{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(271116, 15)" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "import seaborn as sns\n", "\n", "df = pd.read_csv('athlete_events.csv')\n", "df.shape" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "male_df = df[df.Sex=='M']\n", "sport_weight_height_metrics = male_df.groupby(['Sport'])['Weight','Height'].agg(['min','max','mean'])" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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minmaxmean
Sport
Tug-Of-War75.0118.095.615385
Basketball59.0156.091.683529
Rugby Sevens65.0113.091.006623
Bobsleigh55.0145.090.387385
Beach Volleyball62.0110.089.512821
Handball62.0132.089.387914
Water Polo61.0125.087.706172
Volleyball56.0120.086.925926
Baseball38.0120.085.707792
Ice Hockey52.0116.083.775593
Rowing37.0137.083.665663
Judo52.0214.083.573945
Skeleton65.0127.082.018349
Curling61.0105.081.465686
Luge52.0112.080.803311
Weightlifting50.0176.580.251796
Canoeing53.0115.079.972378
Golf63.0104.079.245283
Sailing50.0130.078.849712
Tennis59.0111.078.842912
Alpine Skiing50.0107.078.626035
Swimming45.0114.078.040567
Shooting41.0140.077.834960
Rugby68.099.077.533333
Archery46.0130.077.066866
Motorboating77.077.077.000000
Snowboarding50.0102.076.861598
Lacrosse60.098.076.714286
Wrestling47.0190.076.400640
Speed Skating50.0100.076.300403
Fencing48.0108.075.381977
Art Competitions59.093.075.290909
Taekwondo54.0110.074.653595
Freestyle Skiing47.0108.074.648148
Badminton55.097.074.362536
Athletics42.0165.073.839129
Hockey48.0105.073.343761
Football28.0100.073.086644
Biathlon51.095.072.632123
Cycling48.0104.072.190234
Modern Pentathlon56.091.072.068824
Cross Country Skiing53.0100.071.700832
Table Tennis50.099.071.414239
Short Track Speed Skating51.086.071.401869
Equestrianism50.0100.070.924559
Figure Skating47.090.069.591644
Triathlon54.082.068.803774
Diving37.091.067.069378
Nordic Combined53.086.066.909560
Trampolining57.084.065.837838
Boxing46.0140.065.296280
Ski Jumping50.085.065.245881
Gymnastics46.0102.063.343605
\n", "
" ], "text/plain": [ " min max mean\n", "Sport \n", "Tug-Of-War 75.0 118.0 95.615385\n", "Basketball 59.0 156.0 91.683529\n", "Rugby Sevens 65.0 113.0 91.006623\n", "Bobsleigh 55.0 145.0 90.387385\n", "Beach Volleyball 62.0 110.0 89.512821\n", "Handball 62.0 132.0 89.387914\n", "Water Polo 61.0 125.0 87.706172\n", "Volleyball 56.0 120.0 86.925926\n", "Baseball 38.0 120.0 85.707792\n", "Ice Hockey 52.0 116.0 83.775593\n", "Rowing 37.0 137.0 83.665663\n", "Judo 52.0 214.0 83.573945\n", "Skeleton 65.0 127.0 82.018349\n", "Curling 61.0 105.0 81.465686\n", "Luge 52.0 112.0 80.803311\n", "Weightlifting 50.0 176.5 80.251796\n", "Canoeing 53.0 115.0 79.972378\n", "Golf 63.0 104.0 79.245283\n", "Sailing 50.0 130.0 78.849712\n", "Tennis 59.0 111.0 78.842912\n", "Alpine Skiing 50.0 107.0 78.626035\n", "Swimming 45.0 114.0 78.040567\n", "Shooting 41.0 140.0 77.834960\n", "Rugby 68.0 99.0 77.533333\n", "Archery 46.0 130.0 77.066866\n", "Motorboating 77.0 77.0 77.000000\n", "Snowboarding 50.0 102.0 76.861598\n", "Lacrosse 60.0 98.0 76.714286\n", "Wrestling 47.0 190.0 76.400640\n", "Speed Skating 50.0 100.0 76.300403\n", "Fencing 48.0 108.0 75.381977\n", "Art Competitions 59.0 93.0 75.290909\n", "Taekwondo 54.0 110.0 74.653595\n", "Freestyle Skiing 47.0 108.0 74.648148\n", "Badminton 55.0 97.0 74.362536\n", "Athletics 42.0 165.0 73.839129\n", "Hockey 48.0 105.0 73.343761\n", "Football 28.0 100.0 73.086644\n", "Biathlon 51.0 95.0 72.632123\n", "Cycling 48.0 104.0 72.190234\n", "Modern Pentathlon 56.0 91.0 72.068824\n", "Cross