如果条件在另一列中为真，如何按一列分组，将第三列中的值与 pandas 求和

Question

我想不出该怎么做：正如标题所解释的那样，我只想在另一列包含 Closed Won 时按列 acquired_month 对数据框进行分组（在示例中，我制作了一个辅助列，如果满足该条件，则只标记 True尽管我不确定该步骤是否必要）。然后，如果满足这些条件，我想对第三列的值求和，但不知道该怎么做。到目前为止，这是我的代码：

us_lead_scoring.loc[us_lead_scoring['Stage'].str.contains('Closed Won'), 'closed_won_binary'] = True acquired_date = us_lead_scoring.groupby('acquired_month')['closed_won_binary'].sum()

但是如果真假列在 acquired_month groupby 之后为真，那么这只是对真假列求和而不是 sum 列。任何方向表示赞赏。

谢谢

Answer 1

如果需要聚合列 col 将不匹配的值替换为 Series.where 中的 0 值，然后聚合 sum:

us_lead_scoring = pd.DataFrame({'Stage':['Closed Won1','Closed Won2','Closed', 'Won'],
                                'col':[1,3,5,6],
                                'acquired_month':[1,1,1,2]})

out = (us_lead_scoring['col'].where(us_lead_scoring['Stage']
                             .str.contains('Closed Won'), 0)
                             .groupby(us_lead_scoring['acquired_month'])
                             .sum()
                             .reset_index(name='SUM'))
     
print (out)
   acquired_month  SUM
0               1    4
1               2    0

如果条件在另一列中为真，如何按一列分组，将第三列中的值与 pandas 求和

How to group by one column if condition is true in another column summing values in third column with pandas

pandas

pandas-groupby