Pandas (31)

How to fill an intermittent time series so all missing dates show up with values of previous non-missing date?

# Input
ser = pd.Series([1,10,3, np.nan], index=pd.to_datetime(['2000-01-01', '2000-01-03', '2000-01-06', '2000-01-08']))

# 1
ser.resample('D').ffill()  # fill with previous value

# 2
ser.resample('D').bfill()  # fill with next value
ser.resample('D').bfill().ffill()  # fill next else prev value

# output
2000-01-01     1.0
2000-01-02    10.0
2000-01-03    10.0
2000-01-04     3.0
2000-01-05     3.0
2000-01-06     3.0
2000-01-07     3.0
2000-01-08     3.0
Freq: D, dtype: float64