带有分隔符的Pandas groupby加入

问题描述：

我尝试使用groupby对具有多个值的行进行分组.

I tried to use groupby to group rows with multiple values.

col val
A  Cat
A  Tiger
B  Ball
B  Bat

import pandas as pd
df = pd.read_csv("Inputfile.txt", sep='\t')
group = df.groupby(['col'])['val'].sum()

我知道了

A CatTiger
B BallBat

我想引入一个定界符，以便我的输出看起来像

I want to introduce a delimiter, so that my output looks like

A Cat-Tiger
B Ball-Bat

我尝试过

group = df.groupby(['col'])['val'].sum().apply(lambda x: '-'.join(x))

这产生了

A C-a-t-T-i-g-e-r
B B-a-l-l-B-a-t

这是什么问题?

谢谢

答

或者您也可以这样:

In [48]: df.groupby('col')['val'].agg('-'.join)
Out[48]:
col
A    Cat-Tiger
B     Ball-Bat
Name: val, dtype: object

更新:从评论中回答问题:

UPDATE: answering question from the comment:

In [2]: df
Out[2]:
  col    val
0   A    Cat
1   A  Tiger
2   A  Panda
3   B   Ball
4   B    Bat
5   B  Mouse
6   B    Egg

In [3]: df.groupby('col')['val'].agg('-'.join)
Out[3]:
col
A       Cat-Tiger-Panda
B    Ball-Bat-Mouse-Egg
Name: val, dtype: object

最后一次将索引或MultiIndex转换为列:

Last for convert index or MultiIndex to columns:

df1 = df.groupby('col')['val'].agg('-'.join).reset_index(name='new')

带有分隔符的Pandas groupby加入

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