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Python: How to place columns with identical names from different dataframes adjacent to each other?

.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty height:90px;width:728px;box-sizing:border-box;

2

I would like to know if there's a way in Python to place columns from different dataframes with the same names (or related names) adjacent to each other.

I know there's the option to use JOIN, but I would like to make a function from the scratch that can achieve the same.

Example:

Let's assume 2 dataframes df1 and df2

df1 is

id A B
50 1 5
60 2 6
70 3 7
80 4 8

df2 is

id A_1 B_1
50 a b
60 c d
70 e f
80 g h

Expected Output: A new dataframe, say df3, looking like this

 id A A_1 B B_1
 50 1 a 5 b
 60 2 c 6 d
 70 3 e 7 f
 80 4 g 8 h

python python-3.x pandas dataframe

share|improve this question

edited Mar 8 at 19:02

Bibliophile20

asked Mar 8 at 18:51

Bibliophile20Bibliophile20

18910

add a comment | 

2

I would like to know if there's a way in Python to place columns from different dataframes with the same names (or related names) adjacent to each other.

I know there's the option to use JOIN, but I would like to make a function from the scratch that can achieve the same.

Example:

Let's assume 2 dataframes df1 and df2

df1 is

id A B
50 1 5
60 2 6
70 3 7
80 4 8

df2 is

id A_1 B_1
50 a b
60 c d
70 e f
80 g h

Expected Output: A new dataframe, say df3, looking like this

 id A A_1 B B_1
 50 1 a 5 b
 60 2 c 6 d
 70 3 e 7 f
 80 4 g 8 h

python python-3.x pandas dataframe

share|improve this question

edited Mar 8 at 19:02

Bibliophile20

asked Mar 8 at 18:51

Bibliophile20Bibliophile20

18910

add a comment | 

I would like to know if there's a way in Python to place columns from different dataframes with the same names (or related names) adjacent to each other.

I know there's the option to use JOIN, but I would like to make a function from the scratch that can achieve the same.

Example:

Let's assume 2 dataframes df1 and df2

df1 is

id A B
50 1 5
60 2 6
70 3 7
80 4 8

df2 is

id A_1 B_1
50 a b
60 c d
70 e f
80 g h

Expected Output: A new dataframe, say df3, looking like this

 id A A_1 B B_1
 50 1 a 5 b
 60 2 c 6 d
 70 3 e 7 f
 80 4 g 8 h

python python-3.x pandas dataframe

share|improve this question

edited Mar 8 at 19:02

Bibliophile20

asked Mar 8 at 18:51

Bibliophile20Bibliophile20

18910

id A B
50 1 5
60 2 6
70 3 7
80 4 8

id A_1 B_1
50 a b
60 c d
70 e f
80 g h

 id A A_1 B B_1
 50 1 a 5 b
 60 2 c 6 d
 70 3 e 7 f
 80 4 g 8 h

share|improve this question

edited Mar 8 at 19:02

Bibliophile20

asked Mar 8 at 18:51

Bibliophile20Bibliophile20

18910

share|improve this question

edited Mar 8 at 19:02

Bibliophile20

asked Mar 8 at 18:51

Bibliophile20Bibliophile20

18910

asked Mar 8 at 18:51

Bibliophile20Bibliophile20

18910

asked Mar 8 at 18:51

Bibliophile20Bibliophile20

18910

2 Answers
2

active

oldest

votes

2

you can use sorted() with column names like:

m=pd.concat([df1.set_index('id'),df2.set_index('id')],axis=1)
m[(sorted(m.columns))].reset_index()

 id A A_1 B B_1
0 50 1 a 5 b
1 60 2 c 6 d
2 70 3 e 7 f
3 80 4 g 8 h

share|improve this answer

answered Mar 8 at 19:11

anky_91anky_91

10.8k2922

add a comment | 

1

First you join the 2 dataframes -

df3 = df1.join(df2, how='inner')

And then you can sort the index -

df3 = df3.sort_index(axis=1)

share|improve this answer

answered Mar 8 at 18:59

MortzMortz

857619

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Hey, @Mortz. Thank you for your response. I am aware that a join could be used, but I was wondering if a function can be made from scratch to achieve the same. Thanks
  
  – Bibliophile20
  Mar 8 at 19:02
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  From scratch? Can you clarify? Do you mean not using the pandas library at all? Maybe, you can take a look at the pandas codebase to get an idea on how such functionality is implemented
  
  – Mortz
  Mar 8 at 19:15
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Yes, I was thinking about the same. Thanks
  
