I have table:

It is necessary to check if there is 1 in the column "days_since_install" in grouping by "user_id" and fill in True in the column "retention_1d" otherwise False.

The resulting table should look like this:

CodePudding user response：

Let us do any

df.groupby('user_id')['days_since_install'].any().reset_index()

CodePudding user response：

One option using groupby.any:

out = (df['days_since_install'].eq(1).groupby(df['user_id']).any()
       .reset_index(name='retention_1d')
      )

Output:

   user_id  retention_1d
0        1          True