When I insert pandas Series into dataframe, all values become NaN

问题

I have a pandas series that looks like this:

>>> myseries 2012-01-01 15:20:00-05:00 2 2012-01-01 15:30:00-05:00 1 2012-01-01 15:40:00-05:00 0...

And I try to put it into a dataframe as so:

>>> mydf = pd.DataFrame(myseries, columns=["myseries"], index = myseries.index)

and all the values become NaN for some reason:

>>> mydf 2012-01-01 15:20:00-05:00 NaN 2012-01-01 15:30:00-05:00 NaN 2012-01-01 15:40:00-05:00 NaN

I'm pretty confused. This seems like a really simple application. What am I doing wrong? By the way, replacing with pd.DataFrame(myseries.values, columns=...) fixes the problem, but why is it necessary? Thank you.

回答1:

s = pd.Series([0,1,2,3], index=pd.date_range('2014-01-01', periods=4))
df = pd.DataFrame(s, columns=['s'], index=s.index)
print(df)

yields

            s
2014-01-01  0
2014-01-02  1
2014-01-03  2
2014-01-04  3

回答2:

Even simpler:

s = pd.Series([0,1,2,3], index=pd.date_range('2014-01-01', periods=4), name='s')
df = pd.DataFrame(s)
print(df)

yields

            s
2014-01-01  0
2014-01-02  1
2014-01-03  2
2014-01-04  3

来源：https://stackoverflow.com/questions/28934992/when-i-insert-pandas-series-into-dataframe-all-values-become-nan