  – Bibliophile20
  Mar 8 at 20:01
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Hey @Mortz, when I try your method, I am getting the following error TypeError: '<' not supported between instances of 'str' and 'int'
  
  – Bibliophile20
  Mar 9 at 13:45
  

  
  
  
  

add a comment | 

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2

you can use sorted() with column names like:

m=pd.concat([df1.set_index('id'),df2.set_index('id')],axis=1)
m[(sorted(m.columns))].reset_index()

 id A A_1 B B_1
0 50 1 a 5 b
1 60 2 c 6 d
2 70 3 e 7 f
3 80 4 g 8 h

share|improve this answer

answered Mar 8 at 19:11

anky_91anky_91

10.8k2922

add a comment | 

2

you can use sorted() with column names like:

m=pd.concat([df1.set_index('id'),df2.set_index('id')],axis=1)
m[(sorted(m.columns))].reset_index()

 id A A_1 B B_1
0 50 1 a 5 b
1 60 2 c 6 d
2 70 3 e 7 f
3 80 4 g 8 h

share|improve this answer

answered Mar 8 at 19:11

anky_91anky_91

10.8k2922

add a comment | 

you can use sorted() with column names like:

m=pd.concat([df1.set_index('id'),df2.set_index('id')],axis=1)
m[(sorted(m.columns))].reset_index()

 id A A_1 B B_1
0 50 1 a 5 b
1 60 2 c 6 d
2 70 3 e 7 f
3 80 4 g 8 h

share|improve this answer

answered Mar 8 at 19:11

anky_91anky_91

10.8k2922

m=pd.concat([df1.set_index('id'),df2.set_index('id')],axis=1)
m[(sorted(m.columns))].reset_index()

 id A A_1 B B_1
0 50 1 a 5 b
1 60 2 c 6 d
2 70 3 e 7 f
3 80 4 g 8 h

share|improve this answer

answered Mar 8 at 19:11

anky_91anky_91

10.8k2922

answered Mar 8 at 19:11

anky_91anky_91

10.8k2922

answered Mar 8 at 19:11

anky_91anky_91

10.8k2922

1

First you join the 2 dataframes -

df3 = df1.join(df2, how='inner')

And then you can sort the index -

df3 = df3.sort_index(axis=1)

share|improve this answer

answered Mar 8 at 18:59

MortzMortz

857619

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Hey, @Mortz. Thank you for your response. I am aware that a join could be used, but I was wondering if a function can be made from scratch to achieve the same. Thanks
  
  – Bibliophile20
  Mar 8 at 19:02
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  From scratch? Can you clarify? Do you mean not using the pandas library at all? Maybe, you can take a look at the pandas codebase to get an idea on how such functionality is implemented
  
  – Mortz
  Mar 8 at 19:15
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Yes, I was thinking about the same. Thanks
  
  – Bibliophile20
  Mar 8 at 20:01
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Hey @Mortz, when I try your method, I am getting the following error TypeError: '<' not supported between instances of 'str' and 'int'
  
  – Bibliophile20
  Mar 9 at 13:45
  

  
  
  
  

add a comment | 

1

First you join the 2 dataframes -

df3 = df1.join(df2, how='inner')

And then you can sort the index -

df3 = df3.sort_index(axis=1)

share|improve this answer

answered Mar 8 at 18:59

MortzMortz

857619

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Hey, @Mortz. Thank you for your response. I am aware that a join could be used, but I was wondering if a function can be made from scratch to achieve the same. Thanks
  
  – Bibliophile20
  Mar 8 at 19:02
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  From scratch? Can you clarify? Do you mean not using the pandas library at all? Maybe, you can take a look at the pandas codebase to get an idea on how such functionality is implemented
  
  – Mortz
  Mar 8 at 19:15
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Yes, I was thinking about the same. Thanks
  
  – Bibliophile20
  Mar 8 at 20:01
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Hey @Mortz, when I try your method, I am getting the following error TypeError: '<' not supported between instances of 'str' and 'int'
  
  – Bibliophile20
  Mar 9 at 13:45
  

  
  
  
  

add a comment | 

First you join the 2 dataframes -

df3 = df1.join(df2, how='inner')

And then you can sort the index -

df3 = df3.sort_index(axis=1)

share|improve this answer

answered Mar 8 at 18:59

MortzMortz

857619

df3 = df1.join(df2, how='inner')

df3 = df3.sort_index(axis=1)

share|improve this answer

answered Mar 8 at 18:59

MortzMortz

857619

answered Mar 8 at 18:59

MortzMortz

857619

answered Mar 8 at 18:59

MortzMortz

857619