pandas :基于 pandas 列中匹配子字符串的分组 [英] Pandas: Groupby based on matching substring in pandas column

问题描述

我有一个包含以下元素的列表:

I have a list that has elements like:

emails= ['xyz.com', 'abc.com','def.com']

现在，我有一个如下所示的数据框:

Now, I have a dataframe that looks like:

df:

UserID    Email_Address
U001      [e-mail]
U002      [e-mail]
U003      [e-mail]
U004      [e-mail]
U004      [e-mail]
U006      [e-mail]
U007      [e-mail]

我想根据子字符串对 groupby 进行计数，其中子字符串是列表中的元素.

I want to perform count on groupby based on substring where the substring is the elements from the list.

因此，输出应如下所示:

Hence, the output should look like:

abc.com     2
def.com     3
xyz.com     2

我当前的代码:

for domain in list1:
    count = df.groupby( [df.Email_Address.str.find(domain)]).sum()

推荐答案

使用 Series.str.extract 用于按列表获取值并按 GroupBy.size:

pat = '|'.join(emails)
s = df['Email_Address'].str.extract('('+ pat + ')', expand=False)
df1 = df.groupby(s).size().reset_index(name='Count')
print (df1)
  Email_Address  Count
0       abc.com      2
1       def.com      3
2       xyz.com      2

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