How to clean Pandas data frame column which contains mix of both datetime and date?

Question

I have a column in a Pandas data frame that has a date column but has datetime and date mixed in together as follows:

2020-05-20 00:00:00
2020-05-21 00:00:00
2020-05-22 
2020-05-23

Is there any way to convert everything to a date format as follows:

Does this answer your question? [Working with mixed date time formats in pandas](https://stackoverflow.com/questions/60390709/working-with-mixed-date-time-formats-in-pandas) — Bertil Johannes Ipsen, Jun 08 '20 at 10:37
@BertilJohannesIpsen No, the date format is the same across the entire column. Just that a few have time (00:00:00) attached to them .The answer by **jezrael** seems to be working. Will validate and update. — Biswankar Das, Jun 08 '20 at 10:45
@BertilJohannesIpsen that's not a relevant dupe target, it;s about multiple *datetime* formats (`YYYY-MM-DD` vs `DD.MM.YYYY`). But this one is about a single date format, except that it may/may not contain the time. — smci, Jun 08 '20 at 10:45

score 2 · Accepted Answer · answered Jun 08 '20 at 10:38

2

Convert values to strings and then to datetimes, last to dates:

pd.to_datetime(df['date'].astype(str)).dt.date

answered Jun 08 '20 at 10:38

jezrael

1 Answers1