将列从一个DataFrame复制到另一个DataFrame会产生NaN值吗？

Question

这个问题已被问过很多次了,它似乎对其他人NaN有用,但是,当我从不同的DataFrame中复制一个列时,我得到了值(df1并且df2长度相同).

df1

        date     hour      var1
a   2017-05-01  00:00:00   456585
b   2017-05-01  01:00:00   899875
c   2017-05-01  02:00:00   569566
d   2017-05-01  03:00:00   458756
e   2017-05-01  04:00:00   231458
f   2017-05-01  05:00:00   986545

df2

      MyVar1     MyVar2 
 0  6169.719338 3688.045368
 1  5861.148007 3152.238704
 2  5797.053347 2700.469871
 3  5779.102340 2730.471948
 4  6708.219647 3181.298291
 5  8550.380343 3793.580394

我需要这样的 df2

       MyVar1    MyVar2        date        hour
 0  6169.719338 3688.045368  2017-05-01  00:00:00
 1  5861.148007 3152.238704  2017-05-01  01:00:00
 2  5797.053347 2700.469871  2017-05-01  02:00:00
 3  5779.102340 2730.471948  2017-05-01  03:00:00
 4  6708.219647 3181.298291  2017-05-01  04:00:00
 5  8550.380343 3793.580394  2017-05-01  05:00:00

我试过以下,

df2['date'] = df1['date']
df2['hour'] = df1['hour']

type(df1)
>> pandas.core.frame.DataFrame

type(df2)
>> pandas.core.frame.DataFrame

我得到以下,

       MyVar1    MyVar2      date       hour
 0  6169.719338 3688.045368  NaN        NaN
 1  5861.148007 3152.238704  NaN        NaN
 2  5797.053347 2700.469871  NaN        NaN

为什么会这样？还有另一篇文章讨论merge,但我只需要复制它.任何帮助,将不胜感激.

Answer 1

您的DataFrame的索引不一样,因此请先重置它们.

# Setup
A = pd.DataFrame(index=['a', 'b', 'c']) 
B = pd.DataFrame(index=['b', 'c', 'd', 'f'])                                  
C = pd.DataFrame(index=[1, 2, 3])

或者,如果它们的长度相同,则将一个索引指定给另一个:

# Example of alignable indexes - A & B (complete or partial overlap of indexes)
A.index B.index
      a        
      b       b   (overlap)
      c       c   (overlap)
              d
              f

现在,组合DataFrames,

# Example of unalignable indexes - A & C (no overlap at all)
A.index C.index
      a        
      b        
      c        
              1
              2
              3

Answer 2

试试这个 ？

df2['date'] = df1['date'].values
df2['hour'] = df1['hour'].values