pandas 崩溃的行数据 [英] pandas collapsing row data

问题描述

大熊猫新手，我在这里学习. 我有一个看起来像这样的数据框:

New to pandas, I m climbing my learning curve here. I have a dataframe that looks like:

Relinquished Degree Count DTD DNP outindefinitely seasonout 
-----------------------------------------------------------
player1        1      1    1    
player1        3      1                1

程度"列中的值在1到4的范围内，它表示伤害程度(DTD，DNP，无限期，反季节). 如何在已放弃"列下合并具有相同玩家名称的两行? 预期输出:

Values in column Degree ranges from 1 to 4 and it represents degree of injury (DTD,DNP,outindefinitely,seasonout). How do I merge the two rows that has same player name under column Relinquished? Expected output:

Relinquished DTD DNP outindefinitely seasonout 
-----------------------------------------------------------
player1        1        1

提前谢谢！

推荐答案

您不能在将缺少的值替换为空字符串第一步，然后汇总sum:

You cannot replace missing values to empty strings in first step and then aggregate sum:

df = df.groupby('Relinquished').sum()

如果要指定总和列:

print (df)
  Relinquished  Degree  Count  DTD  DNP  outindefinitely  seasonout
0      player1       1      1  1.0  NaN              NaN        NaN
1      player1       3      1  NaN  NaN              1.0        NaN

df = df.groupby('Relinquished')['DTD','DNP','outindefinitely','seasonout'].sum()
print (df)
              DTD  DNP  outindefinitely  seasonout
Relinquished                                      
player1       1.0  0.0              1.0        0.0

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