Effectively Using Matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Effectively Using Matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Pandas has his own built in fixed functions but we need to use one custome called xlrd so please use before starting\n",
    "# pip install xlrd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import FuncFormatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>account number</th>\n",
       "      <th>name</th>\n",
       "      <th>sku</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "      <th>ext price</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>740150</td>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>39</td>\n",
       "      <td>86.69</td>\n",
       "      <td>3380.91</td>\n",
       "      <td>2014-01-01 07:21:51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>S2-77896</td>\n",
       "      <td>-1</td>\n",
       "      <td>63.16</td>\n",
       "      <td>-63.16</td>\n",
       "      <td>2014-01-01 10:00:47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>218895</td>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>B1-69924</td>\n",
       "      <td>23</td>\n",
       "      <td>90.70</td>\n",
       "      <td>2086.10</td>\n",
       "      <td>2014-01-01 13:24:58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>307599</td>\n",
       "      <td>Kassulke, Ondricka and Metz</td>\n",
       "      <td>S1-65481</td>\n",
       "      <td>41</td>\n",
       "      <td>21.05</td>\n",
       "      <td>863.05</td>\n",
       "      <td>2014-01-01 15:05:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S2-34077</td>\n",
       "      <td>6</td>\n",
       "      <td>83.21</td>\n",
       "      <td>499.26</td>\n",
       "      <td>2014-01-01 23:26:55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   account number                         name       sku  quantity  \\\n",
       "0          740150                   Barton LLC  B1-20000        39   \n",
       "1          714466              Trantow-Barrows  S2-77896        -1   \n",
       "2          218895                    Kulas Inc  B1-69924        23   \n",
       "3          307599  Kassulke, Ondricka and Metz  S1-65481        41   \n",
       "4          412290                Jerde-Hilpert  S2-34077         6   \n",
       "\n",
       "   unit price  ext price                 date  \n",
       "0       86.69    3380.91  2014-01-01 07:21:51  \n",
       "1       63.16     -63.16  2014-01-01 10:00:47  \n",
       "2       90.70    2086.10  2014-01-01 13:24:58  \n",
       "3       21.05     863.05  2014-01-01 15:05:22  \n",
       "4       83.21     499.26  2014-01-01 23:26:55  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(\"https://github.com/chris1610/pbpython/blob/master/data/sample-salesv3.xlsx?raw=true\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Top 10 customers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>ext price</th>\n",
       "      <th>quantity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>137351.96</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>White-Trantow</td>\n",
       "      <td>135841.99</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>123381.38</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>112591.43</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fritsch, Russel and Anderson</td>\n",
       "      <td>112214.71</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>109438.50</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Will LLC</td>\n",
       "      <td>104437.60</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Koepp Ltd</td>\n",
       "      <td>103660.54</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Frami, Hills and Schmidt</td>\n",
       "      <td>103569.59</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Keeling LLC</td>\n",
       "      <td>100934.30</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           name  ext price  quantity\n",
       "0                     Kulas Inc  137351.96        94\n",
       "1                 White-Trantow  135841.99        86\n",
       "2               Trantow-Barrows  123381.38        94\n",
       "3                 Jerde-Hilpert  112591.43        89\n",
       "4  Fritsch, Russel and Anderson  112214.71        81\n",
       "5                    Barton LLC  109438.50        82\n",
       "6                      Will LLC  104437.60        74\n",
       "7                     Koepp Ltd  103660.54        82\n",
       "8      Frami, Hills and Schmidt  103569.59        72\n",
       "9                   Keeling LLC  100934.30        74"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top10 = (df.groupby('name')['ext price', 'quantity'].agg({'ext price' : 'sum', 'quantity' : 'count'})\n",
    "         .sort_values(by='ext price', ascending = False))[:10].reset_index()\n",
    "top10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Purchases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>137351.96</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>White-Trantow</td>\n",
