reindex系列应填充NaN

Question

除非我完全误解了reindex的作用，否则我认为下面的片段应该使用NaN来填充已删除的时间索引：

import pandas as pd
import numpy

dateRange = pd.date_range(start='2014-01-01 1:00:00', periods=8, freq='S')
modifiedRange = dateRange.values
modifiedRange = numpy.delete(modifiedRange, (2), axis=0) # remove third row

ts = pd.Series(range(len(modifiedRange)), index=modifiedRange) # series with a gap
print(ts)

ts.reindex(dateRange) # pad the gap with NaN
print(ts)

我得到的输出在这里：

2014-01-01 01:00:00    0
2014-01-01 01:00:01    1
2014-01-01 01:00:03    2
2014-01-01 01:00:04    3
2014-01-01 01:00:05    4
2014-01-01 01:00:06    5
2014-01-01 01:00:07    6
dtype: int64
2014-01-01 01:00:00    0
2014-01-01 01:00:01    1
2014-01-01 01:00:03    2
2014-01-01 01:00:04    3
2014-01-01 01:00:05    4
2014-01-01 01:00:06    5
2014-01-01 01:00:07    6
dtype: int64

两个指纹是一样的..。但是，我希望第二个包含填充的NaN值：

2014-01-01 01:00:00    0
2014-01-01 01:00:01    1
2014-01-01 01:00:02    NaN
2014-01-01 01:00:03    2
2014-01-01 01:00:04    3
2014-01-01 01:00:05    4
2014-01-01 01:00:06    5
2014-01-01 01:00:07    6
dtype: int64

Answer 1

reindex不在现场.这么做，你就会得到你想要的。

ts = ts.reindex(dateRange)
print(ts)