Give default datetime object value to pandas.to_datetime()

Question

I have some dates in string with different formats that I convert to datetime objects using to_datetime(). However, the list of strings also has some garbage values that I want to convert to default date.

import pandas as pd
import datetime as dt

print(df)

       dates
0   2018-02-12
1   2018-03-19
2   12-24-2018
3   garbage

I use errors='coerece' to avert to throw exception. It produces NaT, that I want to convert to a default date 2018-12-31, in my case.

df['dates'] = pd.to_datetime(df['dates'], errors='coerce')

Below result.

      dates
0   2018-02-12
1   2018-03-19
2   2018-12-24
3   NaT

Approach:

I am checking if the given value is a valid datetime or not. If not, put the default datetime object. But for some reason, it produces all default values.

df['dates'].apply(lambda x: dt.datetime(2018,12,31) if x is not dt.datetime else x)

Current Output

     dates
0   2018-12-31
1   2018-12-31
2   2018-12-31
3   2018-12-31

Expected Output:

     dates
0   2018-02-12
1   2018-03-19
2   2018-12-24
3   2018-12-31

Is there a way to give a default date to to_datetime() function so that, it won’t produce NaT? If not, how do I put default dates afterwards?

Asked By: user4110225

||

Source

Answer 1

You just need adding fillna at the end after pd.to_datetime call

pd.to_datetime(df['dates'], errors='coerce').fillna(pd.to_datetime('2018-12-31'))
Out[217]: 
0   2018-02-12
1   2018-03-19
2   2018-12-24
3   2018-12-31
Name: dates, dtype: datetime64[ns]

Answered By: BENY

Give default datetime object value to pandas.to_datetime()

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