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Created February 17, 2017 06:05
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Survey analysis for Armok Vision
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# The Armok Vision Survey\n",
"\n",
"[Armok Vision](http://www.bay12forums.com/smf/index.php?topic=146473) is a program to visualise [Dwarf Fortress](http://bay12games.com/dwarves/) locations with true 3D graphics, in real time. This survey ran [2016-11-10](http://www.bay12forums.com/smf/index.php?topic=146473.msg7257431#msg7257431) to [2017-01-09](http://www.bay12forums.com/smf/index.php?topic=146473.msg7319806#msg7319806), ie for the lifetime of version 0.14.\n",
"\n",
"As the maintainer of [the DF Starter Pack](http://dffd.bay12games.com/file.php?id=7622), I'm interested in what people use and why - and thought I'd share my exploration of the survey results."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Start by importing our standard packages\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The Armok Vision survey asked respondents questions in three categories:\n",
"\n",
"1. to rate four directions for development, and explain their reasoning\n",
"2. demographics - eg age, gender, period and frequency of playing DF\n",
"3. other comments, how they get Armok Vision, and what other visualisers they use\n",
"\n",
"Now let's check out the answers!\n",
"\n",
"(OK, first there's a lot of boring stuf to load the data. Just skip the next cell.)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"raw = pd.read_csv(\n",
" 'https://docs.google.com/spreadsheets/d/1Ndob7X4XjbWs3tL5_SvYYpxUYNMSKaN9bw3_4Qp5JhQ/export?format=csv',\n",
" parse_dates=['Timestamp'], )\n",
"\n",
"# clean up column names\n",
"df = raw.rename(columns={\n",
" 'How long have you been playing dwarf fortress?': 'df_age',\n",
" 'How often do you play dwarf fortress?': 'df_freq',\n",
" 'How often do you use Armok Vision?': 'av_freq',\n",
" 'Reasoning behind your rating': 'Reasoning_3D_dwarfs',\n",
" 'Reasoning behind your rating.1': 'Reasoning_Dwarf_Sprites',\n",
" 'Reasoning behind your rating.2': 'Reasoning_Control_Dwarf_Fortress',\n",
" 'Reasoning behind your rating.3': 'Reasoning_General_Artwork',\n",
" 'What other Dwarf Fortress Visualizers do you use?': 'other_visualisers',\n",
" 'Where do you get Armok Vision from, generally?': 'download',\n",
" })\n",
"# make category types categorical\n",
"df['Gender'] = df['Gender'].astype('category', categories=['Male', 'Female', 'Rather not say', 'write in']).fillna('write in')\n",
"df['Age'] = df['Age'].astype('category', ordered=True, categories=[\n",
" '10-15', '15-19', '20-24', '25-29', '30-34', '35-39', '40 and over'])\n",
"df['df_age'] = df['df_age'].astype('category', ordered=True, categories=[\n",
" 'I have never played dwarf fortress', 'Less than 1 year', '1-2 years', '2-5 years', 'More than 5 years'])\n",
"df['df_freq'] = df['df_freq'].astype('category', ordered=True, categories=[\n",
" \"I'm not sure.\", 'Rarely, if ever.', 'Once every month or so.', \n",
" 'Once or twice a week.', 'Daily', 'All day, every day.'])\n",
"df['av_freq'] = df['av_freq'].astype('category', ordered=True, categories=[\n",
" \"I haven't tried it yet.\", \"I've used it once or twice.\", 'I use it occasionally.',\n",
" 'I use it when I want to share screenshots.', 'I use it whenever I play Dwarf Fortress'])\n",
"df['download'] = df['download'].astype('category', categories=[\n",
" 'From a starter pack', 'Direct download from the Github release page', 'Other']).fillna('Other')\n",
"# Split 'Other visualisers' into boolean columns\n",
"known_vis = ['Dorven Realms', 'Dwarf Portrait', 'Isoworld', 'Legends Viewer', 'Stonesense', 'World Viewer']\n",
"df = pd.concat([df, pd.DataFrame(\n",
" [[k in r for k in known_vis] for r in df.other_visualisers.fillna('').str.split(', ')],\n",
" columns=['Uses ' + v for v in known_vis])], axis=1)\n",
"del df['Timestamp']\n",
"del df['other_visualisers']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Whew!\n",
"\n",
"Alright, we'll start with the summary tables for numeric and categorical columns."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>3D dwarfs</th>\n",
" <th>Dwarf Sprites</th>\n",
" <th>Control Dwarf Fortress</th>\n",
" <th>General Artwork</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>261.000000</td>\n",
" <td>261.000000</td>\n",
" <td>261.000000</td>\n",
" <td>261.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>6.107280</td>\n",
" <td>6.743295</td>\n",
" <td>7.019157</td>\n",
" <td>6.865900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>2.706826</td>\n",
" <td>2.290281</td>\n",
" <td>3.223056</td>\n",
" <td>2.342177</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>4.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>6.000000</td>\n",
" <td>7.000000</td>\n",
" <td>8.000000</td>\n",
" <td>7.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>8.000000</td>\n",
" <td>8.000000</td>\n",
" <td>10.000000</td>\n",
" <td>8.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>10.000000</td>\n",
" <td>10.000000</td>\n",
" <td>10.000000</td>\n",
" <td>10.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 3D dwarfs Dwarf Sprites Control Dwarf Fortress General Artwork\n",
"count 261.000000 261.000000 261.000000 261.000000\n",
"mean 6.107280 6.743295 7.019157 6.865900\n",
"std 2.706826 2.290281 3.223056 2.342177\n",
"min 1.000000 1.000000 1.000000 1.000000\n",
"25% 4.000000 5.000000 5.000000 5.000000\n",
"50% 6.000000 7.000000 8.000000 7.000000\n",
"75% 8.000000 8.000000 10.000000 8.000000\n",
