CODEWITHSUNDEEP
pythondatetimepandasdataframe
Niladri Gomes
Niladri Gomes

Reputation: 211

ValueError: day is out of range for month

I want to convert a string from a dataframe to datetime.

dfx = df.ix[:,'a']
dfx = pd.to_datetime(dfx)

But it gives the following error:

ValueError: day is out of range for month

Can anyone help?

Upvotes: 20

Views: 87462

Answers (2)

Hasnain Sikander
Hasnain Sikander

Reputation: 511

Well in my case

year = 2023
month = 2
date = datetime.date(year, month, 30)

got me this error because February month has 29 or 28 days in it. Maybe that point helps someone

Upvotes: 4

jezrael
jezrael

Reputation: 863721

Maybe help add parameter dayfirst=True to to_datetime, if format of datetime is 30-01-2016:

dfx = df.ix[:,'a']
dfx = pd.to_datetime(dfx, dayfirst=True)

More universal is use parameter format with errors='coerce' for replacing values with other format to NaN:

dfx = '30-01-2016'

dfx = pd.to_datetime(dfx, format='%d-%m-%Y', errors='coerce')
print (dfx)
2016-01-30 00:00:00

Sample:

dfx = pd.Series(['30-01-2016', '15-09-2015', '40-09-2016'])
print (dfx)
0    30-01-2016
1    15-09-2015
2    40-09-2016
dtype: object

dfx = pd.to_datetime(dfx, format='%d-%m-%Y', errors='coerce')
print (dfx)
0   2016-01-30
1   2015-09-15
2          NaT
dtype: datetime64[ns]

If format is standard (e.g. 01-30-2016 or 01-30-2016), add only errors='coerce':

dfx = pd.Series(['01-30-2016', '09-15-2015', '09-40-2016'])
print (dfx)
0    01-30-2016
1    09-15-2015
2    09-40-2016
dtype: object

dfx = pd.to_datetime(dfx, errors='coerce')
print (dfx)
0   2016-01-30
1   2015-09-15
2          NaT
dtype: datetime64[ns]

Upvotes: 28

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