import pandas as pd

football_dict = { "player": ["Lionel Messi", "Cristiano Ronaldo"], "year": [2016, 2016], "goals": [37, 25], } football_stats = pd.DataFrame(football_dict) print(football_stats)

football_list = [ {"player": "Lionel Messi", "year": 2016, "goals": 37}, {"player": "Cristiano Ronaldo", "year": 2016, "goals": 25}, ] football_stats = pd.DataFrame(football_list) print(football_stats)

df = pd.read_csv('/work/datasets/football_mini_stats.csv') print(df)

df = pd.read_csv('/work/datasets/football_mini_stats.csv', index_col='player') print(df)

df = pd.read_csv('/work/datasets/football_stats.csv', index_col='player_id') df

print(df.sample(3))

print(df.shape)

print(df.size)

print(df.info())

df.describe()

df.sort_values('player_name', ascending=False)

print(df.sort_values(['team_name', 'goals'], ascending=[True, False]).head(3))

df['team_name'].unique()

df[df.player_name=='Aaron Connolly']

df[df['player_name']=='Aaron Connolly']

df.query('player_name == "Aaron Connolly"')

# Goles de Cristiano Ronaldo en 2014 cr7 = df[(df.player_name == 'Cristiano Ronaldo') & (df.year == 2014)] cols = ['player_name', 'year', 'goals'] print(cr7[cols])

# Goles de Ronaldo, Messi y Suárez en 2015 players = ['Cristiano Ronaldo', 'Lionel Messi', 'Luis Suárez'] top_players = df[(df.player_name.isin(players)) & (df.year == 2015)] print(top_players[cols])

# Goles de Ronaldo, Messi y Suárez en 2015 df = df.reset_index() df = df.set_index('player_name') players = ['Cristiano Ronaldo', 'Lionel Messi', 'Luis Suárez'] cols = ['year', 'goals'] top_players = df.loc[players, cols] print(top_players.query('year==2015'))

# Máxima cantidad de goles hechas por un jugador en una temporada max_goals = df['goals'].max() cols = ['goals', 'year', 'team_name'] print(df[df.goals == max_goals][cols])

# Porcentaje de disparos al arco que terminan en gol total_shots = df['shots'].sum() total_goals = df['goals'].sum() print(round(total_goals / total_shots * 100, 2))

# Top 10 jugadores que más goles han marcado top_players = df.groupby('player_name')['goals'].sum() print(top_players.sort_values(ascending=False).head(10))

# Top 5 equipos con más tarjetas rojas y amarillas red_cards = df.groupby('team_name')[['red_cards', 'yellow_cards']].sum() print(red_cards.sort_values('red_cards', ascending=False).head())

df['goals_assists'] = df.goals + df.assists best_players = df.groupby('player_name')['goals_assists'].sum() print(best_players.sort_values(ascending=False).head())