Pandas-将默认日期时间更改为另一个时间

Question

I have a dataframe which has two datetime columns. I am doing difference of those two datetime columns to find number of days between them. The problem is the time in both of them starts from 06:00:00 so when the actual day gets over, the difference remains the same.

Here is the dataframe

machineID   datetime_tel    comp1     datetime_maint    sincelastComp1
30       2021-01-01 23:00:00    1   2020-07-31 06:00:00 154
30       2021-01-02 00:00:00    1   2020-07-31 06:00:00 154
30       2021-01-02 01:00:00    1   2020-07-31 06:00:00 154
30       2021-01-02 02:00:00    1   2020-07-31 06:00:00 154
30       2021-01-02 03:00:00    1   2020-07-31 06:00:00 154
30       2021-01-02 04:00:00    1   2020-07-31 06:00:00 154
30       2021-01-02 05:00:00    1   2020-07-31 06:00:00 154
30       2021-01-02 06:00:00    1   2020-07-31 06:00:00 155
30       2021-01-02 07:00:00    1   2020-07-31 06:00:00 155

Here you can see when we have date as 2021-01-02 and time as 00:00:00 , there is no increment in sincelastComp1 (ideally it should have been incremented as date as increased by 1). It is only increasing when time is 06:00:00 .

I want the increment to happen when the date changes.

Answer 1

if I understand you right, you want to calculate the difference between dates and not between timestamps:

df['sincelastComp1'] = (df['datetime_tel'].apply(pd.Timestamp).dt.date -
                        df['datetime_maint'].apply(pd.Timestamp).dt.date).dt.days

output:

    machineID         datetime_tel  comp1       datetime_maint  sincelastComp1
0         30  2021-01-01 23:00:00      1  2020-07-31 06:00:00             154
1         30  2021-01-02 00:00:00      1  2020-07-31 06:00:00             155
2         30  2021-01-02 01:00:00      1  2020-07-31 06:00:00             155
3         30  2021-01-02 02:00:00      1  2020-07-31 06:00:00             155
4         30  2021-01-02 03:00:00      1  2020-07-31 06:00:00             155
5         30  2021-01-02 04:00:00      1  2020-07-31 06:00:00             155
6         30  2021-01-02 05:00:00      1  2020-07-31 06:00:00             155
7         30  2021-01-02 06:00:00      1  2020-07-31 06:00:00             155
8         30  2021-01-02 07:00:00      1  2020-07-31 06:00:00             155