Question

此question已被多次询问，但似乎适用于其他人，但是，当我从其他DataFrame复制列时，我获得了NaN个值df1和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

我需要在df2

中这样做

       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

我尝试了以下内容，

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

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

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

我得到以下内容，

       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？还有另一个post讨论了merge，但我只需要复制它。任何帮助，将不胜感激。

Answer 1

您的DataFrame索引不一样，因此请先重置它们。

df1, df2 = [d.reset_index(drop=True) for d in (df1, df2)]

或者，如果它们的长度相同，则将索引指定为另一个：

df1.index = df2.index

现在，合并DataFrames，

# pd.concat([df2, df1[['date', 'hour']]], axis=1)
df2.join(df1[['date', 'hour']])

        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

Answer 2

试试这个？

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

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

2 个答案: