列到日期时间 pandas 与滚动时间

Question

I have a df that has a timestamp column that looks like:

0:40:40
0:40:45 
...

23:59:55
0:00:00
0:00:05 
...

And repeats like this for many days. How can this be converted into a datetime object with a different consecutive day assigned to each new day? Currently, the to_datetime assigns them all to the same day.

Answer 1

after making the DATE column with to_datetime:

df['New_date'] = df.apply(lambda row : row['DATE']+datetime.timedelta(days=row.name), axis=1)

NB: row.name to add the index number as a day

Answer 2

df.timestamp = pd.to_datetime(df.timestamp) days = 0 for i in range(2, size + 1): if df.at[i - 1, 'timestamp'].hour > df.at[i, 'timestamp'].hour: days += 1 df.at[i, 'timestamp'] += datetime.timedelta(days=days)