Question

假设我有一个df-

Player       Challenge      Description
James          ABC              Desc1
Bob            ABC              Desc1
Bob            XYZ              Desc X
Bob            ABX101           Desc4
Alex           XYZ              Desc X           
Mark           ABC123           Desc 123 
Jessica        ABC123           Desc 123
Lynn           XYZ              Desc X
Bob            ABX101           Desc4
Alex           ABX101           Desc 4
Mark           ABC              Desc 1
Lynn           ABC              Desc 1
Mark           POQ              Desc 3
Mark           XYZ              Desc X
Mark           ABC              Desc 1

我可以按玩家分组并使用groupby-

挑战

df.groupby(by=['Player', 'Challenge'])

但是如何获得每个玩家的挑战计数（可能在下一列），然后平均每个玩家的挑战呢？

Answer 1

使用：

count_challenge=df.groupby('Player').Challenge.count()
print(count_challenge)

Player
Alex       2
Bob        4
James      1
Jessica    1
Lynn       2
Mark       5
Name: Challenge, dtype: int64

如果您不希望计算重复次数：

count_challenge=df.drop_duplicates(['Challenge','Player']).groupby('Player').Challenge.count()
print(count_challenge)
Player
Alex       2
Bob        3
James      1
Jessica    1
Lynn       2
Mark       4
Name: Challenge, dtype: int64

然后您可以计算平均值：

count_challenge.mean()

如果您想为每个玩家挑战每种类型的挑战

count_differents_challenge=df.groupby('Player').Challenge.value_counts()
print(count_differents_challenge)

Player   Challenge
Alex     ABX101       1
         XYZ          1
Bob      ABX101       2
         ABC          1
         XYZ          1
James    ABC          1
Jessica  ABC123       1
Lynn     ABC          1
         XYZ          1
Mark     ABC          2
         ABC123       1
         POQ          1
         XYZ          1
Name: Challenge, dtype: int64

Answer 2

您可以尝试使用pivot：

df.pivot(index='foo', columns='bar')

熊猫Groupby以获得每个组的平均值

2 个答案: