Pandas: Count login days of users

Asked Mar 10 '20 at 08:05

Active Mar 10 '20 at 08:05

Viewed 29 times

I have a data frame contains one-month data.

   login_date    user_id
0  2019-12-22   432
1  2019-12-22   432
2  2019-12-22   339
3  2019-12-23   438
4  2019-12-23   432
5  2019-12-23   431
6  2019-12-25   339
7  2019-12-25   438
8  2019-12-25   432
9  2019-12-25   432
10  2019-12-25   339
11  2019-12-26   438
12  2019-12-29   339
13  2019-12-31   432
14  2019-12-31   432
15  2019-12-31   453

I am trying to calculate count the user's login days of the month.

Expected output:

   user_id login_days
0  432     4
1  339     3
2  438     3
3  431     1
4  453     1

I tried using the below code.

df.groupby(df['user_id']).count()

But I am not getting what I want. If someone can help, it would be grateful.

asked Mar 10 '20 at 08:05

xcen

1

Use `df = df.groupby(df['user_id'], sort=False)['login_date'].nunique().reset_index()` – jezrael Mar 10 '20 at 08:08
@jezrael Thank you for your answer comment and sorry for not noticing the similar question and answer. – xcen Mar 10 '20 at 08:15
1

No problem, its happens ;) – jezrael Mar 10 '20 at 08:15

Pandas: Count login days of users

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