       "      <td>135841.99</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>123381.38</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>112591.43</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fritsch, Russel and Anderson</td>\n",
       "      <td>112214.71</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>109438.50</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Will LLC</td>\n",
       "      <td>104437.60</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Koepp Ltd</td>\n",
       "      <td>103660.54</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Frami, Hills and Schmidt</td>\n",
       "      <td>103569.59</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Keeling LLC</td>\n",
       "      <td>100934.30</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Name      Sales  Purchases\n",
       "0                     Kulas Inc  137351.96         94\n",
       "1                 White-Trantow  135841.99         86\n",
       "2               Trantow-Barrows  123381.38         94\n",
       "3                 Jerde-Hilpert  112591.43         89\n",
       "4  Fritsch, Russel and Anderson  112214.71         81\n",
       "5                    Barton LLC  109438.50         82\n",
       "6                      Will LLC  104437.60         74\n",
       "7                     Koepp Ltd  103660.54         82\n",
       "8      Frami, Hills and Schmidt  103569.59         72\n",
       "9                   Keeling LLC  100934.30         74"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Above example labels does not look nice so lets change it a bit.\n",
    "top_10 = (df.groupby('name')['ext price', 'quantity'].agg({'ext price': 'sum', 'quantity': 'count'})\n",
    "          .sort_values(by='ext price', ascending=False))[:10].reset_index()\n",
    "\n",
    "top_10.rename(columns={'name': 'Name', 'ext price': 'Sales', 'quantity': 'Purchases'}, inplace=True)\n",
    "top_10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['bmh',\n",
       " 'classic',\n",
       " 'dark_background',\n",
       " 'fivethirtyeight',\n",
       " 'ggplot',\n",
       " 'grayscale',\n",
       " 'seaborn-bright',\n",
       " 'seaborn-colorblind',\n",
       " 'seaborn-dark-palette',\n",
       " 'seaborn-dark',\n",
       " 'seaborn-darkgrid',\n",
       " 'seaborn-deep',\n",
       " 'seaborn-muted',\n",
       " 'seaborn-notebook',\n",
       " 'seaborn-paper',\n",
       " 'seaborn-pastel',\n",
       " 'seaborn-poster',\n",
       " 'seaborn-talk',\n",
       " 'seaborn-ticks',\n",
       " 'seaborn-white',\n",
       " 'seaborn-whitegrid',\n",
       " 'seaborn',\n",
       " '_classic_test']"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What are avaiable styles for rendering plots?\n",
    "plt.style.available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# You can experiment in here and choose the best one for you\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sdFs3b96s8L3RrZGUlMT27dvRaDQ4OjpaTheUaNiwIUOGDCEoKAgPD48yJ17+2dChQ1m5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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbe69630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# But now let's use standard pandas ploting\n",
    "top_10.plot(kind='barh', y='Sales', x='Name')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below you have list of **plot kind**s: \n",
    "* ‘line’ : line plot (default)\n",
    "* ‘bar’ : vertical bar plot\n",
    "* ‘barh’ : horizontal bar plot\n",
    "* ‘hist’ : histogram\n",
    "* ‘box’ : boxplot\n",
    "* ‘kde’ : Kernel Density Estimation plot\n",
    "* ‘density’ : same as ‘kde’\n",
    "* ‘area’ : area plot\n",
    "* ‘pie’ : pie plot\n",
    "* ‘scatter’ : scatter plot\n",
    "* ‘hexbin’ : hexbin plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Customizing the plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sdFs3b96s8L3RrZGUlMT27dvRaDQ4OjpaTheUaNiwIUOGDCEoKAgPD48yJ17+2dChQ1m5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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbef0210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# It is critical to get access to axes and figures in matplotlib\n",
    "fig, ax = plt.subplots()\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### You may ask why we want to have access to axes or figures?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ks++TkpLYsmULdnZ2ODk5mS5TFKtZsyZ9+/YlJCQELy+vMgeQ/tnzzz/P0qVLmTZtGj4+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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8125030>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's play around axes and set limits to it and labes\n",
    "fig, ax = plt.subplots()\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "\n",
    "ax.set_xlim([-20000, 140000])\n",
    "ax.set_xlabel('Total Revenue')\n",