Country Skiing 53.0 100.0 71.700832\n", "Table Tennis 50.0 99.0 71.414239\n", "Short Track Speed Skating 51.0 86.0 71.401869\n", "Equestrianism 50.0 100.0 70.924559\n", "Figure Skating 47.0 90.0 69.591644\n", "Triathlon 54.0 82.0 68.803774\n", "Diving 37.0 91.0 67.069378\n", "Nordic Combined 53.0 86.0 66.909560\n", "Trampolining 57.0 84.0 65.837838\n", "Boxing 46.0 140.0 65.296280\n", "Ski Jumping 50.0 85.0 65.245881\n", "Gymnastics 46.0 102.0 63.343605" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sport_weight_height_metrics.Weight.dropna().sort_values('mean', ascending=False)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.distplot(sport_weight_height_metrics.Height.dropna()['mean'])" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "means = list(sport_weight_height_metrics.Weight.dropna()['mean'])\n", "sports = list(sport_weight_height_metrics.Weight.dropna().index)\n", "plot_data = sorted(zip(sports, means), key = lambda x:x[1])\n", "plot_data_dict = {\n", " 'x' : [i for i, _ in enumerate(plot_data)],\n", " 'y' : [v[1] for i, v in enumerate(plot_data)],\n", " 'group' : [v[0] for i, v in enumerate(plot_data)]\n", "}\n", "sns.scatterplot(data = plot_data_dict, x = 'x' , y = 'y')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "lightest:\n", "Gymnastics: 63.34360475924893\n", "Ski Jumping: 65.24588053553038\n", "Boxing: 65.29627979505457\n", "Trampolining: 65.83783783783784\n", "Nordic Combined: 66.9095595126523\n", "\n", "heaviest:\n", "Beach Volleyball: 89.51282051282051\n", "Bobsleigh: 90.38738521024649\n", "Rugby Sevens: 91.00662251655629\n", "Basketball: 91.68352893565358\n", "Tug-Of-War: 95.61538461538461\n" ] } ], "source": [ "print('lightest:')\n", "for sport,weight in plot_data[:5]:\n", " print(sport + ': ' + str(weight))\n", "\n", "print('\\nheaviest:') \n", "for sport,weight in plot_data[-5:]:\n", " print(sport + ': ' + str(weight))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "means = list(sport_weight_height_metrics.Height.dropna()['mean'])\n", "sports = list(sport_weight_height_metrics.Height.dropna().index)\n", "plot_data = sorted(zip(sports, means), key = lambda x:x[1])\n", "plot_data_dict = {\n", " 'x' : [i for i, _ in enumerate(plot_data)],\n", " 'y' : [v[1] for i, v in enumerate(plot_data)],\n", " 'group' : [v[0] for i, v in enumerate(plot_data)]\n", "}\n", "sns.scatterplot(data = plot_data_dict, x = 'x' , y = 'y')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "shortest:\n", "Gymnastics: 167.6444383959354\n", "Weightlifting: 169.1530612244898\n", "Trampolining: 171.3684210526316\n", "Diving: 171.55535224153707\n", "Wrestling: 172.87068623562078\n", "\n", "tallest:\n", "Rowing: 186.88269794721407\n", "Handball: 188.77837311251827\n", "Volleyball: 193.26565995525726\n", "Beach Volleyball: 193.29090909090908\n", "Basketball: 194.87262357414448\n" ] } ], "source": [ "print('shortest:')\n", "for sport,height in plot_data[:5]:\n", " print(sport + ': ' + str(height))\n", "\n", "print('\\ntallest:') \n", "for sport,height in plot_data[-5:]:\n", " print(sport + ': ' + str(height))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "mean_heights = sport_weight_height_metrics.Height.dropna()['mean']\n", "mean_weights = sport_weight_height_metrics.Weight.dropna()['mean']\n", "avg_build = mean_weights/mean_heights\n", "avg_build.sort_values(ascending = True)\n", "builds = list(avg_build.sort_values(ascending = True))\n", "\n", "plot_dict = {'x':[i for i,_ in enumerate(builds)],'y':builds}\n", "sns.lineplot(data=plot_dict, x='x', y='y')" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Sport\n", "Tug-Of-War 