python - How to get the count of a group based on another group and plot the result

Question

• I have the following dataset of the Olympic games.
• I am trying to find out the number of won medals(I want to see them separate Gold/Silver/Bronze) of all sports in a specific country.
  • In Germany how many medals(Gold/Silver/Bronze) have been won for Football, Gymnastics, etc.

I want to display them after that in something like this:

but instead of the countries there, I want to see the sport types.

I tried something like this:

athletes = pd.read_csv('athlete_events.csv')
athlete_GER=athletes.loc[athletes["NOC"]=="GER",:] 
df=athlete_GER.groupby("Sport")
df=df["Sport",'Medal']

I have no idea how to count and separate the Medals into Gold/Silver/Bronze

The dataset can be found here: https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results

Can anyone explain to me how to achieve that?

Data Sample

ID,Name,Sex,Age,Height,Weight,Team,NOC,Games,Year,Season,City,Sport,Event,Medal
1,A Dijiang,M,24.0,180.0,80.0,China,CHN,1992 Summer,1992,Summer,Barcelona,Basketball,Basketball Men's Basketball,
2,A Lamusi,M,23.0,170.0,60.0,China,CHN,2012 Summer,2012,Summer,London,Judo,Judo Men's Extra-Lightweight,
3,Gunnar Nielsen Aaby,M,24.0,,,Denmark,DEN,1920 Summer,1920,Summer,Antwerpen,Football,Football Men's Football,
4,Edgar Lindenau Aabye,M,34.0,,,Denmark/Sweden,DEN,1900 Summer,1900,Summer,Paris,Tug-Of-War,Tug-Of-War Men's Tug-Of-War,Gold
5,Christine Jacoba Aaftink,F,21.0,185.0,82.0,Netherlands,NED,1988 Winter,1988,Winter,Calgary,Speed Skating,Speed Skating Women's 500 metres,
5,Christine Jacoba Aaftink,F,21.0,185.0,82.0,Netherlands,NED,1988 Winter,1988,Winter,Calgary,Speed Skating,"Speed Skating Women's 1,000 metres",
5,Christine Jacoba Aaftink,F,25.0,185.0,82.0,Netherlands,NED,1992 Winter,1992,Winter,Albertville,Speed Skating,Speed Skating Women's 500 metres,
5,Christine Jacoba Aaftink,F,25.0,185.0,82.0,Netherlands,NED,1992 Winter,1992,Winter,Albertville,Speed Skating,"Speed Skating Women's 1,000 metres",
5,Christine Jacoba Aaftink,F,27.0,185.0,82.0,Netherlands,NED,1994 Winter,1994,Winter,Lillehammer,Speed Skating,Speed Skating Women's 500 metres,
5,Christine Jacoba Aaftink,F,27.0,185.0,82.0,Netherlands,NED,1994 Winter,1994,Winter,Lillehammer,Speed Skating,"Speed Skating Women's 1,000 metres",
6,Per Knut Aaland,M,31.0,188.0,75.0,United States,USA,1992 Winter,1992,Winter,Albertville,Cross Country Skiing,Cross Country Skiing Men's 10 kilometres,
6,Per Knut Aaland,M,31.0,188.0,75.0,United States,USA,1992 Winter,1992,Winter,Albertville,Cross Country Skiing,Cross Country Skiing Men's 50 kilometres,
6,Per Knut Aaland,M,31.0,188.0,75.0,United States,USA,1992 Winter,1992,Winter,Albertville,Cross Country Skiing,Cross Country Skiing Men's 10/15 kilometres Pursuit,
6,Per Knut Aaland,M,31.0,188.0,75.0,United States,USA,1992 Winter,1992,Winter,Albertville,Cross Country Skiing,Cross Country Skiing Men's 4 x 10 kilometres Relay,
6,Per Knut Aaland,M,33.0,188.0,75.0,United States,USA,1994 Winter,1994,Winter,Lillehammer,Cross Country Skiing,Cross Country Skiing Men's 10 kilometres,
6,Per Knut Aaland,M,33.0,188.0,75.0,United States,USA,1994 Winter,1994,Winter,Lillehammer,Cross Country Skiing,Cross Country Skiing Men's 30 kilometres,
6,Per Knut Aaland,M,33.0,188.0,75.0,United States,USA,1994 Winter,1994,Winter,Lillehammer,Cross Country Skiing,Cross Country Skiing Men's 10/15 kilometres Pursuit,
6,Per Knut Aaland,M,33.0,188.0,75.0,United States,USA,1994 Winter,1994,Winter,Lillehammer,Cross Country Skiing,Cross Country Skiing Men's 4 x 10 kilometres Relay,
7,John Aalberg,M,31.0,183.0,72.0,United States,USA,1992 Winter,1992,Winter,Albertville,Cross Country Skiing,Cross Country Skiing Men's 10 kilometres,

7,John Aalberg,M,31.0,183.0,72.0,United States,USA,1992 Winter,1992,Winter,Albertville,Cross Country Skiing,Cross Country Skiing Men's 50 kilometres,
7,John Aalberg,M,31.0,183.0,72.0,United States,USA,1992 Winter,1992,Winter,Albertville,Cross Country Skiing,Cross Country Skiing Men's 10/15 kilometres Pursuit,
7,John Aalberg,M,31.0,183.0,72.0,United States,USA,1992 Winter,1992,Winter,Albertville,Cross Country Skiing,Cross Country Skiing Men's 4 x 10 kilometres Relay,
7,John Aalberg,M,33.0,183.0,72.0,United States,USA,1994 Winter,1994,Winter,Lillehammer,Cross Country Skiing,Cross Country Skiing Men's 10 kilometres,
7,John Aalberg,M,33.0,183.0,72.0,United States,USA,1994 Winter,1994,Winter,Lillehammer,Cross Country Skiing,Cross Country Skiing Men's 30 kilometres,
7,John Aalberg,M,33.0,183.0,72.0,United States,USA,1994 Winter,1994,Winter,Lillehammer,Cross Country Skiing,Cross Country Skiing Men's 10/15 kilometres Pursuit,
7,John Aalberg,M,33.0,183.0,72.0,United States,USA,1994 Winter,1994,Winter,Lillehammer,Cross Country Skiing,Cross Country Skiing Men's 4 x 10 kilometres Relay,
8,"Cornelia ""Cor"" Aalten (-Strannood)",F,18.0,168.0,,Netherlands,NED,1932 Summer,1932,Summer,Los Angeles,Athletics,Athletics Women's 100 metres,
8,"Cornelia ""Cor"" Aalten (-Strannood)",F,18.0,168.0,,Netherlands,NED,1932 Summer,1932,Summer,Los Angeles,Athletics,Athletics Women's 4 x 100 metres Relay,
9,Antti Sami Aalto,M,26.0,186.0,96.0,Finland,FIN,2002 Winter,2002,Winter,Salt Lake City,Ice Hockey,Ice Hockey Men's Ice Hockey,
10,"Einar Ferdinand ""Einari"" Aalto",M,26.0,,,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Swimming,Swimming Men's 400 metres Freestyle,
11,Jorma Ilmari Aalto,M,22.0,182.0,76.5,Finland,FIN,1980 Winter,1980,Winter,Lake Placid,Cross Country Skiing,Cross Country Skiing Men's 30 kilometres,
12,Jyri Tapani Aalto,M,31.0,172.0,70.0,Finland,FIN,2000 Summer,2000,Summer,Sydney,Badminton,Badminton Men's Singles,
13,Minna Maarit Aalto,F,30.0,159.0,55.5,Finland,FIN,1996 Summer,1996,Summer,Atlanta,Sailing,Sailing Women's Windsurfer,
13,Minna Maarit Aalto,F,34.0,159.0,55.5,Finland,FIN,2000 Summer,2000,Summer,Sydney,Sailing,Sailing Women's Windsurfer,
14,Pirjo Hannele Aalto (Mattila-),F,32.0,171.0,65.0,Finland,FIN,1994 Winter,1994,Winter,Lillehammer,Biathlon,Biathlon Women's 7.5 kilometres Sprint,
15,Arvo Ossian Aaltonen,M,22.0,,,Finland,FIN,1912 Summer,1912,Summer,Stockholm,Swimming,Swimming Men's 200 metres Breaststroke,
15,Arvo Ossian Aaltonen,M,22.0,,,Finland,FIN,1912 Summer,1912,Summer,Stockholm,Swimming,Swimming Men's 400 metres Breaststroke,
15,Arvo Ossian Aaltonen,M,30.0,,,Finland,FIN,1920 Summer,1920,Summer,Antwerpen,Swimming,Swimming Men's 200 metres Breaststroke,Bronze
15,Arvo Ossian Aaltonen,M,30.0,,,Finland,FIN,1920 Summer,1920,Summer,Antwerpen,Swimming,Swimming Men's 400 metres Breaststroke,Bronze
