{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Who is the best character in Mario Kart? This is actually a non-trivial question, because the characters have widely varying stats across a number of attributes (for the unfamiliar, Mario Kart is a video game where you select characters from the Nintendo universe and race them against each other in cartoonish go-karts). The question is compounded when you consider the modifications introduced by the the various karts and tires players can select from. In general it isn't possible to optimize across multiple dimensions simultaneously, however some setups are undeniably worse than others. The question for an aspiring Mario Kart champion is \"How can one pick a character / kart / tire combination that is in some sense optimal, even if there isn't one 'best' option?\" To answer this question we turn to one of Mario's compatriots, the nineteenth century Italian economist Vilfredo Pareto who introduced the concept of [Pareto efficiency](https://en.wikipedia.org/wiki/Pareto_efficiency) and the related [Pareto frontier](https://en.wikipedia.org/wiki/Pareto_efficiency#Pareto_frontier).\n", "\n", "The concept of Pareto efficiency applies to situations where a finite pool of resources is being allocated among several competing groups. A particular allocation is said to be Pareto efficient if it is impossible to increase the portion assigned to any group without also decreasing the portion assigned to some other group. The set of allocations which are Pareto efficient define the Pareto frontier. As with many things, this is more easily explained with a picture (courtesy of wikipedia)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The elements in red lie on the Pareto frontier: for each element in the set an increase along one axis requires a decrease along the other. \n", "\n", "We can apply this same concept to Mario Kart: the resources are total stat points and the groups are the individual attributes, for instance, speed, acceleration, or traction. (In general, characters in Mario Kart have the same number of total stat points, and differ only in their allocation). Speed and acceleration are generally the two most important attributes of any given setup, so the goal of this post is to identify those configurations that lie on the Pareto frontier for speed and acceleration." ] }, { "cell_type": "code", "execution_count": 82, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import itertools as it\n", "\n", "from sklearn.cluster import KMeans\n", "\n", "sns.set_context('talk')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As usual, we start with a little data wrangling to get things into a form we can use. One particular quirk of Mario Kart is that while there are a couple dozen characters, lots of them have identical stats. We'll start by picking out one character from each stat group to use in this analysis (and then do the same for karts and tires)." ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# originally from https://github.com/woodnathan/MarioKart8-Stats, added DLC and fixed a few typos\n", "bodies = pd.read_csv('bodies.csv')\n", "chars = pd.read_csv('characters.csv')\n", "gliders = pd.read_csv('gliders.csv')\n", "tires = pd.read_csv('tires.csv')\n", "\n", "# use only stock (non-DLC) characters / karts / tires\n", "chars = chars.loc[chars['DLC']==0]\n", "bodies = bodies.loc[bodies['DLC']==0]\n", "tires = tires.loc[tires['DLC']==0]\n", "gliders = gliders.loc[gliders['DLC']==0]\n", "\n", "stat_cols = bodies.columns[2:-1]\n", "main_cols = ['Weight','Speed','Acceleration','Handling','Traction']\n", "\n", "# lots of characters/karts/tires are exactly the same. here we just want one from each stat type\n", "chars_unique = chars.drop_duplicates(subset=stat_cols).set_index('Character')[stat_cols].sort('Weight')\n", "bodies_unique = bodies.drop_duplicates(subset=stat_cols).set_index('Body')[stat_cols].sort('Acceleration')\n", "tires_unique = tires.drop_duplicates(subset=stat_cols).set_index('Tire')[stat_cols].sort('Speed')\n", "\n", "n_uniq_chars = len(chars_unique)\n", "n_uniq_bodies = len(bodies_unique)\n", "n_uniq_tires = len(tires_unique)\n", "\n", "# add a column indicating which category each character/kart/tire is