在pandas数据帧中填写缺失值

Question

I would like to fill in missing values in my pandas dataframe. Optimally I would like the minute column to range from 0-60 for each hour. Unfortunately, the data generating process did not record any rows where sub_count = 0 . Is there anyway to do this? My data covers the dates 2014-03-31 and 2014-04-01 .

df = 

   sub_count        date  hour  minute
0          1  2014-03-31     0       0
1          1  2014-03-31     0       4
2          1  2014-03-31     0       5
3          1  2014-03-31     0       6
4          2  2014-03-31     0       7
...

Answer 1

Construct a DatetimeIndex (you may be able to do this while reading the data in, depending on how it's stored):

df = df.set_index(pd.to_datetime(df.date + 'T' +
                                 df.hour.astype(str) + ':' +
                                 df.minute.astype(str))

In [23]: df = df['sub_count']

In [24]: df
Out[24]: 
2014-03-31 00:00:00    1
2014-03-31 00:04:00    1
2014-03-31 00:05:00    1
2014-03-31 00:06:00    1
2014-03-31 00:07:00    2
Name: sub_count, dtype: int64

Then resample:

In [26]: df.resample('T')
Out[26]: 
2014-03-31 00:00:00     1
2014-03-31 00:01:00   NaN
2014-03-31 00:02:00   NaN
2014-03-31 00:03:00   NaN
2014-03-31 00:04:00     1
2014-03-31 00:05:00     1
2014-03-31 00:06:00     1
2014-03-31 00:07:00     2
Freq: T, Name: sub_count, dtype: float64