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bgbg/before_and_after_stacked_bars.ipynb

Created November 26, 2020 11:04
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before_and_after_stacked_bars.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Before and after -- stacked bar charts"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A fellow data analyst asked a question? What do we do when we need to draw a stacked bar chart that has too many colors? How do we select the colors so that they are nice but also are easily distinguishable? To answer this question, let's look at the data similar to what appeared in the original question. I also tried to recreate the actual chart's style"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-26T11:03:15.911768Z",
"start_time": "2020-11-26T11:03:14.430546Z"
}
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pylab as plt\n",
"import seaborn as sns\n",
"%matplotlib inline\n",
"import datetime\n",
"plt.rcParams['figure.dpi'] = 220\n",
"plt.rcParams['figure.figsize'] = (8, 2.5)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-26T11:03:15.953267Z",
"start_time": "2020-11-26T11:03:15.913522Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>Region</th>\n",
" <th>us-east</th>\n",
" <th>us-west</th>\n",
" <th>us-central</th>\n",
" <th>asia-east1</th>\n",
" <th>asia-east2</th>\n",
" <th>asia-east3</th>\n",
" <th>australia-south</th>\n",
" <th>australia-north</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2020-03-31 00:00:00</th>\n",
" <td>61.2</td>\n",
" <td>5.8</td>\n",
" <td>37.3</td>\n",
" <td>58.7</td>\n",
" <td>17.0</td>\n",
" <td>0.6</td>\n",
" <td>85.5</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-04-01 00:00:00</th>\n",
" <td>16.9</td>\n",
" <td>6.8</td>\n",
" <td>9.5</td>\n",
" <td>81.4</td>\n",
" <td>8.2</td>\n",
" <td>1.8</td>\n",
" <td>72.6</td>\n",
" <td>1.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-04-02 00:00:00</th>\n",
" <td>44.6</td>\n",
" <td>20.8</td>\n",
" <td>5.9</td>\n",
" <td>43.1</td>\n",
" <td>31.0</td>\n",
" <td>1.6</td>\n",
" <td>44.3</td>\n",
" <td>0.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-04-03 00:00:00</th>\n",
" <td>77.9</td>\n",
" <td>5.8</td>\n",
" <td>72.1</td>\n",
" <td>3.7</td>\n",
" <td>4.1</td>\n",
" <td>2.9</td>\n",
" <td>88.0</td>\n",
" <td>3.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-04-04 00:00:00</th>\n",
" <td>30.5</td>\n",
" <td>1.6</td>\n",
" <td>63.5</td>\n",
" <td>46.4</td>\n",
" <td>19.5</td>\n",
" <td>2.8</td>\n",
" <td>37.5</td>\n",
" <td>5.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-04-05 00:00:00</th>\n",
" <td>14.9</td>\n",
" <td>14.4</td>\n",
" <td>67.2</td>\n",
" <td>10.5</td>\n",
" <td>14.6</td>\n",
" <td>1.6</td>\n",
" <td>29.7</td>\n",
" <td>1.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-04-06 00:00:00</th>\n",
" <td>3.2</td>\n",
" <td>13.4</td>\n",
" <td>66.2</td>\n",
" <td>82.7</td>\n",
" <td>12.2</td>\n",
" <td>1.1</td>\n",
" <td>2.5</td>\n",
" <td>2.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-04-07 00:00:00</th>\n",
" <td>42.0</td>\n",
" <td>5.5</td>\n",
" <td>79.3</td>\n",
" <td>70.8</td>\n",
" <td>21.8</td>\n",
" <td>1.9</td>\n",
" <td>3.4</td>\n",
" <td>1.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Region us-east us-west us-central asia-east1 asia-east2 \\\n",
"2020-03-31 00:00:00 61.2 5.8 37.3 58.7 17.0 \n",
"2020-04-01 00:00:00 16.9 6.8 9.5 81.4 8.2 \n",
"2020-04-02 00:00:00 44.6 20.8 5.9 43.1 31.0 \n",
"2020-04-03 00:00:00 77.9 5.8 72.1 3.7 4.1 \n",
"2020-04-04 00:00:00 30.5 1.6 63.5 46.4 19.5 \n",
"2020-04-05 00:00:00 14.9 14.4 67.2 10.5 14.6 \n",
"2020-04-06 00:00:00 3.2 13.4 66.2 82.7 12.2 \n",
"2020-04-07 00:00:00 42.0 5.5 79.3 70.8 21.8 \n",
"\n",
"Region asia-east3 australia-south australia-north \n",
"2020-03-31 00:00:00 0.6 85.5 0.5 \n",
"2020-04-01 00:00:00 1.8 72.6 1.3 \n",
"2020-04-02 00:00:00 1.6 44.3 0.3 \n",
"2020-04-03 00:00:00 2.9 88.0 3.3 \n",
"2020-04-04 00:00:00 2.8 37.5 5.4 \n",
"2020-04-05 00:00:00 1.6 29.7 1.8 \n",
"2020-04-06 00:00:00 1.1 2.5 2.8 \n",
"2020-04-07 00:00:00 1.9 3.4 1.5 "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dates = [str(d) for d in pd.date_range('2020-03-31', '2020-04-07 ')]\n",
"df = pd.DataFrame(columns=[\"Region\"] + dates, \n",
" data=[[\"us-east\",0,0,1,1,1,0,1,0],\n",
" [\"us-west\",1,0,1,1,0,1,1,0],\n",
" [\"us-central\",0,0,0,0,0,0,1,0],\n",
" [\"asia-east1\",1,0,1,1,1,0,1,1],\n",
" [\"asia-east2\",0,0,1,0,1,0,0,0],\n",
" [\"asia-east3\",0,1,1,1,1,0,1,0],\n",
" [\"australia-south\",0,0,1,1,0,1,1,0],\n",
" [\"australia-north\",0,0,0,1,0,0,1,0]]).set_index('Region')\n",
"np.random.seed(111)\n",
