python - 用于计算 2 列值的 Pandas groupby/pivot 表

Question

我有一个像这样的 pandas DataFrame

week  player_a  player_b
 1      True      True
 1      True     False
 1     False     False
 2     False      True
 2     False     False
 2      True     False

我想按周计算每个玩家的 True 和 False 的数量，但我似乎无法将其变成方便的 pandas groupby 或数据透视表操作。期望的结果如下所示:

week            True  False
      player
 1   player_a     2     1
     player_b     1     2
 2   player_a     1     2
     player_b     1     2

Answer 1

使用DataFrame.melt先数再数crosstab :

df1 = df.melt('week', var_name='player')

df = pd.crosstab([df1['week'], df1['player']], df1['value'])

或者使用DataFrame.pivot_table :

df = df1.pivot_table(index=['week', 'player'], columns='value', fill_value=0, aggfunc='size')

或按 GroupBy.size 汇总计数并通过 Series.unstack reshape :

df = df1.groupby(['week', 'player', 'value']).size().unstack(fill_value=0)

---

print (df)
value          False  True 
week player                
1    player_a      1      2
     player_b      2      1
2    player_a      2      1
     player_b      2      1

解决方案 DataFrame.stack , SeriesGroupBy.value_counts和 unstack:

df = df.set_index('week').stack().groupby(level=[0,1]).value_counts().unstack(fill_value=0)
print (df)
               False  True 
week                       
1    player_a      1      2
     player_b      2      1
2    player_a      2      1
     player_b      2      1