I have a (pandas) dataset that consists of a datetime index and several columns for different locations indicating wind speeds.
How can I duplicate the rows two times and always add one hour to the datetime index?
| Date | AL | BA |
|---|---|---|
| 2000-01-01 00:00:00 | 2.994117 | 4.658971 |
| 2000-01-01 03:00:00 | 3.367553 | 5.964710 |
| 2000-01-01 06:00:00 | 3.431327 | 6.633670 |
I have used concat to multiply the rows and could later on also add a new auto_increment column for the hours, but this is not really elegant.
CodePudding user response：
Use DataFrame.asfreq with method='ffill':
df = df.set_index('Date').asfreq('1H', method='ffill')
print (df)
AL BA
Date
2000-01-01 00:00:00 2.994117 4.658971
2000-01-01 01:00:00 2.994117 4.658971
2000-01-01 02:00:00 2.994117 4.658971
2000-01-01 03:00:00 3.367553 5.964710
2000-01-01 04:00:00 3.367553 5.964710
2000-01-01 05:00:00 3.367553 5.964710
2000-01-01 06:00:00 3.431327 6.633670
If need append next 2 rows:
df1 = pd.concat([df,
df.iloc[[-1]].assign(Date = lambda x: x['Date'] pd.Timedelta('2H'))])
df1 = df1.set_index('Date').asfreq('1H', method='ffill')
print (df1)
AL BA
Date
2000-01-01 00:00:00 2.994117 4.658971
2000-01-01 01:00:00 2.994117 4.658971
2000-01-01 02:00:00 2.994117 4.658971
2000-01-01 03:00:00 3.367553 5.964710
2000-01-01 04:00:00 3.367553 5.964710
2000-01-01 05:00:00 3.367553 5.964710
2000-01-01 06:00:00 3.431327 6.633670
2000-01-01 07:00:00 3.431327 6.633670
2000-01-01 08:00:00 3.431327 6.633670
CodePudding user response：
copying can be done simply by indexing new rows like:
df.iloc[3:6,:] = df.iloc[0:2,:]
and changing the datetime index in the new rows can be done via:
df.iloc[3:6].index.hour = 1