asfreq in pandas returns an empty dataframe

I’m tring to use infer_freq and asfreq and the return data frame is empty

Original data set:

    month   interest
0   2004-01 13
1   2004-02 15
2   2004-03 17
3   2004-04 19
4   2004-05 22

Trying to convert the data with different frequency

ice_cream_interest = pd.read_csv('ice_cream_interest.csv')
ice_cream_interest.set_index('month', inplace=True)
ice_cream_interest = ice_cream_interest.asfreq(pd.infer_freq(ice_cream_interest.index))

    interest
month   
2004-01-01  NaN
2004-02-01  NaN
2004-03-01  NaN
2004-04-01  NaN
2004-05-01  NaN
... ...
2020-04-01  NaN
2020-05-01  NaN
2020-06-01  NaN
2020-07-01  NaN
2020-08-01  NaN

Answer

Given:

     month  interest
0  2004-01        13
1  2004-02        15
2  2004-03        17
3  2004-04        19
4  2004-05        22

Doing:

# Convert to datetime
df.month = pd.to_datetime(df.month)

# Set Index
df = df.set_index('month')

# Convert to freq
df = df.asfreq(pd.infer_freq(df.index))

Output:

>>> df
            interest
month
2004-01-01        13
2004-02-01        15
2004-03-01        17
2004-04-01        19
2004-05-01        22

>>> df.index
DatetimeIndex(['2004-01-01', '2004-02-01', '2004-03-01', '2004-04-01',
               '2004-05-01'],
              dtype='datetime64[ns]', name='month', freq='MS')

We can see it successfully converted to a frequency index.