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
8/12/2019 0.965
df = df.merge(
p
you can use reindex with bdate_range to create all the missing values in rates for business days only:
new_df = df.set_index('Dates')\
.reindex( pd.bdate_range(df.Dates.min(), df.Dates.max(), name='Dates'),
method='bfill')\
.reset_index()
print (new_df)
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 0.9650
9 2019-08-08 0.9650
10 2019-08-09 0.9650
11 2019-08-12 0.9650