Pandas : 'to_datetime' function not consistent with dates-CodePudding

When I read a date say '01/12/2020', which is in the format dd/mm/yyyy, with pd.to_datetime(), it detects the month as 01.

pd.to_datetime('01/12/2020').month
>> 1

But this behavior is not consistent.

When we create a dataframe with a column containing dates in this format, and convert using the same to_datetime function, it then detects 12 as the month.

tt.dt.month[0]
>> 12

What could be the reason ?

CodePudding user response：

pandas automagically tries to detect the date format, which can be very nice, or annoying in your case.

Be explicit, use the dayfirst parameter:

pd.to_datetime('01/12/2020', dayfirst=False).month
# 1

pd.to_datetime('01/12/2020', dayfirst=True).month
# 12

Example of ambiguous use:

tt = pd.to_datetime(pd.Series(['30/05/2020', '01/12/2020']))
tt.dt.month

UserWarning: Parsing dates in DD/MM/YYYY format when dayfirst=False (the default) was specified. This may lead to inconsistently parsed dates! Specify a format to ensure consistent parsing.
  tt = pd.to_datetime(pd.Series(['30/05/2020', '01/12/2020']))

0    5
1    1
dtype: int64