in\n", "chars['char_class'] = KMeans(n_uniq_chars, random_state=0).fit_predict(chars[stat_cols])\n", "bodies['body_class'] = KMeans(n_uniq_bodies).fit_predict(bodies[stat_cols])\n", "tires['tire_class'] = KMeans(n_uniq_tires).fit_predict(tires[stat_cols])\n", "\n", "# change the character class labels so that they correspond to weight order\n", "# without DLC\n", "char_class_dict = dict(zip([3, 0, 5, 4, 2, 6, 1], [0, 1, 2, 3, 4, 5, 6]))\n", "# with DLC\n", "# char_class_dict = dict(zip([0, 3, 2, 7, 8, 4, 1, 6, 5], [0, 1, 2, 3, 4, 5, 6, 7, 8]))\n", "chars['char_class'] = chars['char_class'].apply(lambda c: char_class_dict[c])\n", "\n", "# only two types of gliders, one of which is pretty clearly just better\n", "glider_best = gliders.loc[gliders['Glider']=='Flower']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From here on out, I'll refer to the character (or kart, or tire) class by the name of its first member. For example, in the heatmap below the row labelled 'Peach' also describes the stats for Daisy and Yoshi. The complete class memberships are listed at the end of the post in case you want to see where your favorite character lands.\n", "\n", "There are seven classes of characters, let's have a look at how their stats compare." ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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JSeaIlIWFBTVq1GDBggVA5pBMhw4dqFmzJgAfffQRa9as4cSJE9StW5egoCCK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\ndBZohcfr2bOn8vX1VQsXLlQHDx5UycnJxmULFy5UNWrUUPv27VMGg0E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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot a heatmap of the stats for each component class\n", "fig, ax = plt.subplots(1,1, figsize=(8,5))\n", "\n", "sns.heatmap(chars_unique[main_cols], annot=True, ax=ax, linewidth=1, fmt='.3g')\n", " \n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The most obvious trend is the trade-off between speed and acceleration; heavy characters have good speed but bad acceleration, while light characters have snappy acceleration but a low top speed. There are variations in the other stats as well, but to a large extend the speed and acceleration dominate the performace of a particular setup so we'll be ignoring the rest of the stats.\n", "\n", "Karts and tires modify the base stats of the characters; the final configuration is a sum of the character's stats and the kart / tire modifiers. As with characters, there are dozens of karts and tires but only a few categories with different stats." ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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QpsjMKyiSoJi51JQUQ4dgdKz/evCV9E120jc5k77JmfRNzqz/9aC9PGXmCYpM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\nmjukfyU/P5+8vDxuvtFj9uzZZ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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot a heatmap of the stats for each component class\n", "fig, axes = plt.subplots(2,1, figsize=(8,10))\n", "\n", "tables = [bodies_unique, tires_unique]\n", "keys = ['Body', 'Tire']\n", "\n", "for ax, table, key in zip(axes, tables, keys):\n", " sns.heatmap(table[main_cols], annot=True, ax=ax, linewidth=1, fmt='.3g')\n", " \n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The trends here are less obvious, but they generally agree with what we saw in the character stats: improvements in speed come at the expense of acceleration, and vice versa.\n", "\n", "Our goal is to find all the configurations that have an optimal combination of speed and acceleration, so the next step is to compute the stats for each unique (character, kart, tire) combination." ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def check(char_name, body_type, tire_type):\n", " # find the stats for each element of the configuration\n", " character = chars.loc[chars['Character']==char_name]\n", " kart = bodies.loc[bodies['Body']==body_type]\n", " wheels = tires.loc[tires['Tire']==tire_type]\n", "\n", " # the total stats for the configuration are just the sum of the components\n", " stats = pd.concat([character[stat_cols], kart[stat_cols], wheels[stat_cols], glider_best[stat_cols]]).sum()\n", " \n", " # index the row by the configuration (character, kart, tire)\n", " index = pd.MultiIndex.from_tuples([(char_name, body_type, tire_type)], names=['Character', 'Body', 'Tire'])\n", " \n", " df = pd.DataFrame(stats).transpose()\n", " df.index = index\n", " return df\n", "\n", "# generate list of tuples for every possible configuration\n", "config_all = it.product(chars_unique.index, bodies_unique.index, tires_unique.index)\n", "\n", "# generate a dataframe with stats for each unique configuration\n", "config_base = pd.DataFrame()\n", "for (c,b,t) in config_all:\n", " this_config = check(c,b,t)\n", " config_base = config_base.append(this_config)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Equipped with the statistics for each possible combination, we can can plot the speed vs the acceleration of each possible setup, and identify those that lie on the Pareto frontier." ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# returns True if the row is at the pareto frontier for variables xlabel and ylabel\n", "def is_pareto_front(row, xlabel, ylabel):\n", " \n", " x = row[xlabel]\n", " y = row[ylabel]\n", " \n", " # look for points with the same y value but larger x value\n", " is_max_x = config_base.loc[config_base[ylabel]==y].max()[xlabel] <= x\n", " # look for points with the same x value but larger y value\n", " is_max_y = config_base.loc[config_base[xlabel]==x].max()[ylabel] <= y\n", " # look for points that are larger in both x and y\n", " is_double = len(config_base.loc[(config_base[xlabel]>x) & (config_base[ylabel]>y)])==0\n", " \n", " return is_max_x and is_max_y and is_double\n", "\n", "# array of True/False indicating whether the corresponding row is on the pareto frontier\n", "is_pareto = config_base.apply(lambda row: is_pareto_front(row, 'Speed', 'Acceleration'), axis=1)\n", "\n", "# just the configurations that are on the pareto frontier\n", "config_pareto = config_base.ix[is_pareto].sort('Speed')" ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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CfkbcNWtkwGPKEadcHbXm/f0LtLm9AICPvq3A8/dcEvCYvk5tApBm0uHheeMC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\np9IhO759TYGDtiOwtNSEOKLeCVohr6y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Xv/oVJk2ahF//+tcoKSnBCy+8gPHjxwMAvv76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\nSUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot all the configurations\n", "fig, ax = plt.subplots(1,1, figsize=(8,5))\n", "sns.regplot(x='Speed', y='Acceleration', data=config_base, fit_reg=False, ax=ax)\n", " \n", "# plot the pareto frontier\n", "plt.plot(config_pareto['Speed'], config_pareto['Acceleration'], '--', label='Pareto frontier', alpha=0.5)\n", "\n", "plt.xlim([0.75,6]);\n", "plt.legend(loc='best');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Looks like the optimal configurations make up a fairly small subset of the total possible setups. In fact, we can quantify this." ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Possible combinations : 149760\n", "Unique stat combinations : 294\n", "Optimal combinations : 15\n" ] } ], "source": [ "# number of possible combinations\n", "print('Possible combinations : ',len(list(it.product(chars.index, bodies.index, tires.index, gliders.index))))\n", "\n", "# number of combinations with different statistics\n", "print('Unique stat combinations : ',len(config_base.drop_duplicates(subset=stat_cols)))\n", "\n", "# number of optimal combinations (considering only speed and acceleration)\n", "print('Optimal combinations : ',len(config_pareto))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's have a look at what these optimal configurations look like." ] }, { "cell_type": "code", "execution_count": 81, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Speed Acceleration\n", "Character Body Tire \n", "Baby Mario Biddybuggy Roller 1.00 5.75\n", "Toad Biddybuggy Roller 1.50 5.50\n", "Peach Biddybuggy Roller 2.00 5.25\n", "Mario Biddybuggy Roller 2.50 5.00\n", "Donkey Kong Biddybuggy Roller 3.00 4.75\n", "Wario Biddybuggy Roller 3.50 4.50\n", "Donkey Kong Sports Bike Roller 3.75 4.25\n", "Wario Sports Bike Roller 4.25 4.00\n", " Wood 4.50 3.25\n", " Biddybuggy Slick 4.50 3.25\n", "Donkey Kong Sports Bike Slick 4.75 3.00\n", "Wario Gold Standard Roller 4.75 3.00\n", " Sports Bike Standard 4.75 3.00\n", " Slick 5.25 2.75\n", " Gold Standard Slick 5.75 1.75\n" ] } ], "source": [ "print(config_base.ix[is_pareto][['Speed','Acceleration']].sort('Speed'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Unless you're going all-in on acceleration, it looks like a heavy character is the way to go; the two heaviest character classes (Wario and Donkey Kong) account for 11/15 of the Pareto-optimal configurations.