I have a dataframe with an index of dates. Each data is the first of the month. I want to fill in all missing dates in the index at a daily level.
I thought this should work:
daily=pd.date_range('2016-01-01', '2018-01-01', freq='D')
df=df.reindex(daily)
But it's returning NA in rows that should have data in (1st of the month dates) Can anyone see the issue?
Use reindex with parameter method='ffill' or resample with ffill for more general solution, because is not necessary create new index by date_range:
df = pd.DataFrame({'a': range(13)},
index=pd.date_range('2016-01-01', '2017-01-01', freq='MS'))
print (df)
a
2016-01-01 0
2016-02-01 1
2016-03-01 2
2016-04-01 3
2016-05-01 4
2016-06-01 5
2016-07-01 6
2016-08-01 7
2016-09-01 8
2016-10-01 9
2016-11-01 10
2016-12-01 11
2017-01-01 12
daily=pd.date_range('2016-01-01', '2018-01-01', freq='D')
df1 = df.reindex(daily, method='ffill')
Another solution:
df1 = df.resample('D').ffill()
print (df1.head())
a
2016-01-01 0
2016-01-02 0
2016-01-03 0
2016-01-04 0
2016-01-05 0
