I intend doing some more analysis in a future blog post. I'm also going to turn the code here into a decent function (or two) that will give me all the series and the DataFrame. I still need to handle frequencies other than monthly when loading the time series, e.g. quarterly and annually."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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