Pandas convert column with year integer to datetime

Question

I am having some problem converting column (datatype:int64) into datetime working with Pandas.

Original data:

Year
2015
2014
...
2010

Desired outcome:

Year
2015-01-01
2014-01-01
...
2010-01-01

My current result:

Year
1970-01-01 00:00:00.000002015
1970-01-01 00:00:00.000002014
...
1970-01-01 00:00:00.000002010

I have tried:

data.Year = pd.to_datetime(data.Year)
data.Year = pd.to_datetime(data.Year, format='%Y-%m-%d')

Asked By: shawnngtq

||

Source

Answer 1

Use format='%Y'

In [225]: pd.to_datetime(df.Year, format='%Y')
Out[225]:
0   2015-01-01
1   2014-01-01
2   2010-01-01
Name: Year, dtype: datetime64[ns]

Details

In [226]: df
Out[226]:
   Year
0  2015
1  2014
2  2010

Answered By: Zero

Answer 2

I know this an old question but, there’s a catch when converting int to datetime, when the type of the data is int64 it will result in wrong parsing. I had the same situation when trying to convert a list of Years as int64, it would result into:

pd.to_datetime(df.Year, format='%Y')

Year
1970-01-01 00:00:00.000002015 
1970-01-01 00:00:00.000002014
...
1970-01-01 00:00:00.000002010

To avoid this, you need to convert int64 to int32
df.Year.astype('int32'). Then you can parse it as pd.to_datetime(df.Year, format = '%Y') and you will get the correct output.

Answered By: Alexandre Machado

Answer 3

I faced similar issue, and in my case pd.to_datetime(df.Year, format='%Y'),
this worked but not completely. Instead I had to use .year at the end of dataframe and voilà! that worked fine.

Answered By: Vinay Singh

Pandas convert column with year integer to datetime

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