使用Pandas groupby连接来自多行的字符串 [英] Concatenate strings from several rows using Pandas groupby

问题描述

我想基于Pandas中的groupedby合并数据框中的几个字符串.

I want to merge several strings in a dataframe based on a groupedby in Pandas.

到目前为止，这是我的代码:

This is my code so far:

import pandas as pd
from io import StringIO

data = StringIO("""
"name1","hej","2014-11-01"
"name1","du","2014-11-02"
"name1","aj","2014-12-01"
"name1","oj","2014-12-02"
"name2","fin","2014-11-01"
"name2","katt","2014-11-02"
"name2","mycket","2014-12-01"
"name2","lite","2014-12-01"
""")

# load string as stream into dataframe
df = pd.read_csv(data,header=0, names=["name","text","date"],parse_dates=[2])

# add column with month
df["month"] = df["date"].apply(lambda x: x.month)

我希望最终结果看起来像这样:

I want the end result to look like this:

我不知道如何使用groupby并在文本"列中应用某种形式的字符串连接.任何帮助表示赞赏！

I don't get how I can use groupby and apply some sort of concatenation of the strings in the column "text". Any help appreciated!

推荐答案

您可以对'name'和'month'列进行分组，然后调用transform，这将返回与原始df对齐的数据并在其中输入一个lambda join文本条目:

You can groupby the 'name' and 'month' columns, then call transform which will return data aligned to the original df and apply a lambda where we join the text entries:

In [119]:

df['text'] = df[['name','text','month']].groupby(['name','month'])['text'].transform(lambda x: ','.join(x))
df[['name','text','month']].drop_duplicates()
Out[119]:
    name         text  month
0  name1       hej,du     11
2  name1        aj,oj     12
4  name2     fin,katt     11
6  name2  mycket,lite     12

我通过在此处传递感兴趣的列的列表df[['name','text','month']]来替换原始df，然后调用drop_duplicates

I sub the original df by passing a list of the columns of interest df[['name','text','month']] here and then call drop_duplicates

编辑实际上，我可以先呼叫apply然后呼叫reset_index:

EDIT actually I can just call apply and then reset_index:

In [124]:

df.groupby(['name','month'])['text'].apply(lambda x: ','.join(x)).reset_index()

Out[124]:
    name  month         text
0  name1     11       hej,du
1  name1     12        aj,oj
2  name2     11     fin,katt
3  name2     12  mycket,lite

更新

lambda在这里是不必要的:

In[38]:
df.groupby(['name','month'])['text'].apply(','.join).reset_index()

Out[38]: 
    name  month         text
0  name1     11           du
1  name1     12        aj,oj
2  name2     11     fin,katt
3  name2     12  mycket,lite

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