    "ax.set_ylabel('Customer')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nXq/XV6g8j1KnTp2n0o+cLhFmBUXG9evX8fT0xNvbm/Pnz3Pu3LmnUmS4u7tz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\nCCHsQjoZQgghhLCL/wOlTM71KqXMZQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbc93450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Here is the shorter verion of it\n",
    "fig, ax = plt.subplots()\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "\n",
    "ax.set_xlim([-10000, 140000])\n",
    "ax.set(title='2014 Revenue', xlabel='Total Revenue', ylabel='Customer')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0coElvf93hQoVtJ/1ej0mk+mR4vXw8ODChQuP1IYQQjxOinV19Ny5c/H396dK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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x81efd50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Going further we can change the size of the plot or disable the legend which is unnecessary in this case\n",
    "fig, ax = plt.subplots(figsize=(5, 3))\n",
    "\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "ax.set_xlim([-10000, 140000])\n",
    "ax.set(title='2014 Revenue', xlabel='Total Revenue', ylabel='Customer')\n",
    "\n",
    "ax.legend().set_visible(False)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding currency\n",
    "```FuncFormatter``` can apply user defined funtion to the value abd return nicely formatter string to place on the axis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# First of all we need to define function that will be changing the currencies\n",
    "# We go either in milions or thousands\n",
    "def currency(x, pos):\n",
    "    'The two args are the value and tick position'\n",
    "    if x == 0:\n",
    "        return 0\n",
    "    if x >= 1000000:\n",
    "        return '${:1.1f}M'.format(x*1e-6)\n",
    "    return '${:1.0f}K'.format(x*1e-3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DBw8uc6bIyEgGDBhA48aNb/v+pUuXeO+998jOzsZisTBkyBBCQkKKbPP555/z448/kpub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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x83541f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now let's print this\n",
    "fig, ax = plt.subplots()\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "ax.set_xlim([-10000, 140000])\n",
    "ax.set(title='2014 Revenue', xlabel='Total Revenue', ylabel='Customer')\n",
    "\n",
    "formatter = FuncFormatter(currency)\n",
    "ax.xaxis.set_major_formatter(formatter)\n",
    "ax.legend().set_visible(False)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding lines and custom text to the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 customers mean value is:  114342.2\n"
     ]
    },
    {
     "data": {
      "image/png": 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eP36sLnt7e3P48GEAzpw5Q2amvF5eCCHE/8iIy9+Ira0ts2fPZt68edjb2zNu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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbe1d830>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create the figure and the axes\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# Plot the data and get the averaged\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "avg = top_10['Sales'].mean()\n",
    "print('Top 10 customers mean value is: ',avg)\n",
    "\n",
    "# Set limits and labels\n",
    "ax.set_xlim([-10000, 140000])\n",
    "ax.set(title='2014 Revenue', xlabel='Total Revenue', ylabel='Customer')\n",
    "\n",
    "# Add a line for the average\n",
    "ax.axvline(x=avg, color='b', label='Average', linestyle='--', linewidth=1)\n",
    "\n",
    "# Annotate the new customers\n",
    "new_customers = [1, 5 ,9]\n",
    "for cust in new_customers:\n",
    "    ax.text(125000, cust, \"New Customer\")\n",
    "\n",
    "# Format the currency\n",
    "formatter = FuncFormatter(currency)\n",
    "ax.xaxis.set_major_formatter(formatter)\n",
    "\n",
    "# Hide the legend\n",
    "ax.legend().set_visible(False)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# I used nrows and ncols but normally people just specify the value without the name parameter\n",
    "# I am using sharey=True so that the yaxis will share the same labels for both figures.\n",
    "fig, (ax0, ax1) = plt.subplots(nrows=1, ncols=2, sharey=True, figsize=(7, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GtGvXDp1OR+PGjcv8WMjf35+ZM2dqr5ctW2b2vi1atOCjjz4iLy+Prl270rRp\n0yJtjhw5wqZNm7h+/TpXr16lUaNGWhHUtWtXAJo3b6713Bw9epRBgwYB0KRJE5o0aVLsuSdOnEhi\nYiKHDh3i+++/59ChQ0yePJkjR47w73//GwC9Xo+TkxNXr17F09NTi6958+aFPqeCeBo3bkzDhg2p\nXbs2APXq1ePChQuFiqBjx45pBZe7uztt27Y1+/MKDAwkMDBQe52enm72vqJ6uJN74oUX3CwyvX9B\n76sl3ZpTonq7m9+pHh4eRfav7NwyN6fu+YHRJbl5LMmuXbvIzMwkIiKCJUuW4Obmpj0asrOz09rp\ndDrttU6nw2QyVVq8rVu3Zt68ebi7u/P++++zc+fOQu/n5OQQGRnJSy+9xNKlSxkwYEChx1sFcev1\n+juKu3HjxgwZMoS5c+fyxx9/3LbtzZ+ZXq/HaDQWee/mz7Lg9c3thLBG69Y5WToEIaoka82tKlsE\n3Sw7O5tatWpha2vLkSNH7mrg7969e/nqq6/KMbp8aWlpuLm5ERgYSP/+/Tlz5kyh93NzcwFwdXXF\nYDCUWqhAfmG1a9cuABITE/nrr7+KtDEYDMTGxmqvExISqFu3LgDt2rVj69atQP7jtuzs8l0F2N/f\nnz179mAymbh48WKhOBwdHTEYDOV6PiGEEOJm9/zjMHP06tWLRYsWMXPmTJo2bYq3t/cdH+v8+fPU\nqFGjHKPLFxsby/fff4+NjQ2Ojo7aY6gCzs7ODBgwgJCQEDw9PUscYH2zgQMH8uGHHzJ9+nSaNm1K\ny5Yti7RRSrFp0yZWrFiBvb09jo6OTJo0CYCxY8eyYsUKtm/fjl6vZ/z48bi5uZXPBZP/CO/IkSOE\nhITQoEGDQgPBAwMDCQ8Px93dXQZGCyGEqBA6pZSydBD3kvfee4+xY8eWOGBXWEZSUpJZ7Yp7Vl2V\nVafrLY9rXbzYhRkzrpZTROazhjFBtzI3pyqDtd3HEs/tFRdPZeeWuTlVLXqCytOUKVMsHYIQooL8\n4x/yCFaIimCtuVUtxgQJIYQ5Hn7Ys/RGQogys9bckiJICCGEENWSFEFCCCGEqJakCBJCiBtatsy1\ndAhCVEnWmltSBAkhxA07d1bs4sFCVFfWmltSBAkhxA0tWtS3dAhCVEnWmltSBAkhxA0Gg/xKFKIi\nWGtuWWdUQgghhBAVTIogIYS4Qa+XCfSFqAjWmluybIaoEsyd4t84/tEKjkRYC5tPNlk6BLNZ47IZ\nZwcHWDrIHzZMAAAgAElEQVQEUQVYKg/NzSnpCRJCiBuGD69j6RCEqJKsNbekCKoGRo8erf0cExPD\n1KlTSUur/K8rhoWFER8fX2hbQkICMTExJe4zefJkMjMzKzo0IQCIjnawdAhCVEnWmltSBFUjhw8f\nZtWqVcyaNYu6detaOhwgvwg6cOCApcMQQghRDckq8tXE0aNHWb58ObNmzaJ+/fz5GlJTU/noo4+4\ncuUKrq6uTJo0CQ8PDzIzM1mxYgUXLlwAICgoCD8/P9auXUtKSgoZGRlcuHCBRx99lMDAQGJjY1m7\ndi0uLi4kJSXh7+/PuHHj0OtvX2Pn5eXx9ddfk5OTw/Hjxxk6dCjt2rXj3XffJTMzk5YtWyJD1oQQ\nQlQU6QmqBvLy8liyZAmhoaF4e3tr21euXEmfPn1488036dWrFytXrgRg1apVDBkyhIULFxISEsLy\n5cu1fRITE5k1axZvvPEG3333HRkZGQCcOnWKMWPGsHTpUlJSUti7d2+pcdna2vLkk0/Ss2dPlixZ\nQs+ePfnmm2/w8/Nj8eLFBAQEkJ6eXs6fhhAle++9i5YOQYgqyVpzS3qCqgEbGxt8fX3Zvn07wcHB\n2vaTJ08yffp0AHr37s2XX34J5D82O3funNYuOzsbg8EAQEBAAPb29tjb29OmTRtOnTqFs7MzLVu2\npF69egDcf//9HD9+nO7du5c51mPHjmkxderUCWdn52Lbbdu2jW3btgEQERGBh4eHWcdPKXNE4l5l\n7j1xs5o1dXh4FH/PVXW35pQQ5aEgD601t6QIqgZ0Oh3Tpk1j/vz5rFu3jmHDht22vVKK8PBw7O3t\niz3W7V5XlsDAQAIDA7XX0mMkbnUn90RwsBcDB5o33UJ5soavyN+aU0KUh4I8rOzckq/Ii0IcHByY\nNWsWu3btYvv27QD4+Piwe/duAHbt2oWfnx8A7du3Z8uWLdq+CQkJ2s/79u0jJyeHK1euEBsbS4sW\nLYD8x2GpqamYTCb27NmjHas0jo6OXLt2TXvt7+/Prl27ADhw4ABZWVl3ftFCCCHEbUhPUDXi4uLC\n7Nmzee2113B1deXZZ5/lww8/ZNOmTdrAaIDg4GAiIyOZPn06RqMRf39/JkyYAEDLli2JiIggPT2d\n4cOH4+7uTnJyMj4+Pnz55ZckJibi7+9P165di40hIiICGxsbIL8ImzBhAhs3biQ0NJShQ4cyYsQI\n3n33XV5++WX8/f3v6JGGEEIIYQ6ZMVqYbe3atTg6OvLoo4VnXY6NjeX7779n5syZFopMZowWRd3J\nTLXDh9fhu+8uVEA0t2cNj8NuJTNGi/JQkIeVnVvm5pT0BIlqpd763dVq/JCHh0e1ud7yuFZLFEDW\nypqWHbG2+1jiub3i4rHW3JIiSJjtiSeeKHZ7mzZtaNOmTSVHI0T5a9SoAWfPJls6DCGqHGvNLRkY\nLYQQN5hMlvm2oxBVnbXmlhRBQgghhKiWpAgSQogbHB1Nlg5BiCrJWnNLiiAhhLghPv68pUMQokqy\n1tySIkgIIW7o06eupUMQokqy1tySIkgIIW44dcrO0iEIUSVZa25JESSEEEKIakmKICGEEEJUS1IE\nCSHEDVu2pFo6BCGqJGvNLZkxWlQrKUN7WjqESpVi6QAqUXHXWtalH376yZF27a6WT0D3OGtaZ8/a\n7uPqGM/dLqNirbklPUFCCHHDu++6WjoEIaoka80tKYIEAJ999hk//vij9jo8PJyPP/5Ye/2f//yH\nH374gYyMDJYuXQrkrx4fEREBwI4dO4iMjCxy3JK2T548mczMzCLbDxw4wMyZM5k2bRovvvgi//nP\nf+762oQQQojiyOMwAYCfnx+7d+9m8ODBmEwmMjMzyc7O1t4/ceIEQUFBuLu7ExISUiExJCYmsnLl\nSmbOnIm3tzdGo5Fff/21Qs4lhBBCSE+QAMDHx4eTJ08CcO7cORo1akSNGjW4evUqubm5/P333zRv\n3pzU1NQKK4I2bdrE0KFD8fb2BsDGxoaBAwdWyLmEKM6wYdmlNxJClJm15pb0BAkA3N3d0ev1pKen\nc+LECXx8fMjIyCAuLg4nJycaN26MrW3F3i5nz55lyJAhZrXdtm0bGzduJDs7m8jISDw8PMzaz9oG\nNIqKZe59UWDNGoCy7VNV3JpTQtysLLlka2tbpL215pYUQULj6+vLiRMnOHHiBEOGDClUBPn6+lo6\nvEICAwMJDAzUXqenp1swGmGtynpfeHt78fffSRUUTcm8vLwq/Zy3ujWnhLhZWXLJw8OjSPvKzi1z\nc0oehwlNQRF09uxZGjdujI+PD3FxcZw4caJSiqCGDRty+vTpCj+PEEIIAXdRBKWkpJCaap2TH4k7\n4+vrS0xMDC4uLuj1elxcXMjKyiIuLg4fH58KP/+jjz7K+vXrSUrK/9+CyWTihx9+qPDzCiGEqJ7M\nfhz2zjvv8I9//ANfX1+ioqL49NNP0ev1BAcH079//4qMUVSSxo0bc+XKFXr16lVom8FgwNX1zud4\n2LFjB/v27dNeh4eHAxAaGopOpwOgR48eBAUFMXbsWN59911ycnIA6Ny58x2fV4iy8vAwWjoEIaok\na80tnVJKmdNw3LhxfPzxx9ja2hISEsL48eNxdnZmyZIlvPfeexUdpxC3VdB7VBprmgVXVLy7neW2\nsljDmKBbnR0cYOkQhBUpSy4VNyaospmbU2b3BOXl5WFra0tGRgZXr17Fz88PgMuXL99ZhEJYQL31\nuy2enJXJGn4ZVZbyuNYOHepx8KB8hxCsq4C0tvtY4ik7a80ts4ugpk2bsn79etLS0ujUqRMAGRkZ\n1KhRo8KCE0KIypSebmPpEISokqw1t8weGD1x4kQSExPJycnhqaeeAiAuLq7Q+BEhhBBCiHuFWT1B\nJpOJnTt38vzzz2Nvb69t7969O927d6+w4IQQQgghKopZPUF6vZ6tW7dW+IzBQghhSZaYKFGI6sBa\nc8vsx2G9e/fml19+qchYhBDCol54wc3SIQhRJVlrbpndtXPq1Cm2bNnCpk2bqFOnjja/C8C8efMq\nJDghhKhM69Y58f77lywdhhBVjrXmltlF0IABAxgwYEBFxiKEEEIIUWnMLoL69u1bgWEIIYQQQlQu\ns4sgpRS//vorv//+O1euXOHNN9/k6NGjXLp0iZ49e1ZkjEIIUSmmTs20dAhCVEnWmltmD4z++uuv\niYqKIjAwUJuZsk6dOmzcuLHCghNCiMr0j38YLB2CEFWSteaW2T1BO3fuZNGiRbi6uvLpp58C4Onp\nKSvJi3tKytDq1WtpfZPUV5yyXGtJS0I8/LCn1X6Vt7JZ0zp71nYfSzy3d3M8Bblmrblldk+QyWTC\n0dGx0DaDwVBkmxBCCCHEvcDsnqD77ruP//znPwQFBQH5Y4S+/vprOnfuXGHBibJ78sknady4MZA/\nyeWzzz6Lr69vmY6xbt06hg0bVi7xrF27FkdHRx59tPD/KkePHs3q1auLtN+5cyebNm1CKYVSin79\n+hXZVwghhCgPZvcEjRkzhosXLzJ27Fiys7MZM2YMaWlpjBw5siLjE2Vkb2/PkiVLWLJkCU8//TRf\nffWV2fsqpTCZTKxfv74CIyzZgQMH2Lx5M3PmzOGtt95i0aJFODk5WSQWUT21bJlr6RCEqJKsNbfM\n7glycnIiNDSUS5cukZ6ejoeHB25u1jkDpMh37do1nJ2dgfxHl4sXLyYrK4u8vDyeeuopunTpQmpq\nKgsXLqRNmzbExcXRtGlTcnJyCA0NpVGjRkyZMoUffviBqKgoAPr378/gwYO1/Xx9fYmLi8Pd3Z0Z\nM2YUWluurDZs2MDo0aNxd3cH8gu6wMDAu/8ghDDTzp1plg5BiCrJWnOrzIuB2dvb4+7ujslkIiMj\nA0D7R0tYXkEBk5uby8WLF3nttdcAsLOzY/r06Tg5OZGZmcmcOXMICAgAICkpieeff55x48YBsGfP\nHpYsWQLA6dOniYqKIjw8HIDZs2fTunVrnJ2dSU5OZurUqUycOJG33nqL6OhoevfufcexJyYm0rx5\nc7Pabtu2jW3btgEQERGBh4eHWftZ2wBCYRkl3S9ubnZcumSd/2OtaLfmlBDloSDXrDW3zC6CDh06\nxIoVK0hLK1rNff311+UalLhzBY/DAOLi4vjggw9YunQpSinWrFnDsWPH0Ol0ZGRkcPnyZSD/JvXx\n8Sn2eMePH6dr167aAPiuXbty7NgxAgIC8PT0pGnTpgA0b9682HujogQGBhbqJSqYtkEIc5R0v1y7\n5mWRe8nLy6vSz3mrW3NKiPJQkE+VnVvm