Count the number of occurrences of an event in times series

Asked Mar 21 '22 at 22:10

Active Mar 22 '22 at 02:44

Viewed 23 times

I have this kind of dataframe :

shopping_center_id  device_local_date              day_of_week
19365   2                   01/09/2019 00:19                       7
27055   4                   01/09/2019 00:26                       7
27014   4                   01/09/2019 00:26                       7
26906   4                   01/09/2019 00:26                       7
28422   4                   01/09/2019 00:26                       7

I would like to count the number of times a shopping center id has been visited at a given time ? I tried many combinations with groupby and count and didn't get any the wanted result Thanks in advance

data_new['Count']=data_new.groupby('device_local_date')['shopping_center_id'].count()

this gave me a column of Count filled with "Nan"

edited Mar 22 '22 at 02:44

furas

134,197
12
106
148

asked Mar 21 '22 at 22:10

Lagos

what is expected result? – furas Mar 22 '22 at 02:43
maybe first display result without assigning to new column. – furas Mar 22 '22 at 02:44
you don't need \ in code when you put in question. – furas Mar 22 '22 at 02:45
code gives me two values and it simply doesn't how to convert it to 6 rows which you have in original dataframe. – furas Mar 22 '22 at 02:52
you have to use `.transform('count')` instread of `.count()` like in answer https://stackoverflow.com/questions/45346986/pandas-group-by-count-and-add-count-to-original-dataframe – furas Mar 22 '22 at 02:58

Count the number of occurrences of an event in times series

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