在pandas数据框中获取一列字符串数据，并将其拆分为单独的列 [英] Take column of string data in pandas dataframe and split into separate columns

问题描述

我从CSV读取的数据中有一个pandas数据框.一列是组的名称，而另一列包含一个字符串(看起来像一个列表)，如下所示:

I have a pandas dataframe from data I read from a CSV. One column is for the name of a group, while the other column contains a string (that looks like a list), like the following:

Group      |  Followers
------------------------------------------
biebers    |  u'user1', u'user2', u'user3'
catladies  |  u'user4', u'user5'
bkworms    |  u'user6', u'user7'

我想尝试在跟随者"列中拆分字符串，并创建一个单独的数据框，其中每一行用于用户，以及一列显示其所在的组.因此，在此示例中我想得到以下内容:

I'd like to try to split up the strings in the "Followers" column and make a separate dataframe where each row is for a user, as well as a column showing which group they're in. So for this example I'd like to get the following:

User       |     Group
--------------------------------
user1      |     biebers
user2      |     biebers
user3      |     biebers
user4      |     catladies
user5      |     catladies
user6      |     bkworms
user7      |     bkworms

有人对解决此问题的最佳方法提出建议吗?这是它的屏幕截图:

Anyone have suggestions for the best way to approach this? Here's a screenshot of what it looks like:

推荐答案

df.Followers = df.Followers.str.replace(r"u'([^']*)'", r'\1')

df.set_index('Group').Followers.str.split(r',\s*', expand=True) \
  .stack().rename('User').reset_index('Group').set_index('User')

将User保留为列.

df.Followers = df.Followers.str.replace(r"u'([^']*)'", r'\1')

df.set_index('Group').Followers.str.split(r',\s*', expand=True) \
  .stack().rename('User').reset_index('Group') \
  .reset_index(drop=True)[['User', 'Group']]

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