Resolved: Pandas resample by day and count occurrences to new column

Question:

So I went through a lot of workarounds about resampling and groupby methods in pandas and could not find the solution of my problem.
I have dataset with time and error type. I would like to count a specific type of error that occurred per day but there is more than one type in one day.
Example of my data:

               time  error  
0 2021-10-03 19:18:20   2222     
1 2021-10-03 19:39:36   2222     
2 2021-10-03 19:48:03   3333    
3 2021-10-03 19:48:23   4444     
4 2021-10-03 19:48:36   3333

So I am trying the following:

df = df.groupby(['time','error'], as_index=False).size()

And after that resample the data by day and sum the occurrence number.
Unfortunately without any success.
Desired output is:

               time  error  size
0          2021-10-03   2222   2
1          2021-10-03   3333   2
2          2021-10-03   4444   1

And so on for every error type and day.
Thanks for any help!

Answer:

Let’s try

df['time'] = pd.to_datetime(df['time'])
out = df.groupby([df['time'].dt.date,'error'], as_index=False).size()

print(out)

         time  error  size
0  2021-10-03   2222     2
1  2021-10-03   3333     2
2  2021-10-03   4444     1

If you have better answer, please add a comment about this, thank you!

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