15,Arvo Ossian Aaltonen,M,34.0,,,Finland,FIN,1924 Summer,1924,Summer,Paris,Swimming,Swimming Men's 200 metres Breaststroke,
16,Juhamatti Tapio Aaltonen,M,28.0,184.0,85.0,Finland,FIN,2014 Winter,2014,Winter,Sochi,Ice Hockey,Ice Hockey Men's Ice Hockey,Bronze
17,Paavo Johannes Aaltonen,M,28.0,175.0,64.0,Finland,FIN,1948 Summer,1948,Summer,London,Gymnastics,Gymnastics Men's Individual All-Around,Bronze
17,Paavo Johannes Aaltonen,M,28.0,175.0,64.0,Finland,FIN,1948 Summer,1948,Summer,London,Gymnastics,Gymnastics Men's Team All-Around,Gold
17,Paavo Johannes Aaltonen,M,28.0,175.0,64.0,Finland,FIN,1948 Summer,1948,Summer,London,Gymnastics,Gymnastics Men's Floor Exercise,
17,Paavo Johannes Aaltonen,M,28.0,175.0,64.0,Finland,FIN,1948 Summer,1948,Summer,London,Gymnastics,Gymnastics Men's Horse Vault,Gold
17,Paavo Johannes Aaltonen,M,28.0,175.0,64.0,Finland,FIN,1948 Summer,1948,Summer,London,Gymnastics,Gymnastics Men's Parallel Bars,
17,Paavo Johannes Aaltonen,M,28.0,175.0,64.0,Finland,FIN,1948 Summer,1948,Summer,London,Gymnastics,Gymnastics Men's Horizontal Bar,
17,Paavo Johannes Aaltonen,M,28.0,175.0,64.0,Finland,FIN,1948 Summer,1948,Summer,London,Gymnastics,Gymnastics Men's Rings,
17,Paavo Johannes Aaltonen,M,28.0,175.0,64.0,Finland,FIN,1948 Summer,1948,Summer,London,Gymnastics,Gymnastics Men's Pommelled Horse,Gold
17,Paavo Johannes Aaltonen,M,32.0,175.0,64.0,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Gymnastics,Gymnastics Men's Individual All-Around,
17,Paavo Johannes Aaltonen,M,32.0,175.0,64.0,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Gymnastics,Gymnastics Men's Team All-Around,Bronze
17,Paavo Johannes Aaltonen,M,32.0,175.0,64.0,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Gymnastics,Gymnastics Men's Floor Exercise,
17,Paavo Johannes Aaltonen,M,32.0,175.0,64.0,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Gymnastics,Gymnastics Men's Horse Vault,
17,Paavo Johannes Aaltonen,M,32.0,175.0,64.0,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Gymnastics,Gymnastics Men's Parallel Bars,
17,Paavo Johannes Aaltonen,M,32.0,175.0,64.0,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Gymnastics,Gymnastics Men's Horizontal Bar,
17,Paavo Johannes Aaltonen,M,32.0,175.0,64.0,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Gymnastics,Gymnastics Men's Rings,
17,Paavo Johannes Aaltonen,M,32.0,175.0,64.0,Finland,FIN,1952 Summer,1952,Summer,Helsinki,Gymnastics,Gymnastics Men's Pommelled Horse,
18,Timo Antero Aaltonen,M,31.0,189.0,130.0,Finland,FIN,2000 Summer,2000,Summer,Sydney,Athletics,Athletics Men's Shot Put,
19,Win Valdemar Aaltonen,M,54.0,,,Finland,FIN,1948 Summer,1948,Summer,London,Art Competitions,"Art Competitions Mixed Sculpturing, Unknown Event",
20,Kjetil Andr Aamodt,M,20.0,176.0,85.0,Norway,NOR,1992 Winter,1992,Winter,Albertville,Alpine Skiing,Alpine Skiing Men's Downhill,
