i want to combine months from years into sequence, for example, i have dataframe like this:
stuff_id date
1 2015-02-03
2 2015-03-03
3 2015-05-19
4 2015-10-13
5 2016-01-07
6 2016-03-20
i want to sequence the months of the date. the desired output is:
stuff_id date month
1 2015-02-03 1
2 2015-03-03 2
3 2015-05-19 4
4 2015-10-13 9
5 2016-01-07 12
6 2016-03-20 14
which means feb'15 is the first month in the date list and jan'2016 is the 12th month after feb'2015
CodePudding user response:
If your date
column is a datetime (if it's not, cast it to one), you can use the .dt.month
and .dt.year
properties for this!
https://pandas.pydata.org/docs/reference/api/pandas.Series.dt.month.html
recast
(text copy from Answer to Pasting data into a pandas dataframe)
>>> df = pd.read_table(io.StringIO(s), delim_whitespace=True) # text from SO
>>> df["date"] = pd.to_datetime(df["date"])
>>> df
stuff_id date
0 1 2015-02-03
1 2 2015-03-03
2 3 2015-05-19
3 4 2015-10-13
4 5 2016-01-07
5 6 2016-03-20
>>> df.dtypes
stuff_id int64
date datetime64[ns]
dtype: object
extract years and months to decimal months and reduce to relative
>>> months = df["date"].dt.year * 12 df["date"].dt.month # series
>>> df["months"] = months - min(months) 1
>>> df
stuff_id date months
0 1 2015-02-03 1
1 2 2015-03-03 2
2 3 2015-05-19 4
3 4 2015-10-13 9
4 5 2016-01-07 12
5 6 2016-03-20 14