CODEWITHSUNDEEP
pythonpandasdatetime
RoshanShah22
RoshanShah22

Reputation: 420

Convert string Month-Year to datetime in pandas dataframe

I have a column in my dataframe called 'date' as below:

Date
Jan-1981
Feb-1981
Mar-1981
.
.
Sep-2005
.
Dec-2008

Is there a way to convert this into datetime format so the default format is DD/MM/YYYY where DD is always 01. eg.

Expected 'Date'

01-01-1981
01-02-1982
.
.
.
.
.
01-12-2008

Upvotes: 5

Views: 19882

Answers (2)

user12932966
user12932966

Reputation: 320

If for some reason pd.to_datetime doesnt parse dates directly (happened to me once where the date format of data was YYYYMMDD with no separators at all) you can get away by using datetime.strptime first, in your case :

import datetime as dt


df['Date'] = pd.to_datetime(df['Date'].apply(lambda x: dt.strptime(x, '%b-%Y')))

Note : the reason you still need to use pd.to_datetime is because the datetime's and pandas' date-data type are different :

datetime.strptime returns a datetime object cf the documentation

pandas.to_datetime returns a Timestamp or datetime64 cf pandas' documentation

Upvotes: 3

jezrael
jezrael

Reputation: 862406

If need datetimes use to_datetime:

df['Date'] = pd.to_datetime(df['Date'])

print (df)
0 1981-01-01
1 1981-02-01
2 1981-03-01
3 2005-09-01
4 2008-12-01

If need custom format use Series.dt.strftime, but datetimes format is lost and get strings (objects):

df['Date'] = pd.to_datetime(df['Date']).dt.strftime('%d-%m-%Y')

print (df)
         Date
0  01-01-1981
1  01-02-1981
2  01-03-1981
3  01-09-2005
4  01-12-2008

Upvotes: 10

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