5pTZRdDHH3/M8OHDuf/+++/qkYeoPD4+Ply5coXMzEwO\nHDhAZmYmERER2NraMnnyZHJycgDu+Bt+dnZ22s96vV473p1q1KgRp0+fpm3btnd1HCGEEMIcZg+M\nzs3NpV+/fjg6OqLX6wv9Edbp77//xmQyUbNmTbKzs6lVqxa2trYcOXLktr02tra25OXlAeDn58e+\nffu4fv06BoOBffv24e/vXyHxPvbYY6xevZpLl/IX2cvNzWXz5s0Vci4hiqPXK0uHIESVZK25ZXZP\n0ODBg9m4cSOPPfZYoRXkhXUpGBNUYPLkyej1enr16sWiRYuYOXMmTZs2xdvbu8RjDBgwgNDQUJo1\na8aUKVPo27cvs2fPBvIHRjdr1qxMk2SuW7euUDHz8ccfk5OTw8SJE7VtQ4YMYciQIVy+fJnXX38d\npRQ6nY5+/fqV5fKFuCtnzyZbOgQhqiRrzS2dUsqs8iw5OZnw8HCuXLlCzZo1C733wQcfVEhwQpgr\nKcm8mUitaRZcYTklzRg9fHgdvvvuQiVHYx1jgm51dnCApUMQVUBBrlV2bpX7mKC33noLPz8/evTo\nIWOCxD2r3vrd1WoQtYeHR7W53vK41uhoh3KK5t5XUqFoCdZ2H0s8t1dcPNaaW2YXQampqSxatEjG\nAAkhhBCiSjC7ogkICODIkSMVGYsQQgghRKUxuycoNzeXxYsX4+/vT61atQq99+9//7vcAxNCiMr2\n3nsXLR2CEFWSteaW2UVQo0aNaNSoUUXGIoQQQghRacwugkaMGFGRcQghhMVNmVKb4cOvWToMIaoc\na82tMq0dFhsby86dO7l48SK1a9emd+/eMruvEEIIIe5JZg+M/vXXX3n77bdxc3Oja9eu1K5dm3ff\nfVdbcE8IIYQQ4l5idk/Qpk2bmDt3rrZgJkDPnj1ZunSpLLonhKgSune/bukQhKiSrDW3zO4JunLl\nCg0bNiy0zcvLi6tXr5Z7UEIIYQmWmC1aiOrAWnPL7CLIz8+P//znP1y/nl/NGQwGVq9ejY+PT4UF\nJ4QQlalRowaWDkGIKslac8vsx2Hjx4/nnXfeYezYsbi4uHD16lV8fHyYOnVqRcYnRLlKGdrT0iFU\nqhRLB1CJ7vRab14ewmSSxaELWNM6e9Z2H0s8t5dC0WVXrDW3zC6Cateuzbx587hw4YL27bA6depU\nZGxCCCGEEBXG7MdhM2bMAKBOnTq0bNlSK4BmzpxZ6r5PPvkkoaGh2p/U1NQibTIyMli6dCkACQkJ\nxMTEmBtaIWFhYcTHx5dpn4L4QkJCiIiIICsr647OXRapqamEhIRU+nF//PFHRo4cSXZ2dpmPvWPH\nDiIjI+8mPCGsmqOjydIhCFElWWtumd0TdP78+SLblFKkpJTeEWdvb8+SJUtKfN9oNOLu7q79452Q\nkEB8fDydOnUyN7y7cnN8H3zwAT///DPDhg2rlHNXtt9//50WLVrwxx9/0K9fvwo9l9FoxMbGpkLP\nIUR5io8v+ntOCHH3rDW3Si2CPvjgAwDy8vK0nwukpaXd8VIaO3bsICYmhpycHK5fv87zzz/PokWL\nWLRoEV9//TU5OTkcP36coUOH4ubmxqpVqwDQ6XTMmzePGjVqsGHDBn777Tf0ej0dO3Zk5MiRAOzZ\ns4dPP/2U7OxsJk6ciL+/v9lx+fj4kJiYCORPDvn9999rvV2RkZG0aNGCvn378uWXX7J//35sbGxo\n3749Y8aMYc+ePXz77bfo9XqcnJyYN28eJpOJL7/8kqNHj5Kbm8tDDz3Egw8+WOL5DQYDixcvJisr\ni7y8PJ566im6dOlCamoqCxcuxNfXl7i4ONzd3ZkxYwb29vacPn2ajz76CHt7e/z8/Eo89vnz5zEY\nDIwbN45169ZpRdCOHTvYv38/169fJyUlha5duzJq1CgAoqKi2LBhA25ubjRo0AA7OzsAMjMzWbFi\nBRcu5I/4DwoKws/Pj7Vr13Lx4kXS0tKoWbMmw4YN48MPPyQvLw+lFCEhITRo0IAffviBqKgoAPr3\n78/gwYNve41CVIY+feqyc2eapcMQosqx1twqtQiqV69esT/rdDp8fX3p0aNHqSfJyckhNDQUAE9P\nT+3nuLg43nzzTVxcXLRHZLa2tjz55JPEx8fz3HPPARAREcFzzz2Hn58fBoMBOzs7Dhw4wP79+1mw\nYAEODg6FvqpvMplYuHAhMTExfPvtt7zyyivmfBaYTCaOHDlC//79b9vuypUr7N27l3feeQedTqc9\nPvv222+ZM2cO7u7u2rbt27fj5OTEwoULyc3N5ZVXXqFDhw4lHtvOzo7p06fj5OREZmYmc+bMISAg\nAIDk5GSmTp3KxIkTeeutt4iOjqZ37958+OGHPPvss7Ru3ZrVq1eXeOzdu3fTs2dP/Pz8SEpK4tKl\nS7i5uQH5vW+LFy/G1taWF198kYcffhgbGxvWrl3LokWLtKKuYJ6oVatWMWTIEPz8/EhPTyc8PJy3\n334bgNOnT/P6669jb2/PypUrGTRoEA888AB5eXmYTCZOnz5NVFQU4eHhAMyePZvWrVvj7Oxc4jXe\natu2bWzcuJHs7GwiIyPx8PC47d9ZAWsbQCgs7+Z759QpO7Pvparm1pwS4m7cmkfWmlulFkEFa4a1\natWKjh073tFJSnoc1r59e1xcXErdv+Dr+b169aJbt27UqVOHw4cP07dvXxwcHAAKHadr164ANG/e\nvNjxR7cqKNLS0tJo3rw57du3v217Jycn7O3t+eijj+jcuTOdO3cGwNfXl2XLltGjRw+6desGwMGD\nB0lMTCQ6OhqA7OxskpOTadCg+K8LKqVYs2YNx44dQ6fTkZGRweXLl4H8ArKgCGnevDlpaWlkZWWR\nlZVF69atAejduzf/+9//ij3277//zvTp09Hr9XTr1o3o6GgefvhhANq2bYuTkxMADRs2JD09nczM\nTNq0aYOrqysAPXr0IDk5GYDDhw9z7tw57djZ2dkYDAYAAgICtN4bHx8f1q1bx4ULF+jWrRsNGjTg\n+PHjdO3aFUdHRyD/7+vYsWMEBAQUe43FCQwMLDRJZ3p6erHthChN4XvHyyL3kpeXV6Wf81a35pQQ\nd6NoHlVubpmbU2aPCbK1tSU1NRVPT08uXbrEF198gV6v55lnntF6E8qqoIApzWOPPUanTp2IiYlh\nzpw5pfbsFDyy0ev1mEylD8YqKNKys7OJiIhgy5YtDBo0CBsbG5RSWrvc3FwAbGxsWLBgAYcPH2b3\n7t1s2bKF1157jQkTJnDy5EliYmKYMWMGixcvRilFcHBwkQKypOJs165dZGZmEhERga2tLZMnTyYn\nJ6fQdRVcW8F2cyQmJpKcnMwbb7wB5D/e9PT01IqgW49tNBpvezylFOHh4cU+qrr577VXr160bNmS\nmJgYwsPDmThx4m2PezfXKIQQQpSF2d8Oi4yMRK/Pb/75559jNBrR6XQsX7683INydHTk2rX/v9rs\n+fPnady4MY899hjNmzfn77//pn379uzYsUObvLG0maszMjKYP3/+bds4OTkRHBzMDz/8gNFoxMPD\ng3PnzpGbm0tWVhaHDx8G8sftZGdn06lTJ8aOHUtCQoIWZ6tWrXjyySepWbMmFy5coGPHjmzdupW8\nvDwAkpKStB6T4mRnZ1OrVi1sbW05cuRIiT0hBZydnXF2dub48eMA/Pbbb8W227VrFyNGjGDZsmUs\nW7aM5cuXk5GRcdvjt2rViqNHj3LlyhXy8vK03izI78XbsmWL9rrgM7hVSkoK9erVY9CgQQQEBPDX\nX3/h5+fHvn37uH79OgaDgX379pVp3JYQFWXLltJ7joUQZWetuWV2T1BGRgYeHh4YjUYOHjzIhx9+\niK2tLf/617/KPai2bduyceNGQkNDGTp0KMePHyc2NhadTkfDhg257777sLOzIyEhgZkzZ2Jra8t9\n993HM888U+IxL168aNY3lZo1a0bjxo35/fff6d27Nz169GD69Ok0aNCAZs2aAXDt2jUWL15Mbm4u\nSimCgoIA+OKLL7THRW3btqVJkyY0btyY1NRUXn75ZQBcXV21MVHF6dWrF4sWLWLmzJk0bdoUb2/v\nUmOeNGmSNjC6pPFGu3fvZtasWYW2de3ald9//73EnrzatWszYsQI5s6di5ubG82aNdN61oKDg4mM\njGT69OkYjUb8/f2ZMGFCkWPs2bOH//73v9jY2ODm5sbjjz+Oi4sLffv2Zfbs2UD+wOhmzZqZ9ehS\niIr000+OtGsnSwEJUd6sNbd06ubnPbcxceJEIiIiOHv2LN988w3z588nLy+P5557js8//7yi47xr\nW7ZswcPDQxtkLKqWpKQks9p5eHhUq/FD1el6y+Navb29+Ptv8+6l8mQNY4JuZW5OVQZru48lntsr\nLp7Kzq1yHxP08MMPM2vWLPLy8hg7diwAx48fN6unwhoUjH0RQgghhIAyFEGPPfYYXbt2Ra/XU79+\nfQDc3d1LHegqhBBCCGGNzC6CoGj3kjV24QohxJ0aNqzsy8kIIUpnrblldhH0/PPPl/jeRx99VC7B\nCCGEJb3//iVLhyBElWStuWV2EfTCCy8Uen3x4kU2b97M/fffX+5BCSGEJVhqYLQQVZ215pbZRVDB\njMQ3a9OmDeHh4QwaNKhcgxJCCCGEqGhmT5ZYnIJZpIUQQggh7jVm9wR9/fXXhV5fv36dAwcOcN99\n95V7UEIIYQkeHrdfLkYIcWesNbfMLoIuXLhQ6LWDgwOPPPIIDzzwQLkHJYQQlnDwYIqlQxCiSrLW\n3Cq1CDp+/Dj79+9n0qRJRd774osvOHPmDD4+PhUSnBBCVKYOHepZ7S9rIe5l1ppbpRZB69ev56GH\nHir2vbZt27Ju3TpmzpxZ7oEJURFShva0dAiVyvp+5VScu7lWm082