"deltas = [100, 20, 80, 100, 30, 2, 90, 10]\n",
"for i in range(len(deltas)):\n",
" d = np.random.rand(df.shape[1]) * deltas[i]\n",
" df.iloc[i] += d\n",
"df = np.round(df, 1).T\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-26T11:03:16.300786Z",
"start_time": "2020-11-26T11:03:15.955686Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 1760x550 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.style.use('dark_background')\n",
"df.plot(kind='bar', stacked=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So, how do we select colors? \n",
"The answer to this question is pretty complicated. To have a set of easily distinguishable colors, one needs to model the color perception in a typical human being properly. Luckily, a tool called [I What Hue](https://medialab.github.io/iwanthue/) that's based on a solid theory explained [here](https://medialab.github.io/iwanthue/theory/). The problem, however, isn't in colors. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## This is not the right question\n",
"\n",
"\n",
"Distinguishing between eight colors in a graph is a challenging task. Selecting the right color scheme might help, but it won't solve this fundamental problem. Moreover, stacked bar plots are tricky due to another complication. \n",
"\n",
"We, the humans, are somewhat good are comparing positions but not as good at comparing sizes. This is why comparing the heights of the bars is relatively easy. It is easy because the bars start at the same line, and our task is to compare the bar end position, not the bar size. Reading the heights of the lowest segment in the bars is also an easy task for the same reason: we don't compare the sizes but the heights. \n",
"\n",
"However, comparing the sizes of the middle components is more challenging. As a result, the intermediate parts of a graph don't add useful information but rather add noise. Thus, let us explain two options. First, we will reduce the number of groups. Next, we will explore what happens when reducing the number of groups is not an option.\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Option 1. Reduce the number of categories\n",
"\n",
"It is hard to advise about data visualization when I don't know what conclusion the author wants to convey. However, I am sure that in many cases, the number of categories that are relevant to the **viewer** is much smaller than the number of types that are relevant to the **analyst**. The viewer might not care about all the hard job you did while collecting the data; what they are about is an insight. For example, if we reduce the discussion to two groups: the USA and non-USA data centers, the graph becomes much more readable. "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-26T11:03:16.499963Z",
"start_time": "2020-11-26T11:03:16.303976Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1760x550 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_reduced = pd.DataFrame(index=df.index)\n",
"df_reduced['US'] = df[[c for c in df.columns if c.startswith('us')]].sum(axis=1)\n",
"df_reduced['non-US'] = df[[c for c in df.columns if not c.startswith('us')]].sum(axis=1)\n",
"df_reduced.plot(kind='bar', stacked=True, color=['C0', 'gray'])\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note how two groups in a stacked graph pose no problem in deciphering the sizes. If we take care of readability and improve the data-ink ratio, we get a nice data visualization piece."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-26T11:03:16.655801Z",
"start_time": "2020-11-26T11:03:16.502590Z"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1760x550 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots()\n",
"df_reduced.plot(kind='bar', stacked=True, color=['C0', 'gray'], ax=ax)\n",
"str_dates = pd.to_datetime(df_reduced.index).strftime('%b %d')\n",
"ax.set_xticklabels(str_dates, rotation=0)\n",
"sns.despine(ax=ax)\n",
"ax.set_yticks([0, 150, 300])\n",
"ax.set_ylim(0, 310)\n",
"ax.set_ylabel('Daily\\nerrors', rotation=0, ma='left', ha='right', y=1, color='gray')\n",
"ax.grid(False)\n",
"fig.set_facecolor(ax.get_facecolor())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Option 2. When reducing the number of categories is not an option\n",
"\n",
"But what if reducing the number of categories is not an option? If you are **absolutely** sure that the audience absolutely needs to see all the information, you can split the different groups into separate subgraphs. \n",
"\n",
