Convert object type into datetime in Time series Forecasting

Question

I am working on Time Series so I want to convert object type to datetime. I have a data frame like this:

   trxyear  trxmonth
0   2014    JUL-13
1   2014    JUL-13
2   2014    JUL-13
3   2014    JUL-13
4   2014    JUL-13
... ... ...
46394   2023    SEP-22
46395   2023    SEP-22
46396   2023    SEP-22
46397   2023    SEP-22
46398   2023    SEP-22

I want to convert trxmonth to datetime so I can apply time series. but when I convert using this code

CODE:

from dateutil import parser
print(parser.parse("JUL-13"))

OUTPUT:
2022-07-13 00:00:00

but it can convert July 2013 to 13 July 2022.

CODE:

print(parser.parse("01-JUL-13") )

OUTPUT:
2013-07-01 00:00:00

when I use this code it can converts correctly but my data is not in this format.
Simply I want to convert JUL-13 –> 01-07-2013

Asked By: Mehmaam

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Source

Answer 1

Use to_datetime with format parameter:

df['trxmonth'] = pd.to_datetime(df['trxmonth'], format='%b-%y')

print (df)
       trxyear   trxmonth
0         2014 2013-07-01
1         2014 2013-07-01
2         2014 2013-07-01
3         2014 2013-07-01
4         2014 2013-07-01
46394     2023 2022-09-01
46395     2023 2022-09-01
46396     2023 2022-09-01
46397     2023 2022-09-01
46398     2023 2022-09-01

Answered By: jezrael

Convert object type into datetime in Time series Forecasting

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