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create additional rows for missing dates pandas

In [11]: idx = pd.period_range(min(df.date), max(df.date))
    ...: results.reindex(idx, fill_value=0)
    ...:
Out[11]:
                  f1        f2        f3        f4
2000-01-01  2.049157  1.962635  2.756154  2.224751
2000-01-02  2.675899  2.587217  1.540823  1.606150
2000-01-03  0.000000  0.000000  0.000000  0.000000
2000-01-04  0.000000  0.000000  0.000000  0.000000
2000-01-05  0.000000  0.000000  0.000000  0.000000
2000-01-06  0.000000  0.000000  0.000000  0.000000
2000-01-07  0.000000  0.000000  0.000000  0.000000
2000-01-08  0.000000  0.000000  0.000000  0.000000
2000-01-09  0.000000  0.000000  0.000000  0.000000
2000-01-10  0.000000  0.000000  0.000000  0.000000
2000-01-11  0.000000  0.000000  0.000000  0.000000
2000-01-12  0.000000  0.000000  0.000000  0.000000
2000-01-13  0.000000  0.000000  0.000000  0.000000
2000-01-14  0.000000  0.000000  0.000000  0.000000
2000-01-15  0.000000  0.000000  0.000000  0.000000
2000-01-16  0.000000  0.000000  0.000000  0.000000
2000-01-17  0.000000  0.000000  0.000000  0.000000
2000-01-18  0.000000  0.000000  0.000000  0.000000
2000-01-19  0.000000  0.000000  0.000000  0.000000
2000-01-20  0.000000  0.000000  0.000000  0.000000
2000-01-21  0.000000  0.000000  0.000000  0.000000
2000-01-22  0.000000  0.000000  0.000000  0.000000
2000-01-23  0.000000  0.000000  0.000000  0.000000
2000-01-24  0.000000  0.000000  0.000000  0.000000
2000-01-25  0.000000  0.000000  0.000000  0.000000
2000-01-26  0.000000  0.000000  0.000000  0.000000
2000-01-27  0.000000  0.000000  0.000000  0.000000
2000-01-28  0.000000  0.000000  0.000000  0.000000
2000-01-29  0.000000  0.000000  0.000000  0.000000
2000-01-30  0.000000  0.000000  0.000000  0.000000
2000-01-31  0.000000  0.000000  0.000000  0.000000
2000-02-01  0.000000  0.000000  0.000000  0.000000
2000-02-02  0.000000  0.000000  0.000000  0.000000
2000-02-03  0.000000  0.000000  0.000000  0.000000
2000-02-04  1.856158  2.892620  2.986166  2.793448

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create additional rows for missing dates pandas

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