AZCeXvr6gtWFcfyjlg5BY233\nscRze8XFk56+3+x7qiAfK0OpA6MTEhLo2LFjse+1a9eOM2fOlHtQQgghhBAVrdQi6Nq1a+Tl5RX7\nntFo5Nq1a+UelCjZ6NGj73jfHTt2EBkZWaZ9wsLCiI+P116npqYSEhICQHx8PCtXrrzjY5ckKyuL\nn3/+uVyOJYQQQpSk1CLI29ubgwcPFvvewYMH75kFVKsbpRQmk6lCz9GiRQueffbZcj2m0WgkKyuL\nrVu3lutxhTCHNU7mJkRVkDgowNIhFKvUMUGDBw9mxYoVmEwmunTpgl6vx2QysW/fPiIjIxkzZkxl\nxClusWnTJvbs2UNubi5du3bliSeeIDU1lYULF9KmTRvi4uIIDQ3lyJEjbNiwATc3Nxo0aICdnR0A\nmZmZrFixQvvWX1BQEH5+fmWKITY2lu+//77ImLBly5ZhZ2fHuXPnuHz5MmPGjKFz586YTCa+/PJL\njh49Sm5uLg899BAPPvggsbGxfPvtt7i5uZGQkECTJk04f/48oaGhtG/f/q56v4QoixdecLPa6f2F\nuJdN/d983u34qqXDKKLUIqhXr15cunSJZcuWkZubi6urK5mZmdjZ2fHEE0/Qq1evyohT3OTgwYMk\nJyezYMEClFIsXryYo0eP4uHhQVJSEs8//zzjxo3j4sWLrF27lkWLFuHk5MS8efNo2rQpAKtWrWLI\nkCH4+fmRnp5OeHg4b7/9drHne++997C3twcgLy8Pvb70OTbT0tIICwsjJSWFefPm0a5dO/773//i\n5OTEwoULyc3N5ZVXXqFDhw4AnDp1iqVLl+Lp6Ulqaipnz55lyZIl5fOBCWGmdeucpAgSogKsTxp0\nbxZBAEOGDKF///7ExcVx9epVXFxc8PHxwcnJqaLjE8U4ePAghw4dYsaMGQAYDAbOnz+Ph4cHHh4e\n2pQFJ0+epE2bNri6ugLQo0cPkpOTATh8+DDnzp3TjpmdnY3BYMDR0bHI+aZMmUKLFi2A/DFBixYt\nKjXGHj16oNfradCgAfXq1SMpKYmDBw+SmJhIdHS0ds7k5GRsbW1p2bIlnp6eZn8G27ZtY9u2bQBE\nRETg4eFh1n7W9i0KYR1uvn/MvZeqmltzSghLqcwcNHuyRCcnpxK/JSYq32OPPcaDDz5YaFtqamqx\nRUxxlFKEh4drPTwFwsPDuXTpEi1atGDixIl3HJ9Opyv2nMHBwUXuo9jYWBwcHMp0/MDAQAIDA7XX\n6enpdxaoENx8/3hZ5F7y8vKq9HPe6tacEsJSyiMHzc2pu1o7TFhGhw4diIqKwmAwAJCRkcHly5eL\ntGvVqhVHjx7lypUr5OXlaT0wAO3bt2fLli3a64SEBADmzJnDkiVL7qoAAoiOjsZkMnH+/HlSUlLw\n8vKiY8eObN26Vfu2YVJSknYNN6tRo4Z861BYxNSpmZYOQYgq6YUWn1o6hGKZ3RMkLM9oNGJnZ0eH\nDh34+++/mTNnDgCOjo688MILRcbq1K5dmxEjRjB37lzc3Nxo1qyZ9o2x4OBgIiMjmT59OkajEX9/\nfyZMmFBusTZo0ICwsDAuX77M+PHjsbe3p3///qSmpvLyyy8D4OrqSmhoaJF9a9asia+vLyEhIXTs\n2FEGRotK849/FC3KhRB37+H62y0dQrF0Sill6SCEeRISEli+fDkLFy60dCi3tWzZMjp37kz37t0r\n7ZxJSeZ9tdmaZsEV1qNghlpvby+LfE3eGh6H3ersYOv8SrO4NzXevN/sr8mXx4zR5uaU9ATdI7Zu\n3dj3Ie4AACAASURBVMpPP/3E2LFjLR3KPa3e+t3VavyQh4dHtbne6nStlaEyly4ojbX93Uo8t1ds\nPN7WdU8VkCLoHjFw4EAGDhxo6TDMMnnyZEuHIIQQQpRKBkYLIcQNLVvmWjoEIaoka80tKYKEEOKG\nnTvTLB2CEFWSteaWFEFCCHFDixb1LR2CEFWSteaWFEFCCHGDwSC/EoWoCNaaW9YZlRBCCCFEBZMi\nSAghbtDrZdo0ISqCteaWFEFCCHHD2bPJlg5BiCrJWnNLiiAhhLhh+PA6lg5BiCrJWnNLiiAhhLgh\nOtrB0iEIUSVZa27JjNGiWkkZ2tPSIVSqFEsHUInK51r3m7W+nDVO/1/erGmdPWu7jyWe2ys+HvNy\ny1zllYPSEySEEEKIakl6girAlStXmD9/PgCXLl1Cr9fj6uoKwMKFC7G1vfOP/ciRI9jb2+Pj41Mu\nsRZ45ZVXyMzMxN7enry8PB555BH69+9frucQwtq902GupUMQokqy1tySIqgC1KxZkyVLlgCwdu1a\nHB0defTRwt2ASimUUuj1ZeuMO3LkCDVr1iz3Ighg2rRpNG3alMzMTKZOnUqfPn2wsbExa1+j0Vio\n7a2vhRBCCGsjRVAlOn/+PEuWLMHX15dTp04xc+ZMvvnmG86cOUNOTg49e/bk8ccfB2DixIn079+f\n/fv3YzKZeOmll9Dr9fz666/o9Xp27NjBuHHjqF27Nh999BFXrlyhVq1aTJo0CTc3N6ZOncoHH3xA\nZmYm48ePZ/78+fj6+jJ37lymTJmCp6dniXEaDAYcHBy0Am358uUlxhgYGMjBgwcZNGgQmzdvpnXr\n1hw/fpyuXbvSpUuXO4otNTWVzz//HAC9Xs+8efNwdHSs4L8dIeDFg28wzHuLpcMQosqx1tySIqiS\nnTt3jkmTJjFhwgQARo4ciYuLC0ajkXnz5tG9e3caNmwIgJubG4sXL2bz5s388MMPTJgwgQEDBlCz\nZk0GDx4MwIIFC+jfvz8PPPAA27Zt47PPPiMkJIR69eqRlJTEuXPnaN68OceOHaNZs2Zcvny5xALo\n7bffxs7OjuTkZJ599ll0Ol2pMTo6OvL6668DsHnzZq5du8a8efPuKrZPP/2UCRMm0KpVKwwGA/b2\n9kVi3bZtGxs3biQ7O5vIyEg8PDzM+vytbQChuDeZe7/dS27NKSGsWXnloBRBlaxevXq0aNFCe71r\n1y6ioqIwGo1cvHiRc+fOaQVG165dAWjevDkHDhwo9ngnT55k5syZAPTu3Zuvv/4aAD8/P44ePcrf\nf//NY489RlRUFK1ataJly5YlxlbwOOzy5cvMnTuXjh3/X3v3HhdVnT5w/DOXAJFgGKAIFAURUtdL\nIXkNK/CVP7e1jTZ3bXM1tSS8VBobbGtp6WaBaZmKmWKSbWu72iav7KKUl2VNjcW7kAhJIHJHCHCE\nOb8/tGlR0EFh5izzvP+aGc453+f7nfPoM+d8zzmD8PLyumqMw4c3v9rqv99fb2yhoaGsX7+ekSNH\nMmTIkBaPAkVFRREVFWV5X1ZW1mq/hGhv7b2/+fn5tev2rsflOSWEml0rB63NKbk6zMacnX++V8KZ\nM2fYtm0bL774IklJSQwcOBCTyWT5+0033QRcPCVkNpvb1E6fPn04ceIEp06dIiwsjJqaGo4fP06f\nPn0AeOWVV4iLi+Odd965Yl0PDw969OjByZMnrxnjf/cHsOq01bVie/jhh3nyySdpaGggISGBM2fU\neadR0fkM8fzW3iEI0SmpNbekCLKj+vp6XFxc6NKlC5WVlRw8ePCa67i4uFBfX295HxISQkZGBgC7\nd++2FBK9e/fm2LFj6PV69Ho93bt3Z8eOHZa/z5s3j8TERMtpuf/W0NDA999/z6233npdMd5obMXF\nxfTo0YOHHnqIwMBAioqKrG5TiBvx0bDp9g5BiE5Jrbklp8PsKDAwkG7dulnmyYSGhl5znfDwcN54\n4w327dvH1KlTmTp1KqtWreLjjz+2TD6Gi0doPD09LVeR9enTh3379llOY7Vk6dKllkvkIyMj6dmz\nJ4qitDnGn1xvbFu3buXEiRNoNBoCAgIYOHCg1W0KcSN6fvoN+WOH2DsMITodteaWRlEUdT7aVYg2\nsPZokZrugivUJ+DTA5weO/iay7X3HaPVMCfocgW/vPY4CGEta3PLWtfKQWtzSoog0SlYWwR5e3s7\n1CRqR+pve/TV39+PwkLbn35VYxGkptPQatuPJZ6raykeW+eWTIwWQog2cnFp2wUIQgjrqDW3pAgS\nQohLcnOL7R2CEJ2SWnNLiiAhhLhk1Cgfe4cgRKek1tySIkgIIS45efIme4cgRKek1tySIkgIIYQQ\nDkmKICGEEEI4JCmChBDiks8+K7F3CEJ0SmrNLSmChBDikm3brv3sOyFE26k1t6QIEkKIS958093e\nIQjRKak1t6QIEkIIIYRDkgeoCody9qHh9g7Bps7aOwAbap++Hujw58u193PHOoqanrOntv1Y4rm6\nluO5MrfUkAtyJEgIIS55yO9Te4cgRKek1tySI0EqsH79enx8fPjlL38JwKJFi/Dy8iImJgaADRs2\nYDQaOXLkCPHx8Vesn5yczAMPPEC3bt3YvHkz0dHRVredlZXFxo0bASguLsZoNOLk5ESPHj2YOXPm\nDfctPT2dO++8E4PBcMPbEqKjvTnoRXuHIESnpNbckiNBKnD77beTnZ0NgNls5ty5cxQUFFj+np2d\nTWNjY6vrx8TE0K1bNwC2bNnSprYHDRpEYmIiiYmJ9OrVi9mzZ5OYmHhFAdTU1NSm7f7kq6++oqqq\n6rrWFcLWAj49YO8QhOiU1JpbciRIBUJCQnjvvfcA+OGHH+jevTtVVVXU1tbi7OxMYWEh48ePJysr\niyVLllBQUEBQUBCzZs1Co9Ewf/58Jk6cyN69ezGZTMTFxdG9e3dmz57Nrl272LZtG42NjfTu3Ztp\n06ah1VpX++7YsYPDhw/T0NDAhQsXmDt3LomJidTV1dHU1MSECRMICwujuLiYxMREgoOD+e677/D2\n9ua5557jwIED5Ofns3TpUpycnHj11Vc5evQo77//Pmaz2RLPqVOnSEtLY86cOezdu5cVK1