Waffle_Chart.ipynb

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    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches # needed for waffle Charts\n",
    "%matplotlib inline"
   ]
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   "source": [
    "### Parameters of the function `create_waffle_chart()` :"
   ]
  },
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    "1. **categories**: Unique categories or classes in dataframe.\n",
    "2. **values**: Values corresponding to categories or classes.\n",
    "3. **height**: Defined height of waffle chart.\n",
    "4. **width**: Defined width of waffle chart.\n",
    "5. **colormap**: Colormap class.\n",
    "6. **value_sign**: In order to make our function more generalizable, we will add this parameter to address signs that could be associated with a value such as %, $, and so on. **value_sign** has a default value of empty string."
   ]
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    "def create_waffle_chart(categories, values, height, width, colormap, value_sign=''):\n",
    "\n",
    "    # compute the proportion of each category with respect to the total\n",
    "    total_values = sum(values)\n",
    "    category_proportions = [(float(value) / total_values) for value in values]\n",
    "\n",
    "    # compute the total number of tiles\n",
    "    total_num_tiles = width * height # total number of tiles\n",
    "    print ('Total number of tiles is', total_num_tiles)\n",
    "    \n",
    "    # compute the number of tiles for each catagory\n",
    "    tiles_per_category = [round(proportion * total_num_tiles) for proportion in category_proportions]\n",
    "\n",
    "    # print out number of tiles per category\n",
    "    for i, tiles in enumerate(tiles_per_category):\n",
    "        print (df_dsn.index.values[i] + ': ' + str(tiles))\n",
    "    \n",
    "    # initialize the waffle chart as an empty matrix\n",
    "    waffle_chart = np.zeros((height, width))\n",
    "\n",
    "    # define indices to loop through waffle chart\n",
    "    category_index = 0\n",
    "    tile_index = 0\n",
    "\n",
    "    # populate the waffle chart\n",
    "    for col in range(width):\n",
    "        for row in range(height):\n",
    "            tile_index += 1\n",
    "\n",
    "            # if the number of tiles populated for the current category \n",
    "            # is equal to its corresponding allocated tiles...\n",
    "            if tile_index > sum(tiles_per_category[0:category_index]):\n",
    "                # ...proceed to the next category\n",
    "                category_index += 1       \n",
    "            \n",
    "            # set the class value to an integer, which increases with class\n",
    "            waffle_chart[row, col] = category_index\n",
    "    \n",
    "    # instantiate a new figure object\n",
    "    fig = plt.figure()\n",
    "\n",
    "    # use matshow to display the waffle chart\n",
    "    colormap = plt.cm.coolwarm\n",
    "    plt.matshow(waffle_chart, cmap=colormap)\n",
    "    plt.colorbar()\n",
    "\n",
    "    # get the axis\n",
    "    ax = plt.gca()\n",
    "\n",
    "    # set minor ticks\n",
    "    ax.set_xticks(np.arange(-.5, (width), 1), minor=True)\n",
    "    ax.set_yticks(np.arange(-.5, (height), 1), minor=True)\n",
    "    \n",
    "    # add dridlines based on minor ticks\n",
    "    ax.grid(which='minor', color='w', linestyle='-', linewidth=2)\n",
    "\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "\n",
    "    # compute cumulative sum of individual categories to match color schemes between chart and legend\n",
    "    values_cumsum = np.cumsum(values)\n",
    "    total_values = values_cumsum[len(values_cumsum) - 1]\n",
    "\n",
    "    # create legend\n",
    "    legend_handles = []\n",
    "    for i, category in enumerate(categories):\n",
    "        if value_sign == '%':\n",
    "            label_str = category + ' (' + str(values[i]) + value_sign + ')'\n",
    "        else:\n",
    "            label_str = category + ' (' + value_sign + str(values[i]) + ')'\n",
    "            \n",
    "        color_val = colormap(float(values_cumsum[i])/total_values)\n",
    "        legend_handles.append(mpatches.Patch(color=color_val, label=label_str))\n",
    "\n",
    "    # add legend to chart\n",
    "    plt.legend(\n",
    "        handles=legend_handles,\n",
    "        loc='lower center', \n",
    "        ncol=len(categories),\n",
    "        bbox_to_anchor=(0., -0.2, 0.95, .1)\n",
    "    )"
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