Merge two pandas dataframes that have slightly different values on the column which is being merged-CodePudding

How can I merge two data frames when the column has a slight offset than the column I am merging to?

df1 =

col1	col2
1	a
2	b
3	c

df2 =

col1	col3
1.01	d
2	e
2.95	f

so, the merged column would end up like this even though the values in col1 are slightly different.

df_merge =

col1	col2	col3
1	a	d
2	b	e
3	c	f

I have seen scenarios like this where "col1" is a string, but I'm wondering if it's possible to do this with something like pandas.merge() in the scenario where there is slight numerical offset (e.g /- 0.05).

CodePudding user response：

Lets do merge_asof with tolerance parameter

pd.merge_asof(
    df1.astype({'col1': 'float'}).sort_values('col1'), 
    df2.sort_values('col1'), 
    on='col1', 
    direction='nearest', 
    tolerance=.05
)

   col1 col2 col3
0   1.0    a    d
1   2.0    b    e
2   3.0    c    f

PS: if the dataframes are already sorted on col1 then there is no need to sort again.