在熊猫数据框中重新索引多索引

Question

I'm trying to reindex a 2-level multiindex pandas dataframe. Data struct looks like this:

In [1]: df.head(5)


Out [1]:                                arrivals    departs
station         datetime
S1              2014-03-03 07:45:00     1           1
                2014-03-03 09:00:00     2           1
                2014-03-03 11:45:00     1           1
                2014-03-04 08:45:00     1           1
                2014-03-04 09:45:00     2           1

I want to fill datetime gaps with 15 minute intervals, but when I call

In [2]: df.reindex(pd.date_range(start='2014-03-03 07:45:00', 
                   end='2014-03-04 07:45:00', freq='15min'), level=1)

I get the exact same dataframe. I expected something like the following

Out [2]:                                arrivals    departs
station         datetime
S1              2014-03-03 07:45:00     1           1 <-- original row
                2014-03-03 08:00:00     0           0 <-- filled in row
                2014-03-03 08:15:00     0           0 <-- filled in
                2014-03-03 08:30:00     0           0 <-- filled in
                2014-03-03 08:45:00     0           0 <-- filled in
                2014-03-03 09:00:00     2           1 <-- original
                etc...

Any ideas?

Answer 1

Turn it back into a simple datetimeindex and fill the gaps:

df = (df.unstack(level=0)
        .reindex(pd.date_range(start='2014-03-03 07:45:00', 
                   end='2014-03-04 07:45:00', freq='15min')))


df = df.fillna(0)  # for the data, 0 is the desired value

df.stack('station').swaplevel(0,1).sort_index()