CODEWITHSUNDEEP
pythonpandasdatetime
mert
mert

Reputation: 15

Pandas: Drop rows if records conflict in datetime intervals

I have a pandas dataframe in which I have three datetime columns. One of them is a log date and the other two (let say start and end) are used to define a datetime interval. What I want to do is to drop records if they are conflicting in datetime interval. I would like to keep the record with newest log time and drop the rest.

For example:

name start end log time
r1 2022/08/05 09:00:00 2022/08/07 08:00:00 2022/08/06 08:00:00
r2 2022/08/06 09:00:00 2022/08/08 08:00:00 2022/08/05 08:00:00
r3 2022/08/07 09:00:00 2022/08/09 08:00:00 2022/08/04 08:00:00

In this table r1 and r2 are conflicting in intervals, hence I would like to keep r1 as it has the newest log time between the two.

So I would like to get the following result.

name start end log time
r1 2022/08/05 09:00:00 2022/08/07 08:00:00 2022/08/06 08:00:00
r3 2022/08/07 09:00:00 2022/08/09 08:00:00 2022/08/04 08:00:00

Upvotes: 0

Views: 103

Answers (1)

Manjari
Manjari

Reputation: 332

Below line will get the index which has starttime is grater than logtime and drop the identified indexes.

df.drop(df[ (df['start'] > df['logtime'])].index, inplace=True)

Upvotes: 1

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