"max 10.000000 10.000000 10.000000 10.000000"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.select_dtypes(include=[np.number]).dropna().describe()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Age</th>\n",
" <th>Gender</th>\n",
" <th>df_age</th>\n",
" <th>df_freq</th>\n",
" <th>av_freq</th>\n",
" <th>download</th>\n",
" <th>Uses Dorven Realms</th>\n",
" <th>Uses Dwarf Portrait</th>\n",
" <th>Uses Isoworld</th>\n",
" <th>Uses Legends Viewer</th>\n",
" <th>Uses Stonesense</th>\n",
" <th>Uses World Viewer</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>261</td>\n",
" <td>268</td>\n",
" <td>265</td>\n",
" <td>227</td>\n",
" <td>258</td>\n",
" <td>268</td>\n",
" <td>268</td>\n",
" <td>268</td>\n",
" <td>268</td>\n",
" <td>268</td>\n",
" <td>268</td>\n",
" <td>268</td>\n",
" </tr>\n",
" <tr>\n",
" <th>unique</th>\n",
" <td>7</td>\n",
" <td>4</td>\n",
" <td>5</td>\n",
" <td>6</td>\n",
" <td>5</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>top</th>\n",
" <td>20-24</td>\n",
" <td>Male</td>\n",
" <td>2-5 years</td>\n",
" <td>Once every month or so.</td>\n",
" <td>I haven't tried it yet.</td>\n",
" <td>From a starter pack</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>freq</th>\n",
" <td>78</td>\n",
" <td>239</td>\n",
" <td>90</td>\n",
" <td>71</td>\n",
" <td>88</td>\n",
" <td>206</td>\n",
" <td>256</td>\n",
" <td>218</td>\n",
" <td>215</td>\n",
" <td>189</td>\n",
" <td>148</td>\n",
" <td>243</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Age Gender df_age df_freq \\\n",
"count 261 268 265 227 \n",
"unique 7 4 5 6 \n",
"top 20-24 Male 2-5 years Once every month or so. \n",
"freq 78 239 90 71 \n",
"\n",
" av_freq download Uses Dorven Realms \\\n",
"count 258 268 268 \n",
"unique 5 3 2 \n",
"top I haven't tried it yet. From a starter pack False \n",
"freq 88 206 256 \n",
"\n",
" Uses Dwarf Portrait Uses Isoworld Uses Legends Viewer Uses Stonesense \\\n",
"count 268 268 268 268 \n",
"unique 2 2 2 2 \n",
"top False False False False \n",
"freq 218 215 189 148 \n",
"\n",
" Uses World Viewer \n",
"count 268 \n",
"unique 2 \n",
"top False \n",
"freq 243 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe(exclude=[np.number, object])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Development suggestions"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3D dwarfs 6.101124\n",
"Dwarf Sprites 6.741445\n",
"Control Dwarf Fortress 7.045455\n",
"General Artwork 6.856604\n",
"dtype: float64\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0xd95fc56128>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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XX37BzTffwpkzGbi6uhEQEICzswuvvTYHWd4QQoi6Y5NJQ32Xl2eYcvfw8CAwMIgmTZpy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"text/plain": [
"<matplotlib.figure.Figure at 0xd95fc52f98>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"nums = df[['3D dwarfs', 'Dwarf Sprites', 'Control Dwarf Fortress', 'General Artwork']]\n",
"print(nums.mean())\n",
"nums.apply(pd.Series.value_counts).plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Looking at the means and graph, people are less excited by 3D dwarves than the other options - though not by much.\n",
"Improving dwarf sprites and general artwork are about equally popular.\n",
"v0.15 improved the terrain substantially, and v0.16 can use any graphics pack for sprites, so I think people will be happy!\n",
"\n",
"And what to say about controlling DF? It's the most popular, but shows a very clear effect 'love it or *meh*' effect. I won't show the details, but this is true even for subgroups like infrequent players - which surprised me; I would expect a 3D interface to be more exciting for people not used to the 2D version. \n",
"\n",
"## Demographics\n",
"\n",
"Plot it all! I'll let you draw your own conclusions, too."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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z6HIzexZYn3AjvBG4AI2KlAYwd+4cTjzvRtYevkGU8t5+43mmHQ/jxo2PUp7k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\nJEmqziJTkiRJ1VlkSpIkqbp/AfiKsHi8sq6wAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd95ff580f0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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JkqT2eOZZkrokM79JUUDP9tiNwFG9jUiSJEnd4plnSZIkSZLmYPEsSZIkSdIc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J1MWQk4Zti1tShnoU8CdqiQaUQRsSjlg+SNKVu2v0z5UPl1wPrAMRGxDbB9Zs6qlVPS+ImIlUe4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\nJEmSJI3ifwC8KCpXNxZdqAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd95ff58940>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def plot(*cols):\n",
" fig, axes = plt.subplots(1, len(cols), figsize=(4 * len(cols), 3))\n",
" for cn, ax in zip(cols, axes):\n",
" chart = df[cn].value_counts().sort_index().plot.bar(ax=ax)\n",
" chart.set_title(cn)\n",
" \n",
"plot('Age', 'Gender')\n",
"plot('df_age', 'df_freq', 'av_freq')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Other visualisers\n",
"\n",
"What else do people use?"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0xd960a129e8>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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P1Q+OiG8B92XmQdXXmwBnADsBtwNHZOYlU/X4kiRpcqZkpCAiXgnsOebw+cA9wLbAOcB5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\nBQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd95ff07240>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df[['Uses ' + v for v in known_vis]].sum().plot.bar()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [default]",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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