aQkpJC\nY2MjcXFxLF++vCOHXwghhIOSIkgFjEYjWq2WsrIysrOzCQkJoaKigpycHFxdXQkICECv15OXl8cb\nb7yBp6cn8+bNIzs7m9tvv92ynd///vd89tlnJCYmAhcLqoyMDF555RX0ej3vvvsuu3fvZtSoUVbH\nlpOTw+uvv46bm5ulKHF1daW6upp58+YRFhYGQFFREU8//TQBAQEkJSWxf/9+RowYwbZt25g6dSo9\ne/bk/PnzrFq1ivnz5+Pr68tbb73F9u3biYqKIi8vD4ATJ07QrVs38vLyaGhoICQkpMW4tm/fzvbt\n2wFYvHgx3t7eVvVHbRMIheOxdl+1tctzSoiOpoZckCJIJUJDQ8nOziY7O5sHHnigWREUGhoKQHBw\nMF5eXgD07NmTkpKSZkXQ5Y4cOUJeXh4JCQkAmEwm3N3bdq+GAQMG4ObmZnn/wQcfcOLECTQaDeXl\n5Zw7dw4AX19fAgICAAgKCqK0tPSKbRUWFnLbbbfh6+sLQEREBOnp6YwZMwZvb2/OnDlDbm4uY8eO\n5fjx4zQ0NNCnT58W44qKiiIqKsryvqysrE39EqIl3k7lHd5GS/uqn59fh7d7LZfnlBDtqaXc6sh/\nt63NKSmCVOKnIqigoICAgAC8vb1JS0ujS5cu3HvvvQDcdNPPT+HVarWYzearblNRFEaNGsWjjz7a\n7PN9+/bx0UcfARfnE/Xq1avVbbi4/HyXz507d1JXV8drr72GTqcjJiaGCxcuAKDX/7wrabXaNs8h\n6tOnD5mZmTg5OdG/f39Wr16NyWTi8ccfb9N2hLgRmVH32zsEITolteaWTIxWidDQUDIzM3Fzc0Or\n1eLm5saPP/5ITk5Oq6eEWqLX6y2TqPv378/evXuprq4GoLa2ltLSUu66665mk6GtVVdXh7u7Ozqd\njkOHDlFRUXHNdbp06UJ9fT0A/v7+FBcXc/bsxZNSu3fvpm/fvsDFyeFpaWmEhoZiMBioqqqiuLjY\nMuFbCFu4c/vn9g5BiE5JrbklR4JUIiAggJqaGkaOHNnss4aGhjadwoqMjCQuLo7AwEBmz57N7373\nOxYuXIiiKOh0OqZOnYqPj891xRgREcFrr71GfHw8gYGB3Hbbbddc55577iE5OdkyMTomJoakpCTL\nxOifDr+HhIRQVVVlKYq6d+9OXV3ddcUpxPUqM3nZOwQhOiW15pZGURTF3kEIcaOKioqsWk5Nd8EV\n6hPw6QFOjx3coW20dJdcNcwJulzBLzt2HIRjaSm3OvKO0dbmlBRBolOwtgjy9vZ2qEnUjtTf9uir\nv78fhYXW7UvtSY1FkLU5ZQtq248lnqtrKR5b55a1OSVzgoQQ4hJ7FEBCOAK15pYUQUIIccmsWfJ4\nFyE6glpzS4ogIYS4ZPNmV3uHIESnpNbckiJICCGEEA5JiiAhhBBCOCQpgoQQ4pKnnz5n7xCE6JTU\nmltSBAkhxCX/938N9g5BiE5JrbklRZAQQlwyZswt9g5BiE5JrbklRZAQQgghHJI8O0w4lLMPDbd3\nCDZ11t4B2FD79PWAzR6t0pGPDGgPanrEjNr2Y4nn6lqOp31zq73yR44ECSHEJb265tk7BCE6JbXm\nlhRBQghxyVejHrF3CEJ0SmrNLSmCHNTEiRMtrzMzM3n66acpLS1tdfmSkhLmzp17w+3Onz+f3Nzc\nG96OEB0h5LPd9g5BiE5JrbklRZCDO3z4MCkpKSQkJODj42PvcISwqwZzF3uHIESnpNbckonRDuzY\nsWOsXr2ahIQEfH19AVixYgVhYWEMHToUuHjEKDU1tdl6JSUlvP3225w/fx6AKVOmEBoaSmVlJcuW\nLaOurg6z2cy0adPo06dPq+1PnDiRsWPHkpmZiZOTE3FxcRgMBqqqqlizZg0lJSUATJs2jdDQ0I4Y\nAiGEEA5MiiAH1djYSGJiIvPnz8ff379N63p4ePDnP/8ZJycnzpw5w5tvvsnixYvZs2cPAwcOJDo6\nGrPZbCmSWnP+/Hl69+7NhAkTeP/999mxYwcPP/wwKSkp9O3bl7i4OMxmMw0NV95ka/v27fzzn/+k\nrq6OtWvX4u3tbVXsaruKQqiLliabtWXtPmsrl+eUEO2pvXOrvfJHiiAHpdPpCA0NJT09nccff7xN\n6zY1NbF27Vry8/PRarWcOXMGgF69erFq1SoaGxu566676Nmz51W3o9frCQsLAyAoKIhDhw4BcOTI\nEWbOnAmAVqvF1fXKpw9HRUURFRVleV9WVtamPgjRkvyxQ2zW1n/vs35+fjZrtzWX55QQ7am9c+ta\n/+Zbm1MyJ8hBaTQann32WU6ePMnmzZstn+t0OsxmMwBms5nGxsYr1k1LS8PDw4PExEQWL15sWaZv\n374sWLAAo9HI8uXL2blz51Vj0Ol0aDQa4GKx09Rku1/hQrTkkX+vtncIQnRKas0tKYIcmLOzMwkJ\nCezZs4f09HQAfHx8OHXqFAAHDhxosTCpq6vD09MTrVbLrl27LEVTaWkpBoOBqKgo7rvvPvLyru++\nEP379+eLL74ALhZidXV117UdIdrqm8owe4cgRKek1tyS02EOzs3NjT/96U+89NJLuLu7ExkZSWJi\nIgkJCfTv3x9nZ+cr1rn//vtZsmQJe/fupV+/fpZljh49ytatW9HpdLi4uFhOabXV5MmTeeedd0hP\nT0er1fLEE08QEhJyQ/0UQgghLqdRFEWxdxBC3KiioiKrlvP29nao+UOO1N/26Ku/vx+FhdbtS+1J\nDXOCLmdtTtmC2vZjiefqWorH1rklc4KEEKKN3nqr0t4hCNEpqTW3pAgSQgghhEOSIkgIIS6ZPdvT\n3iEI0SmpNbekCBJCCCGEQ5IiSAghhBAOSa4OE0IIIYRDkiNBwqHEx8fbOwSbcqT+OlJfO5raxlLi\nuTqJ5/pJESSEEEIIhyRFkBBCCCEckm7+/Pnz7R2EELYUFBRk7xBsypH660h97WhqG0uJ5+oknusj\nE6OFEEII4ZDkdJgQQgghHJI8RV44jKysLFJSUjCbzURGRvLrX//a3iFZbcaMGbi4uKDVatHpdCxe\nvJja2lqWLl1KaWkpPj4+PPvss7i5uaEoCikpKfznP//B2dmZ2NhYy6Hpr7/+ms2bNwMQHR3NPffc\nA8CpU6dYsWIFJpOJO+64g8cffxyNRmOTvq1cuZLMzEw8PDxYsmQJgE361lobjszeOVJWVsaKFSuo\nqqpCo9EQFRXF2LFj7f5dmc1m4uPjMRqNxMfHU1JSwrJly6ipqSEoKIhZs2ah19vmv9Mff/yR5ORk\nCgoK0Gg0PPXUU/j5+dltfNLS0khPT0ej0dC9e3diY2Opqqqy2/i0mSKEA2hqalJmzpypFBcXKxcu\nXFCee+45paCgwN5hWS02Nlaprq5u9llqaqqyZcsWRVEUZcuWLUpqaqqiKIry7bffKosWLVLMZrOS\nnZ2tJCQkKIqiKDU1NcqMGTOUmpqaZq8VRVHi4+OV7OxsxWw2K4sWLVIyMzNt1rejR48qubm5ypw5\nc2zat9bacFRqyJGKigolNzdXURRFqaurU2bPnq0UFBTY/bvaunWrsmzZMuXVV19VFEVRlixZouzZ\ns0dRFEVZvXq18vnnn9ssluXLlyvbt29XFEVRLly4oNTW1tptfMrLy5XY2Fjl/PnziqJcHJevvvrK\nruPTVnI6TDiEkydP4uvry6233oper2f48OHs37/f3mHdkP379zNq1CgARo0aZenPgQMHiIiIQKPR\nEBISwo8//khlZSVZWVkMGDAANzc33NzcGDBgAFlZWVRWVlJfX09ISAgajYaIiAibjk3fvn2v+NVq\ni7611oajUkOOeHp6Wo7sdenSBX9/fyoqKuz6XZWXl5OZmUlkZCQAiqJw9OhRhg4dCsA999xjs3jq\n6uo4fvw49913HwB6vZ6uXbvadXzMZjMmk4mmpiZMJhMGg8Fu43M9VHp8Soj2VVFRgZeXl+W9l5cX\n3333nR0jartFixYBMHr0aKKioqiursbT8+JDCQ0GA9XV1cDFvnp7e1vW8/LyoqKi4ooxMBqNLX7+\n0/L2ZIu+tdaGo1JbjpSUlJCXl0dwcLBdv6v169fz2GOPUV9fD0BNTQ2urq7odDrg533NFkpKSnB3\nd2flypV8//33BAUFMXnyZLuNj9Fo5Fe/+hVPPfUUTk5ODBw4kKCgILuNz/WQIkiI/wGvvPIKRqOR\n6upqFi5ciJ+fX7O/azQam83hsTVb9K0zj9//ooaGBpYsWcLkyZNxdXVt9jdbflfffvstHh4eBAUF\ncfToUZu0eTVNTU3k5eUxZcoUevfuTUpKCh9//HGzZWw5PrW1tezfv58VK1bg6urKG2+8QVZWlk3a\nbi9yOkw4BKPRSHl5ueV9eXk5RqPRjhG1zU+xenh4EB4ezsmTJ/Hw8KCyshKAyspK3N3dLcuWlZVZ\n1v2pr5ePQUVFRYufq2FsbNG31tpwVGrZDxobG1myZAl33303Q4YMAez3XWVnZ3PgwAFmzJjBsmXL\nOHLkCOvXr6euro6mpibg533NFry8vPDy8qJ3794ADB06lLy8PLuNz+HDh7nllltwd3dHr9czZMgQ\nsrOz7TY+10OKIOEQevXqxZkzZygpKaGxsZGMjAwGDx5s77Cs0tDQYDkU39DQwKFDhwgICGDw4MHs\n3LkTgJ07dxIeHg7A4MGD2bVrF4qikJOTg6urK56engwaNIiDBw9SW1tLbW0tBw8eZNCgQXh6etKl\nSxdycnJQFIVdu3bZfWxs0bfW2nBUasgRRVFITk7G39+fBx54wPK5vb6rRx99lOTkZFasWMEzzzzD\nL37xC2bPnk2/fv3Yu3cvcPGqRFuNk8FgwMvLi6KiIuBiEdKtWze7jY+3tzffffcd58+fR1EUSzz2\nGp/rITdLFA