Erstellen Sie zusätzliche Zeilen für fehlende Daten 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
Cheerful Crane