[英]python dataframe groupby and append new columns
Below is my code so far:到目前为止,以下是我的代码:
business_card_list = [[20180401, 'IT', 'anna'],
[20180401, 'IT', 'ena'],
[20180401, 'IT', 'sunna'],
[20180401, 'ART', 'jejus'],
[20180401, 'ART', 'zico'],
[20180401, 'ART', 'joker']]
business_df = pd.DataFrame(data = business_card_list, columns=['date', 'job_name', 'user_name'])
print(business_df)
I want to change business_df
to such pictures below form through grouping.我想通过分组将
business_df
更改为表格下方的此类图片。 Do you offer in Dataframe?你们提供 Dataframe 吗?
Try using groupby
with apply
, rename
and add_prefix
:尝试将
groupby
与apply
、 rename
和add_prefix
使用:
print(business_df.groupby(['date', 'job_name'])['user_name'].apply(list).apply(pd.Series).rename(columns=lambda x: x+1).add_prefix('user_name_').reset_index())
Output: Output:
date job_name user_name_1 user_name_2 user_name_3
0 20180401 ART jejus zico joker
1 20180401 IT anna ena sunna
Hope this will help!希望这会有所帮助!
business_df.groupby(['date','job_name'])['user_name'].apply(list).apply(pd.Series).reset_index()
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