\n", "\n", "We can also look at the other main stats for each of these configurations." ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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qVasWISEhpKSkEB8fz+7du6V9PD092bZtG0+fPiUtLY3vvvsOyEtgXV1duXLl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TAyMsrTYvW+sLW1xdfXVxrnBqCnp0fdunXR0dGRZt6OGTOGKVOm0Lp1a2rUqMHQoUO5e/cud+7c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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1,1, figsize=(8,7))\n", "sns.heatmap(config_pareto[main_cols].sort('Speed'), annot=True, ax=ax, linewidth=1, fmt='.3g');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So there it is, if speed and acceleration are your main concerns then one of these 15 configurations is your best bet.\n", "\n", "Sometimes an optimal configuration isn't what you're looking for though (say, because your roommate threatened to stop playing if there wasn't some sort of handicap, to choose a random example). In that case, we can explore all the possible configurations with a quick [bokeh](http://bokeh.pydata.org/en/latest/) interactive graphic. I'll omit the code here, but you can find it in the [notebook](/notebooks/mario-kart.ipynb) for this post." ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ " \n", " \n", " \n", " \n", "
\n", " \n", " BokehJS successfully loaded.\n", "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# note: needs modifications from https://github.com/josherick/bokeh/tree/2715_add_callbacks_to_groups to work\n", "from bokeh.io import output_notebook, show\n", "from bokeh.plotting import figure, ColumnDataSource\n", "from bokeh.models import HoverTool, CustomJS\n", "from bokeh.models.widgets import CheckboxButtonGroup\n", "\n", "from bokeh.models.widgets import Dropdown\n", "from bokeh.io import output_file, show, vform\n", "\n", "output_notebook()\n", "output_file('bokeh_plot.html')" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", "
\n", "\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def rgb_to_hex(rgb_tuple):\n", " tuple_255 = tuple([int(255*c) for c in rgb_tuple])\n", " hex_str = '#%02x%02x%02x' % tuple_255\n", " return hex_str\n", "\n", "# make the color palette for plotting\n", "palette = sns.color_palette(\"Set1\", n_colors=n_uniq_chars)\n", "pal_hex = [rgb_to_hex(color) for color in palette]\n", "\n", "# collect all the data from each df (chars, bodies, tires)\n", "bokeh_data = config_base.join(chars.set_index('Character')['char_class'])\\\n", ".join(bodies.set_index('Body')['body_class'])\\\n", ".join(tires.set_index('Tire')['tire_class'])\n", "\n", "\n", "# store all the original data in this ColumnDataSource\n", "source_all = ColumnDataSource(\n", " data = dict(\n", " x=config_base['Speed'],\n", " y=config_base['Acceleration'],\n", " character=config_base.index.get_level_values('Character'),\n", " kart=config_base.index.get_level_values('Body'),\n", " tire=config_base.index.get_level_values('Tire'),\n", " char_class=bokeh_data.char_class,\n", " color=[pal_hex[i] for i in bokeh_data['char_class']]\n", " )\n", ")\n", "\n", "# store just what is currently being shown in the plot in this CDS\n", "source_plot = ColumnDataSource(\n", " data = dict(\n", " x=config_base['Speed'],\n", " y=config_base['Acceleration'],\n", " character=config_base.index.get_level_values('Character'),\n", " kart=config_base.index.get_level_values('Body'),\n", " tire=config_base.index.get_level_values('Tire'),\n", " char_class=bokeh_data.char_class,\n", " color=[pal_hex[i] for i in bokeh_data['char_class']]\n", " )\n", ")\n", "\n", "hover = HoverTool()\n", "hover.tooltips = [\n", " (\"Character\", \"@character\"),\n", " (\"Kart\", \"@kart\"),\n", " (\"Tires\", \"@tire\")\n", "]\n", "\n", "# some javascript to update the plot based on which characters are selected\n", "callback = CustomJS(args=dict(s_all=source_all, s_plot=source_plot), code=\"\"\"\n", " var data = s_all.get('data');\n", " var show_class = cb_obj.get('active')\n", " x = data['x']\n", " y = data['y']\n", " char_class = data['char_class']\n", " \n", " var d2 = s_plot.get('data');\n", " d2['x'] = []\n", " d2['y'] = []\n", " d2['character'] = []\n", " d2['kart'] = []\n", " d2['tire'] = []\n", " d2['char_class'] = []\n", " d2['color'] = []\n", " \n", " var