I have a csv data with daily frequency as shown below:
d = pd.read_csv("DGS5.csv")
d['DATE'] = pd.to_datetime(d.DATE)
d.set_index('DATE', inplace=True)
print(d)
DGS5
DATE
1962-01-02 3.88
1962-01-03 3.87
1962-01-04 3.86
1962-01-05 3.89
1962-01-08 3.91
... ...
2022-11-17 3.93
2022-11-18 3.99
2022-11-21 3.97
2022-11-22 3.93
2022-11-23 3.88
When I try to resample this to monthly frequency, I get the following output; where DATE column is DATE column is converted to monthly frequency by missing DGS5 values.
d.resample('1m').mean()
DATE
2022-01-31
2022-02-28
2022-03-31
2022-04-30
2022-05-31
2022-06-30
2022-07-31
2022-08-31
Below the information about the data.
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 15887 entries, 1962-01-02 to 2022-11-23
Data columns (total 1 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 DGS5 15887 non-null object
dtypes: object(1)
Appreciate support from the community to show where I am going wrong here.