0.523977\n", "Rugby Sevens 0.497754\n", "Bobsleigh 0.496656\n", "Weightlifting 0.474433\n", "Handball 0.473507\n", "Judo 0.470872\n", "Basketball 0.470479\n", "Water Polo 0.469515\n", "Baseball 0.469376\n", "Beach Volleyball 0.463099\n", "Ice Hockey 0.462870\n", "Skeleton 0.452958\n", "Curling 0.450811\n", "Luge 0.450804\n", "Volleyball 0.449774\n", "Rowing 0.447691\n", "Golf 0.442746\n", "Shooting 0.442301\n", "Alpine Skiing 0.441989\n", "Wrestling 0.441953\n", "Canoeing 0.441318\n", "Lacrosse 0.440887\n", "Rugby 0.440288\n", "Sailing 0.437672\n", "Archery 0.431801\n", "Snowboarding 0.430534\n", "Art Competitions 0.430488\n", "Tennis 0.426529\n", "Speed Skating 0.425824\n", "Motorboating 0.425414\n", "Swimming 0.423418\n", "Freestyle Skiing 0.423074\n", "Fencing 0.418756\n", "Hockey 0.414717\n", "Badminton 0.413997\n", "Football 0.411801\n", "Athletics 0.410746\n", "Taekwondo 0.409244\n", "Short Track Speed Skating 0.406590\n", "Cycling 0.406144\n", "Biathlon 0.406092\n", "Table Tennis 0.403451\n", "Cross Country Skiing 0.403363\n", "Modern Pentathlon 0.402422\n", "Equestrianism 0.401695\n", "Figure Skating 0.395267\n", "Diving 0.390949\n", "Trampolining 0.384189\n", "Triathlon 0.381829\n", "Nordic Combined 0.379081\n", "Gymnastics 0.377845\n", "Boxing 0.377679\n", "Ski Jumping 0.369498\n", "Jeu De Paume NaN\n", "Polo NaN\n", "Racquets NaN\n", "Name: mean, dtype: float64" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "avg_build.sort_values(ascending=False)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sport_min_year = male_df.groupby('Sport').Year.agg(['min','max'])['min'].sort_values('index')\n", "year_count = {}\n", "for y in sport_min_year:\n", " try:\n", " year_count[y] += 1\n", " except:\n", " year_count[y] = 1\n", "year = [k for k,v in year_count.items()]\n", "new_sports = [v for k,v in year_count.items()]\n", "\n", "data = {'x':year, 'y':new_sports}\n", "sns.scatterplot(data=data, x = 'x', y='y')" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sport_max_year = male_df.groupby('Sport').Year.agg(['min','max'])['max'].sort_values('index')\n", "year_count = {}\n", "for y in sport_max_year:\n", " try:\n", " year_count[y] += 1\n", " except:\n", " year_count[y] = 1\n", "year = [k for k,v in year_count.items()]\n", "deprecated_sports = [v for k,v in year_count.items()]\n", "\n", "data = {'x':year, 'y':deprecated_sports}\n", "sns.scatterplot(data=data, x = 'x', y='y')" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Sport\n", "Basque Pelota 1900\n", "Croquet 1900\n", "Cricket 1900\n", "Roque 1904\n", "Jeu De Paume 1908\n", "Racquets 1908\n", "Motorboating 1908\n", "Lacrosse 1908\n", "Tug-Of-War 1920\n", "Rugby 1924\n", "Military Ski Patrol 1924\n", "Polo 1936\n", "Aeronautics 1936\n", "Alpinism 1936\n", "Art Competitions 1948\n", "Name: max, dtype: int64" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sport_max_year[sport_max_year <2000]" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Sport\n", "Biathlon 1960\n", "Luge 1964\n", "Volleyball 1964\n", "Judo 1964\n", "Table Tennis 1988\n", "Baseball 1992\n", "Short Track Speed Skating 1992\n", "Badminton 1992\n", "Freestyle Skiing 1992\n", "Beach Volleyball 1996\n", "Snowboarding 1998\n", "Taekwondo 2000\n", "Trampolining 2000\n", "Triathlon 2000\n", "Rugby Sevens 2016\n", "Name: min, dtype: int64" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sport_min_year[sport_min_year >1936]" ] } ], "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": "3.7.5" } }, "nbformat": 4, "nbformat_minor": 2 }