import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

The distribution of weights of medalists in gymnastics and in rowing in the 2016 Olympic games for a comparison between them

mens_rowing = pd.read_csv('../data/mens-rowing.csv')
mens_gymnastics = pd.read_csv('../data/mens_gymnastics.csv')

mens_rowing.head()

	Unnamed: 0	ID	Name	Sex	Age	Height	Weight	Team	NOC	Games	Year	Season	City	Sport	Event	Medal
0	158	62	Giovanni Abagnale	M	21.0	198.0	90.0	Italy	ITA	2016 Summer	2016	Summer	Rio de Janeiro	Rowing	Rowing Men's Coxless Pairs	Bronze
1	11648	6346	Jrmie Azou	M	27.0	178.0	71.0	France	FRA	2016 Summer	2016	Summer	Rio de Janeiro	Rowing	Rowing Men's Lightweight Double Sculls	Gold
2	14871	8025	Thomas Gabriel Jrmie Baroukh	M	28.0	183.0	70.0	France	FRA	2016 Summer	2016	Summer	Rio de Janeiro	Rowing	Rowing Men's Lightweight Coxless Fours	Bronze
3	15215	8214	Jacob Jepsen Barse	M	27.0	188.0	73.0	Denmark	DEN	2016 Summer	2016	Summer	Rio de Janeiro	Rowing	Rowing Men's Lightweight Coxless Fours	Silver
4	18441	9764	Alexander Belonogoff	M	26.0	187.0	90.0	Australia	AUS	2016 Summer	2016	Summer	Rio de Janeiro	Rowing	Rowing Men's Quadruple Sculls	Silver

mens_gymnastics.head()

	Unnamed: 0	ID	Name	Sex	Age	Height	Weight	Team	NOC	Games	Year	Season	City	Sport	Event	Medal
0	794	455	Denis Mikhaylovich Ablyazin	M	24.0	161.0	62.0	Russia	RUS	2016 Summer	2016	Summer	Rio de Janeiro	Gymnastics	Gymnastics Men's Team All-Around	Silver
1	796	455	Denis Mikhaylovich Ablyazin	M	24.0	161.0	62.0	Russia	RUS	2016 Summer	2016	Summer	Rio de Janeiro	Gymnastics	Gymnastics Men's Horse Vault	Silver
2	797	455	Denis Mikhaylovich Ablyazin	M	24.0	161.0	62.0	Russia	RUS	2016 Summer	2016	Summer	Rio de Janeiro	Gymnastics	Gymnastics Men's Rings	Bronze
3	18577	9829	David Sagitovich Belyavsky	M	24.0	165.0	55.0	Russia	RUS	2016 Summer	2016	Summer	Rio de Janeiro	Gymnastics	Gymnastics Men's Team All-Around	Silver
4	18579	9829	David Sagitovich Belyavsky	M	24.0	165.0	55.0	Russia	RUS	2016 Summer	2016	Summer	Rio de Janeiro	Gymnastics	Gymnastics Men's Parallel Bars	Bronze

fig, ax = plt.subplots()
ax.hist(mens_rowing.Weight, histtype='step', bins=5, label='Rowing')
ax.hist(mens_gymnastics.Weight, histtype='step', bins=5, label='Gymnastics')
ax.set_xlabel('Weight (kg)')
ax.set_ylabel('# of observations')
ax.legend()
plt.show()

Selecting groups from the Summer 2016 Olympic Games medalist dataset to compare the height of medalist athletes in two different sports.

Adding error bars

fig, ax = plt.subplots()
ax.bar('Rowing', mens_rowing.Height.mean(), yerr=mens_rowing.Height.std())
ax.bar('Gymnastics', mens_gymnastics.Height.mean(), yerr=mens_gymnastics.Height.std())
ax.set_ylabel("Height (cm)")

plt.show()

Boxplot

fig, ax = plt.subplots(figsize=(10,6))
ax.boxplot([mens_rowing.Height, mens_gymnastics.Height])
ax.set_xticklabels(['Rowing', 'Gymnastics'])
ax.set_ylabel('Height (cm)')
plt.show()

we can see how many individuals are outliers within their group.

summer_2016_medals = pd.read_csv('../data/summer_2016_medals.csv')
summer_2016_medals.head()

	Unnamed: 0	Name	Sex	Age	Height	Weight	Team	NOC	Games	Year	Season	City	Sport	Event	Medal
0	158	Giovanni Abagnale	M	21.0	198.0	90.0	Italy	ITA	2016 Summer	2016	Summer	Rio de Janeiro	Rowing	Rowing Men's Coxless Pairs	Bronze
1	161	Patimat Abakarova	F	21.0	165.0	49.0	Azerbaijan	AZE	2016 Summer	2016	Summer	Rio de Janeiro	Taekwondo	Taekwondo Women's Flyweight	Bronze
2	175	Luc Abalo	M	31.0	182.0	86.0	France	FRA	2016 Summer	2016	Summer	Rio de Janeiro	Handball	Handball Men's Handball	Silver
3	450	Saeid Morad Abdevali	M	26.0	170.0	80.0	Iran	IRI	2016 Summer	2016	Summer	Rio de Janeiro	Wrestling	Wrestling Men's Middleweight, Greco-Roman	Bronze
4	794	Denis Mikhaylovich Ablyazin	M	24.0	161.0	62.0	Russia	RUS	2016 Summer	2016	Summer	Rio de Janeiro	Gymnastics	Gymnastics Men's Team All-Around	Silver

sports = summer_2016_medals.Sport.unique()
sports

array(['Rowing', 'Taekwondo', 'Handball', 'Wrestling', 'Gymnastics',
       'Swimming', 'Basketball', 'Boxing', 'Volleyball', 'Athletics'],
      dtype=object)

fig, ax = plt.subplots(figsize=(14,5))

# Loop over the different sports branches
for sport in sports:
  # Extract the rows only for this sport
  sport_df = summer_2016_medals[summer_2016_medals['Sport']==sport]
  # Add a bar for the "Weight" mean with std y error bar
  ax.bar(sport,sport_df['Weight'].mean(), yerr=sport_df['Weight'].std())

ax.set_ylabel("Weight")
ax.set_xticklabels(sports, rotation=90)

# Save the figure to file
fig.savefig('../data/sports_weights.png')
plt.show()