Python 在pandas.merge\u asof之后保留两个合并键

Python 在pandas.merge\u asof之后保留两个合并键,python,pandas,merge,Python,Pandas,Merge,我发现了这个很好的函数pandas.merge\u asof。 从文件中 pandas.merge_asof(left, right, on=None, left_on=None, right_on=None) Parameters: left : DataFrame right : DataFrame on : label Field name to join on. Must be found in both DataFrames. The data MUST be ordered.

我发现了这个很好的函数
pandas.merge\u asof
。 从文件中

pandas.merge_asof(left, right, on=None, left_on=None, right_on=None)

Parameters: 

left : DataFrame
right : DataFrame
on : label

Field name to join on. Must be found in both DataFrames.
The data MUST be ordered. 
Furthermore this must be a numeric column,such as datetimelike, integer, or float. 
On or left_on/right_on must be given.
它的工作原理与预期一致

但是,我的合并数据框只保留原来位于
左侧的
列。我需要两个都留着,所以

   mydf=pandas.merge_asof(left, right, on='Time')
mydf
以包含

示例数据:

a=pd.DataFrame(data=pd.date_range('20100201', periods=100, freq='6h3min'),columns=['Time'])
b=pd.DataFrame(data=
                  pd.date_range('20100201', periods=24, freq='1h'),columns=['Time'])
b['val']=range(b.shape[0])
out=pd.merge_asof(a,b,on='Time',direction='forward',tolerance=pd.Timedelta('30min'))

我认为一种可能的解决方案是重命名列:

out = pd.merge_asof(a.rename(columns={'Time':'Time1'}), 
                    b.rename(columns={'Time':'Time2'}), 
                    left_on='Time1',
                    right_on='Time2',
                    direction='forward',
                    tolerance=pd.Timedelta('30min'))

print (out.head())
                Time1      Time2  val
0 2010-02-01 00:00:00 2010-02-01  0.0
1 2010-02-01 06:03:00        NaT  NaN
2 2010-02-01 12:06:00        NaT  NaN
3 2010-02-01 18:09:00        NaT  NaN
4 2010-02-02 00:12:00        NaT  NaN

你能添加一些数据样本吗?我在上面…等等