colors = '#e41a1c,#377eb7,#4dae4a,#994ea1,#ff8100,#fdfb32,#a7572b,#f481bd,#999999'.split(',');\n", " \n", " for (i = 0; i < x.length; i++) {\n", " if(show_class.indexOf(char_class[i]) != -1)\n", " { \n", " d2['x'].push(data['x'][i])\n", " d2['y'].push(data['y'][i])\n", " d2['character'].push(data['character'][i])\n", " d2['kart'].push(data['kart'][i])\n", " d2['tire'].push(data['tire'][i])\n", " d2['char_class'].push(data['char_class'][i])\n", " d2['color'].push(colors[data['char_class'][i]])\n", " }\n", " }\n", "\n", " s_plot.trigger('change');\n", " \n", " for (i = 0; i < speed.length; i++) {\n", " if(blockedTile.indexOf(\"118\") != -1)\n", " { \n", " // element found\n", " }\n", " y[i] = Math.pow(x[i], f)\n", " }\n", " source.trigger('change');\n", " \"\"\")\n", "\n", "# make checkboxes for each character class\n", "checkbox_group = CheckboxButtonGroup(\n", " labels=list(config_base.index.get_level_values('Character').unique()), \n", " active=list(range(n_uniq_chars)),\n", " callback=callback)\n", "\n", "TOOLS = [hover]\n", "\n", "p = figure(plot_width=600, plot_height=600, y_range=(0.8,6), x_range=(0.8, 6), tools=TOOLS)\n", "\n", "p.circle('x', 'y', size=8, source=source_plot, fill_color='color', line_color='#000000')\n", "\n", "# janky way to do custom legend: plot 1 point for each color, then cover with white circle\n", "for char, color in zip(chars_unique.index.values, pal_hex):\n", " p.circle(1.5, 1.5, size=8, line_color='#000000', fill_color=color, legend=char)\n", "p.circle(1.5, 1.5, size=10, fill_color='#FFFFFF', line_color='#FFFFFF')\n", "\n", "p.xaxis.axis_label = 'Speed'\n", "p.yaxis.axis_label = 'Acceleration'\n", "\n", "\n", "show(vform(checkbox_group,p)) # show the results" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A few observations:\n", "\n", "- Heavy characters are more versatile than light characters. While Wario's possible configurations can achieve about 77% of the max acceleration, Baby Mario can only get up to 50% of the max speed.\n", "- Metal Mario / Pink Gold Peach are the only characters that have no configurations on the Pareto frontier. \n", "- The Badwagon really is bad. Nearly every configuration on the 'anti-Pareto frontier' (i.e. the worst possible combinations) involves karts from the Badwagon class.\n", "\n", "And finally, in case you have a particular attachment to one of the characters (or karts / tires) you can look up which class he / she / it belongs to below. " ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Character Classes\n", "*****************\n", "Baby Mario, Baby Luigi, Baby Peach, Baby Daisy, Baby Rosalina, Lemmy Koopa, Mii Light\n", "Toad, Shy Guy, Koopa Troopa, Lakitu, Wendy Koopa, Larry Koopa, Toadette\n", "Peach, Daisy, Yoshi\n", "Mario, Luigi, Iggy Koopa, Ludwig Koopa, Mii Medium\n", "Donkey Kong, Waluigi, Rosalina, Roy Koopa\n", "Metal Mario, Pink Gold Peach\n", "Wario, Bowser, Morton Koopa, Mii Heavy\n", "\n", "Body Classes\n", "*****************\n", "Standard Kart, Prancer, Cat Cruiser, Sneeker, The Duke, Teddy Buggy\n", "Gold Standard, Mach 8, Circuit Special, Sports Coupe\n", "Badwagon, TriSpeeder, Steel Driver, Standard ATV\n", "Biddybuggy, Landship, Mr. Scooty\n", "Pipe Frame, Standard Bike, Flame Ride, Varmit, Wild Wiggler\n", "Sports Bike, Jet Bike, Comet, Yoshi Bike\n", "\n", "Tire Classes\n", "*****************\n", "Standard, Blue Standard, Offroad, Retro Offroad\n", "Monster, Hot Monster\n", "Slick, Cyber Slick\n", "Roller, Azure Roller, Button\n", "Slim, Crimson Slim\n", "Metal, Gold\n", "Wood, Sponge, Cushion\n", "\n" ] } ], "source": [ "# print out the various components, grouped by category\n", "tables = [chars, bodies, tires]\n", "keys = ['char_class', 'body_class', 'tire_class']\n", "columns = ['Character', 'Body', 'Tire']\n", "\n", "for table, key, col in zip(tables, keys, columns):\n", " print(col + ' Classes')\n", " print('*****************')\n", " for class_ in table[key].unique():\n", " class_list = table.loc[table[key]==class_][col].values\n", " print(', '.join(class_list))\n", " \n", " print()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The IPython notebook for this post is [here](/notebooks/mario-kart.ipynb) and the data is [here](/data/mariokart.tar.gz)." ] } ], "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": "3.4.3" } }, "nbformat": 4, "nbformat_minor": 0 }