带有agg的pandas groupby无法处理多列 [英] pandas groupby with agg not working on multiple columns

问题描述

我正在尝试将多个列合并到一个基于 Pandas 分组的列表中.下面是我正在使用的代码

I'm trying to merge multiple columns, each into a list based on a group by in pandas. Below is the code I'm using

grouped_df = df.groupby(['d_id', 'time']).agg({'d_name': lambda x: tuple(x)},  
{'ver': lambda x: tuple(x)},
{'f_name': lambda x: tuple(x)})

这只会给我一个列表中的第一列 (d_name)，d_id 和时间在 grouped_df 中.其他两列不显示为列表.我之前尝试使用 list 但发现 list 有 agg 函数的问题，所以我求助于元组.如果我在这里做错了什么，请告诉我.

This only gives me the first column (d_name) in a list with d_id and time in grouped_df. The other two columns do not show as lists. I tried using list earlier but found out that list has an issue with agg function so I resorted to tuple. Let me know if I'm doing something wrong here.

感谢 RafaelC 对此的回答.现在我试图将这些列表列作为 grouped_df 添加到原始数据框中.当我看到 grouped_df 中的列时，它们显示为

Thanks to RafaelC for the answer to this. Now I am trying to add these list columns to the original dataframe as grouped_df. When I see the columns in grouped_df they come out as

Index([u'ver', u'f_name', u'd_name'], dtype='object')

但是当我做头像时，我得到了

But when I do a head, I get

 ver  \
d_id  time
1    2018-06-01   (ver1, ver2, ver3.....
2    2018-06-01   (ver1, ver2, ver3.....
3    2018-06-01   (ver1, ver2, ver3.....


f_name  \
d_id   time
1  2018-06-01   (f_name1, f_name2, f_name2.....
2  2018-06-01   (f_name1, f_name2, f_name2.....
3  2018-06-01   (f_name1, f_name2, f_name2.....

d_name
d_id   time
1 2018-06-01   (d_name1, dname2, d_name3...
2 2018-06-01   (d_name1, dname2, d_name3...
3 2018-06-01   (d_name1, dname2, d_name3...

我如何获得以下信息d_id 时间 ver d_name f_name其中 ver、d_name 和 f_name 是列表.

How do I get the following d_id time ver d_name f_name where ver, d_name and f_name are lists.

希望这很清楚.

推荐答案

使用单个参数而不是三个

Use a single argument instead of three

{'d_name': lambda x: tuple(x), 'ver': lambda x: tuple(x), 'f_name': lambda x: tuple(x)}

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