20,Kjetil Andr Aamodt,M,20.0,176.0,85.0,Norway,NOR,1992 Winter,1992,Winter,Albertville,Alpine Skiing,Alpine Skiing Men's Super G,Gold
20,Kjetil Andr Aamodt,M,20.0,176.0,85.0,Norway,NOR,1992 Winter,1992,Winter,Albertville,Alpine Skiing,Alpine Skiing Men's Giant Slalom,Bronze
20,Kjetil Andr Aamodt,M,20.0,176.0,85.0,Norway,NOR,1992 Winter,1992,Winter,Albertville,Alpine Skiing,Alpine Skiing Men's Slalom,
20,Kjetil Andr Aamodt,M,22.0,176.0,85.0,Norway,NOR,1994 Winter,1994,Winter,Lillehammer,Alpine Skiing,Alpine Skiing Men's Downhill,Silver
20,Kjetil Andr Aamodt,M,22.0,176.0,85.0,Norway,NOR,1994 Winter,1994,Winter,Lillehammer,Alpine Skiing,Alpine Skiing Men's Super G,Bronze
20,Kjetil Andr Aamodt,M,22.0,176.0,85.0,Norway,NOR,1994 Winter,1994,Winter,Lillehammer,Alpine Skiing,Alpine Skiing Men's Giant Slalom,
20,Kjetil Andr Aamodt,M,22.0,176.0,85.0,Norway,NOR,1994 Winter,1994,Winter,Lillehammer,Alpine Skiing,Alpine Skiing Men's Slalom,
20,Kjetil Andr Aamodt,M,22.0,176.0,85.0,Norway,NOR,1994 Winter,1994,Winter,Lillehammer,Alpine Skiing,Alpine Skiing Men's Combined,Silver
20,Kjetil Andr Aamodt,M,26.0,176.0,85.0,Norway,NOR,1998 Winter,1998,Winter,Nagano,Alpine Skiing,Alpine Skiing Men's Downhill,
20,Kjetil Andr Aamodt,M,26.0,176.0,85.0,Norway,NOR,1998 Winter,1998,Winter,Nagano,Alpine Skiing,Alpine Skiing Men's Super G,
20,Kjetil Andr Aamodt,M,26.0,176.0,85.0,Norway,NOR,1998 Winter,1998,Winter,Nagano,Alpine Skiing,Alpine Skiing Men's Giant Slalom,
20,Kjetil Andr Aamodt,M,26.0,176.0,85.0,Norway,NOR,1998 Winter,1998,Winter,Nagano,Alpine Skiing,Alpine Skiing Men's Combined,
20,Kjetil Andr Aamodt,M,30.0,176.0,85.0,Norway,NOR,2002 Winter,2002,Winter,Salt Lake City,Alpine Skiing,Alpine Skiing Men's Downhill,
20,Kjetil Andr Aamodt,M,30.0,176.0,85.0,Norway,NOR,2002 Winter,2002,Winter,Salt Lake City,Alpine Skiing,Alpine Skiing Men's Super G,Gold
20,Kjetil Andr Aamodt,M,30.0,176.0,85.0,Norway,NOR,2002 Winter,2002,Winter,Salt Lake City,Alpin

Answer 1

• In order to get the desired plot, the groupby dataframe, must be pivoted into the correct shape.

import pandas as pd

# read the data
df = pd.read_csv('data/athlete_events.csv')

# groupby Team and Medal and get the counts
dfg = df.groupby(['Team', 'Medal']).Medal.count().reset_index(name='counts')

# pivot the dfg, which will enable the plot you're trying to generate
dfp = dfg.pivot(index='Team', columns='Medal', values='counts')

# add a total column, which will allow dfp to be sorted
dfp['total'] = dfp.sum(axis=1)

# sort dfp
dfp = dfp.sort_values('total', ascending=False)

# plot the top 5 rows without the total column
ax = dfp.iloc[:5, :3].plot.bar(stacked=True, figsize=(9, 6), ylabel='Medal Count')
ax.legend(bbox_to_anchor=(1.2, 0.5), loc='center right')

• While stacked bars are nice, because they don't require as much space, they make it more difficult to compare the visualized data.
• From a data presentation perspective, stacked=False is better.