Dates       rates
7/26/2019   1.04
7/30/2019   1.0116
7/31/2019   1.005
8/1/2019    1.035
8/2/2019    1.01
8/6/2019    0.9886
8/7/2019    1.0048
8/8/2019    0.97
8/9/2019    0.9659
8/12/2019   0.965

In the above dataframe, 29th July 2019 and 5th August 2019 are missing. These are weekdays. I need to populate the missing weekdays dates and assign the 'rate' which is next to missing date. For example: Assign the 30th july 2019 'rate' to the missing 29th july 2019 as well. Please suggest. Thanks

You can use for example pd.offsets.BDay() to get next business day.

Initial dataframe (the Dates column is of DateTime type):

       Dates   rates
0 2019-07-26  1.0400
1 2019-07-30  1.0116
2 2019-07-31  1.0050
3 2019-08-01  1.0350
4 2019-08-02  1.0100
5 2019-08-06  0.9886
6 2019-08-07  1.0048
7 2019-08-08  0.9700
8 2019-08-09  0.9659
9 2019-08-12  0.9650

Then:

df = df.merge(pd.DataFrame({'Dates':df['Dates'] + pd.offsets.BDay()}), on='Dates', how='outer').sort_values('Dates').bfill().dropna().reset_index(drop=True)print(df)

Prints:

        Dates   rates
0  2019-07-26  1.0400
1  2019-07-29  1.0116
2  2019-07-30  1.0116
3  2019-07-31  1.0050
4  2019-08-01  1.0350
5  2019-08-02  1.0100
6  2019-08-05  0.9886
7  2019-08-06  0.9886
8  2019-08-07  1.0048
9  2019-08-08  0.9700
10 2019-08-09  0.9659
11 2019-08-12  0.9650