在 Pandas Dataframe pd.concat 之后，我得到了 NaN
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After Pandas Dataframe pd.concat I get NaNs
提问by prre72
I have three pandas df one of them has been 'row'-shifted and the first element is empty. When I concatenate the three df to obtain a single 3-column dataframe I get all NaN in two out of three columns:
我有三只Pandas df 其中一个已被“行”移动，第一个元素为空。当我连接三个 df 以获得单个 3 列数据帧时，我在三列中的两列中获得所有 NaN：
df1:
df1：
S
2010-12-31 True
2011-01-01 False
2011-01-02 False
df2:
df2：
P
2010-12-31
2011-01-01 On
2011-01-02 On
df3:
df3：
C
2010-12-31 On
2011-01-01 On
2011-01-02 On
res = pd.concat([df1, df2, df3]):
res = pd.concat([df1, df2, df3]):
P C S
2010-12-31 NaN NaN True
2011-01-01 NaN NaN False
2011-01-02 NaN NaN False
The order seems to be inverted as well...
顺序好像也颠倒了……
Many thanks
非常感谢
回答by unutbu
In [2]: index = pd.DatetimeIndex(['2010-12-31', '2011-01-01', '2011-01-02'])
In [3]: df1 = pd.DataFrame({'S':[True,False,False]}, index=index)
In [4]: df2 = pd.DataFrame({'P':['','On','On']}, index=index)
In [5]: df3 = pd.DataFrame({'C':['On','On','On']}, index=index)
If your DataFrames are defined as above, then pd.concatwith axis=1should work:
如果您的 DataFrame 定义如上，那么pd.concatwithaxis=1应该可以工作：
In [7]: pd.concat([df1,df2,df3], axis=1)
Out[7]:
S P C
2010-12-31 True On
2011-01-01 False On On
2011-01-02 False On On
[3 rows x 3 columns]