"Have you noticed that the X-axis in our case represents time? In this case, we can replace the bars with an evolution plot and create a separate chart for each category in the data set. I took special care to keep the Y-axis scale equal between all the graphs so that the viewer can easily distinguish between data centers with a lot of errors and data centers with only a few of them. Here's the result:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-26T11:03:17.031640Z",
"start_time": "2020-11-26T11:03:16.658979Z"
}
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1760x550 with 8 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df.index = str_dates\n",
"n_regions = df.shape[1]\n",
"ncols = 4\n",
"nrows = int(np.ceil(n_regions / ncols))\n",
"fig, axes = plt.subplots(nrows, ncols, sharex=True, sharey=True)\n",
"for region, ax in zip(df.columns, axes.ravel()):\n",
" curr = df[region]\n",
" ax.plot(range(len(curr)), curr, '-o')\n",
" ax.set_title(region, x=0, ha='left', y=1, va='bottom', size='medium' )\n",
" ax.tick_params(axis='x', size=0)\n",
" sns.despine(ax=ax)\n",
" ax.grid(False)\n",
"for ax in axes[-1, :]:\n",
" tks = [0, 3, 7]\n",
" ax.set_xticks(tks)\n",
" ax.set_xticklabels([str_dates[i].replace(' ', '\\n') for i in tks])\n",
" sns.despine(ax=ax)\n",
"axes[0, 0].set_ylabel('Daily\\nerrors', rotation=0, ma='left', ha='right', y=1, va='top')\n",
"plt.tight_layout()\n",
"fig.set_facecolor(ax.get_facecolor())"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-26T11:03:17.037273Z",
"start_time": "2020-11-26T11:03:17.034402Z"
}
},
"outputs": [],
"source": [
"from matplotlib import gridspec"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Suppose the overall error rate is of greater importance than the individual groups. In that case, we can plot them in a larger graph and add the separate groups below, in smaller, un-emphasized subplots."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"ExecuteTime": {
"end_time": "2020-11-26T11:03:17.738594Z",
"start_time": "2020-11-26T11:03:17.040075Z"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1980x1980 with 9 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(figsize=(9, 9), dpi=220)\n",
"H = 5\n",
"spec = gridspec.GridSpec(ncols=1, nrows=H+df.shape[0], figure=fig)\n",
"small_axes = []\n",
"ax = fig.add_subplot(spec[0:H, :])\n",
"ax.set_xticks(range(len(df.index)))\n",
"ax.set_xticklabels(['' for _ in df.index])\n",
"ax.tick_params(axis='x', size=0)\n",
"sns.despine(ax=ax)\n",
"ax.plot(range(len(df)), df.sum(axis=0), '-o', color='C3')\n",
"ax.set_yticks([0, 200, 400])\n",
"ax.grid(False)\n",
"\n",
"ax.set_ylabel('Daily\\nerrors', rotation=0, ma='left', ha='right', y=1, va='top')\n",
"for i, region in enumerate(df.columns): \n",
" ax = fig.add_subplot(spec[H +i, 0])\n",
" ax.grid(False)\n",
" small_axes.append(ax)\n",
" curr = df[region]\n",
" ax.plot(range(len(curr)), curr, '-', color='gray')\n",
" ax.set_title(region,x=1, size='medium', ha='right', va='top' )\n",
" mx = int(np.ceil(ax.get_ylim()[1]))\n",
" ax.set_ylim((0, mx))\n",
" ax.set_yticks([0, mx])\n",
" sns.despine(ax=ax, bottom=False)\n",
" ax.set_xticks(range(len(str_dates)))\n",
" if i == len(df.columns) - 1:\n",
" ax.set_xticklabels(str_dates)\n",
" else:\n",
" ax.set_xticklabels(['' for _ in df.index])\n",
" ax.tick_params(axis='x', size=0)\n",
"fig.subplots_adjust(hspace=0.5)\n",
"fig.set_facecolor(ax.get_facecolor())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Summary -- the Why and the What define the How\n",
"\n",
"When you have a technical question about improving a graph, make sure you ask yourself \"why.\" Why is, does technical problems matter? Why will it improve the chart? To answer this question, you will have to ask another question: \"what?\". \"What is it that I want to say.\" The easiest way to force yourself to ask these questions is to force yourself to add titles to every graph you create (see my [how to suck less in data visualization](https://gorelik.net/2020/07/28/how-to-suck-less-in-data-visualization-and-professional-communication/) post for more details).\n",
"\n",
"Once you have your conclusion ready, you will notice that you don't need a technical solution but rather a conceptual one. In this case, we solved the technical problem of looking for eight distinct colors by reducing the number of categories to two or splitting one elaborate graph into several straightforward ones.\n",
"\n",
"So, remember, the Why and the What define the How"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"gist": {
"data": {
"description": "before_and_after_stacked_bars.ipynb",
"public": true
},
"id": ""
},
"hide_input": false,
"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": "3.8.5"
},
"notify_time": "5",
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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