Combine two dataframes with same values in several columns

Question

I would like to combine two datframe with same index number but different columns number like:

>>> df1
   col_1 col_2 col_3 col_4
0    a     x    NaN    54
1    a     y     5     34
2    b     z    NaN    64
3    c     z     7     23


>>> df2
   col_1 col_2 col_3 col_4 col_5
0    a     x    NaN    14    14
1    b     z    NaN     9     7
2    c     z     7     51    53
3    a     y     5     87    66

The df2 will combine in df1 based on the values of col_1, col_2 andcol_3.

But the order of the rows will not be the same.

I want to combine them based on the order of df1

And the answer will be like this:

   col_1 col_2 col_3 col_4 col_4 col_5
0    a     x    NaN    54    14    14
1    a     y     5     34    87    66
2    b     z    NaN    64     9     7
3    c     z     7     23    51    53

I don't care about the column name, so you guys can modify them if you need.

Do you want to ignore the values in col1, col2 and col3 from df2? — razdi
– razdi, Commented May 10, 2019 at 4:25

gmds · Accepted Answer · 2019-05-10 05:34:07Z

3

If I understand correctly, you want to join on the indices without sorting:

result = df1.join(df2.drop(columns=['col_1', 'col_2', 'col_3']), lsuffix='x', rsuffix='y', sort=False)
print(result)

Output:

  col_1 col_2 col_3 col_4x col_4y col_5
0     a     x   NaN     54     14    14
1     a     y     5     34      9     7
2     b     z   NaN     64     51    53
3     c     z     7     23     87    66

Otherwise, a simple merge on the first three columns, again without sorting, will do:

result = df1.merge(df2, on=['col_1', 'col_2', 'col_3'], sort=False)
print(result)

Output:

  col_1 col_2 col_3 col_4_x col_4_y col_5
0     a     x   NaN      54      14    14
1     a     y     5      34      87    66
2     b     z   NaN      64       9     7
3     c     z     7      23      51    53

edited May 10, 2019 at 5:34

answered May 10, 2019 at 4:28

gmds

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4 Comments

zero Over a year ago

didn't notice the weird request (thought he just wanted it sorted based on df1.). good catch.

Webcy Over a year ago

oh... I'm so sorry. df2 's values in col_4 and col_5 might change the order in to df1.

Webcy Over a year ago

I have modified the result. This is my first time to ask the question, sorry

gmds Over a year ago

@zero Yes, it is rather strange. I originally also gave a merge-based answer.

heena bawa · Accepted Answer · 2019-05-10 04:46:56Z

1

You can use:

df1.merge(df2, how='right', on=['col_1', 'col_2', 'col_3'], sort=False)

  col_1 col_2  col_3  col_4_x  col_4_y  col_5
0     a     x    NaN       54       14     14
1     a     y    5.0       34       87     66
2     b     z    NaN       64        9      7
3     c     z    7.0       23       51     53

answered May 10, 2019 at 4:46

heena bawa

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Comments

Ajay Shah · Accepted Answer · 2019-05-10 04:31:27Z

0

Just use the merge function available

import pandas as pd

df=df1.merge(df2,left_index=True)

answered May 10, 2019 at 4:31

Ajay Shah

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