4jMzOT9957D7PZzL333kt0dLS9Q7LK2bNnSUpKAi4eDh85ciTR0dHU1NSwdOlSysrK\nrriMfO3atRw8eBAnJydiY2Pp1asXAOnp6WzZsgW4eBn5vffeC0Bubi4rV67EZDIxaNAgpkyZYrND\n6suWLePYsWPU1NTg4eHB+PHjCQ8P7/C+tTZ+jszeOXLixAlefPFFAgICLPvfhAkT6N27t92/q6NH\nj7J161bi4+M5e/Ysy5Yto7a2lsDAQGbNmsVNN91kkzjy8/NJTk6msbGRW265hdjYWBRFsdv4bNq0\niYyMDHQ6HT179iQmJoaKigq7jU9bSREkhBBCCIckp8OEEEII4ZCkCBJCCCGEQ5IiSAghhBAOSYog\nIYQQQjgkKYKEEEII4ZCkCBKikzOZTIwfP77ZjfCEELbR0fm3adMm1q5d2yHbdgTy2Awh7GDixImW\n1yaTCb1ej1Z78TfJk08+yd13393qullZWaxdu5bly5e3SywvvPAC+fn5aLVanJyc6NevH9OmTXP4\nOyiLzktN+ffEE08wd+5cbr/9dstnX3zxBd988w3z5s275vrjx4+3vC4sLGTu3Ll8+OGH7RKbI5Ai\nSAg7SE1NtbyeMWMG06dPZ8CAAXaLZ/r06URERFBbW0tSUhIbN27kqaeesls8QnQkteWfsB8pgoRQ\nIZPJxIYNG9i3bx9arZYRI0YwYcIE6uvrSUxMpLGx0fJrduXKlRQWFrJhwwaKiopwdnZm2LBhTJw4\n0fIkZ2u5ubkxePBgdu/ebfnMbDazefNmvv76a+rr6xk4cCBTp06la9euLFiwgJEjRxIZGWlZ/pln\nnuEPf/gDd955J6dPnyYlJYX8/HwMBgMTJkzgrrvuAi7eKdpgMFBYWEh2djY9evRg9uzZ+Pj4tPiL\n9oUXXuD+++8nIiICgC+//JK0tDTOnTtHSEgI06dPV/UzisT/DnvlX0t+yoXp06fzt7/9jQsXLvDg\ngw8ybtw4ADZu3EhNTQ0xMTG89NJLmM1mS2wvv/wyTk5OJCcnc/r0afR6PXfccQczZ8684bg6C5kT\nJIQKbdq0idOnT5OUlMTixYs5duwYn3zyCTfffDNxcXHccsstpKamkpqays0334xer2fKlCmsW7eO\nBQsW8O2337Jjx442t3vu3Dn279+Pr6+v5bNPPvmEQ4cO8fLLL7Nq1Sp0Oh3vvfceACNGjOBf//qX\nZdlTp05RU1PDwIEDqaurY+HChdx3332sXbuWGTNmsGrVKoqLiy3L79mzhwkTJrBu3ToMBgObNm2y\nKs6MjAw+/fRTnn/+edasWUNgYGC7nZ4Qwl751xqz2Uxubi5vvfUWCQkJ/PWvf+Xs2bNXLLdgwQK0\nWq0ltsDAQD744APCw8NZv349q1atIioqqt3i6gykCBJChXbv3s348eNxd3fHYDAQHR3Nrl27Wl0+\nODiY4OBgtFotvr6+REZGcuzYMavbW7NmDZMmTWLatGmYTCYmTZpk+duXX37Jo48+itFoxMnJiUce\neYSMjAwURWHo0KFkZ2dbnmC9Z88ehg0bhk6nY9++fXTv3p27774brVZLcHAwYWFhlgcrAgwbNoyg\noCD0ej0jR44kPz/fqni//PJLoqOj8fPzQ6/X85vf/IYTJ05QVVVldZ+FaI2t888a48ePx8nJieDg\nYPz9/fn++++tWk+n01FaWkpVVRVOTk7N5h4JOR0mhOooikJVVRXe3t6Wz3x8fKioqGh1nR9++IEN\nGzaQl5eHyWSiqamJ0NBQq9t84okniIiIIC8vj9dff53KykqMRiOKolBeXs6rr77a7IGqiqJQU1OD\nu7s7AwYM4N///jdjxowhIyODZ555BoCysjKOHz/O5MmTLes1NTU1e7CjwWCwvHZ2dqahocGqeEtL\nS1mzZk2zq2K0Wi0VFRXNtilEW9k6/3Q6HY2Njc0+a2pqanYqTavVNrtQoS25MnnyZD788EP++Mc/\n4uHhwbhx4yynlIUUQUKojkajwWAwUFZWZjktVVZWdtX5LqtXr6Zv377MmTMHFxcXPv74Yw4fPtzm\ntgMDAxk3bhzr1q1j0aJFaDQajEYjzz33HEFBQS2uM2LECLZt20ZAQAA6nc7yj7+XlxcDBgwgPj6+\nzXE4OztjNpu5cOGC5enT/32Ux8vLi8cee4yhQ4e2edtCXI2t88/b25vS0tJmn5WUlDQrwtoS++WM\nRqPlSfPHjh1j4cKF9O3b97q23xnJ6TAhVGjEiBF89NFH1NTUUF1dzebNmy2X7RoMBs6dO9fsl2B9\nfT2urq64uLhQUFBwQ/MRIiMjKS4uJisrC4DRo0ezceNGysrKAKiurubAgQOW5cPDwykoKGDLli2M\nGDHC8g9xeHg4+fn5ZGRk0NjYSGNjIzk5ORQVFV0zBqPRiLu7O7t378ZsNvP55583+yU+evRoNm/e\nbNlWbW1ts9NsQtwIW+bf8OHDSUtL48yZMyiKQk5ODrt27WLEiBFtjtvd3R2z2WzJVbg4f66iogKN\nRkPXrl0BLLcDEHIkSAhV+u1vf8uGDRuYM2cOWq2W4cOH8+CDDwLQo0cPwsLCiI2NxWw28/bbbzNp\n0iTeffdd/v73v9OrVy+GDRtGbm7udbXt5OTEmDFj+Mc//sGgQYN48MEH0Wg0vPzyy1RVVeHh4UFE\nRASDBw8GLh61GTx4MHv27Gk2l8jNzY0XXniBDRs2WE5b9ezZs9npsdZotVpiYmJYt24dqampjB49\nutmRqJEjR2IymUhKSqK8vJyuXbsyaNAgOTIk2oUt8+/++++nvr6ev/zlL5w7dw5vb28mTZpEv379\n2hy3m5sb48aN4/nnn6epqYn58+eTk5PD+vXrqa+vx9PTU66ivIxGURTF3kEIIYQQQtiaHBMTQggh\nhEOSIkgIIYQQDkmKICGEEEI4JCmChBBCCOGQpAgSQgghhEOSIkgIIYQQDkmKICGEEEI4JCmCKfgu\nPwAAABRJREFUhBBCCOGQpAgSQgghhEP6f92rwEwwZ/maAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x35df8b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax0)\n",
    "ax0.set_xlim([-10000, 140000])\n",
    "ax0.set(title='Revenue', xlabel='Total Revenue', ylabel='Customers')\n",
    "\n",
    "# Plot the average as a vertical line\n",
    "avg = top_10['Sales'].mean()\n",
    "ax0.axvline(x=avg, color='b', label='Average', linestyle='--', linewidth=1)\n",
    "\n",
    "# Repeat for the unit plot\n",
    "top_10.plot(kind='barh', y=\"Purchases\", x=\"Name\", ax=ax1)\n",
    "avg = top_10['Purchases'].mean()\n",
    "ax1.set(title='Units', xlabel='Total Units', ylabel='')\n",
    "ax1.axvline(x=avg, color='b', label='Average', linestyle='--', linewidth=1)\n",
    "\n",
    "# Title the figure\n",
    "fig.suptitle('2014 Sales Analysis', fontsize=14, fontweight='bold');\n",
    "\n",
    "# Hide the legends\n",
    "ax1.legend().set_visible(False)\n",
    "ax0.legend().set_visible(False)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Saving figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'eps': 'Encapsulated Postscript',\n",
       " 'pdf': 'Portable Document Format',\n",
       " 'pgf': 'PGF code for LaTeX',\n",
       " 'png': 'Portable Network Graphics',\n",
       " 'ps': 'Postscript',\n",
       " 'raw': 'Raw RGBA bitmap',\n",
       " 'rgba': 'Raw RGBA bitmap',\n",
       " 'svg': 'Scalable Vector Graphics',\n",
       " 'svgz': 'Scalable Vector Graphics'}"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What are the supported formats for saving files\n",
    "fig.canvas.get_supported_filetypes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# As we are having fig object set we can just save it now\n",
    "fig.savefig('sales.png', transparent=False, dpi=80, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The saved photo is below\n",
    "![Sales data](sales.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}