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0

I am trying to automatically assign integers as column headers to a pandas df after a specific string. I can do this manually by reading and counting the amount of columns in any one df. e.g.

df.columns=['X',1,2,3...]

But I want to achieve this automatically without having to count the number of columns. The first column should be a string and then automatically assign incremental integers to the other columns..

I attempted to achieve this using a combination of @kudeh's suggestion.

df.columns = 'X' + [i for i in range(1,len(df.columns)+1)]

But this returns an error:

df.columns = 'X' + [i for i in range(1,len(df.columns)+1)]

TypeError: must be str, not list

Intended Output:

df.columns = ['X',1,2,3...]

python pandas dataframe int assign

share|improve this question

edited Mar 8 at 0:29

jonboy

asked Mar 7 at 23:54

jonboyjonboy

69111

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I have to manually count the columns and insert df.columns['X',1,2,n]. I want to automatically assign the columns without having to count them.
  
  – jonboy
  Mar 8 at 0:31
  

  
  
  
  

add a comment | 

0

I am trying to automatically assign integers as column headers to a pandas df after a specific string. I can do this manually by reading and counting the amount of columns in any one df. e.g.

df.columns=['X',1,2,3...]

But I want to achieve this automatically without having to count the number of columns. The first column should be a string and then automatically assign incremental integers to the other columns..

I attempted to achieve this using a combination of @kudeh's suggestion.

df.columns = 'X' + [i for i in range(1,len(df.columns)+1)]

But this returns an error:

df.columns = 'X' + [i for i in range(1,len(df.columns)+1)]

TypeError: must be str, not list

Intended Output:

df.columns = ['X',1,2,3...]

python pandas dataframe int assign

share|improve this question

edited Mar 8 at 0:29

jonboy

asked Mar 7 at 23:54

jonboyjonboy

69111

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I have to manually count the columns and insert df.columns['X',1,2,n]. I want to automatically assign the columns without having to count them.
  
  – jonboy
  Mar 8 at 0:31
  

  
  
  
  

add a comment | 

I am trying to automatically assign integers as column headers to a pandas df after a specific string. I can do this manually by reading and counting the amount of columns in any one df. e.g.

df.columns=['X',1,2,3...]

But I want to achieve this automatically without having to count the number of columns. The first column should be a string and then automatically assign incremental integers to the other columns..

I attempted to achieve this using a combination of @kudeh's suggestion.

df.columns = 'X' + [i for i in range(1,len(df.columns)+1)]

But this returns an error:

df.columns = 'X' + [i for i in range(1,len(df.columns)+1)]

TypeError: must be str, not list

Intended Output:

df.columns = ['X',1,2,3...]

python pandas dataframe int assign

share|improve this question

edited Mar 8 at 0:29

jonboy

asked Mar 7 at 23:54

jonboyjonboy

69111

df.columns=['X',1,2,3...]

df.columns = 'X' + [i for i in range(1,len(df.columns)+1)]

df.columns = 'X' + [i for i in range(1,len(df.columns)+1)]

TypeError: must be str, not list

df.columns = ['X',1,2,3...]

share|improve this question

edited Mar 8 at 0:29

jonboy

asked Mar 7 at 23:54

jonboyjonboy

69111

share|improve this question

edited Mar 8 at 0:29

jonboy

asked Mar 7 at 23:54

jonboyjonboy

69111

asked Mar 7 at 23:54

jonboyjonboy

69111

asked Mar 7 at 23:54

jonboyjonboy

69111

1 Answer
1

active

oldest

votes

1

cols = ['X']
otherCols = [i for i in range(1,len(df.columns))]
cols.extend(otherCols)

df.columns = cols

share|improve this answer

edited Mar 8 at 0:33

answered Mar 8 at 0:09

kudehkudeh

350110

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Sorry @kudeh. I didn't explain the question properly. I've amended it now
  
  – jonboy
  Mar 8 at 0:20
  

  
  
  
  

add a comment | 

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1

cols = ['X']
otherCols = [i for i in range(1,len(df.columns))]
cols.extend(otherCols)

df.columns = cols

share|improve this answer

edited Mar 8 at 0:33

answered Mar 8 at 0:09

kudehkudeh

350110

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Sorry @kudeh. I didn't explain the question properly. I've amended it now
  
  – jonboy
  Mar 8 at 0:20
  

  
  
  
  

add a comment | 

1

cols = ['X']
otherCols = [i for i in range(1,len(df.columns))]
cols.extend(otherCols)

df.columns = cols

share|improve this answer

edited Mar 8 at 0:33

answered Mar 8 at 0:09

kudehkudeh

350110

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Sorry @kudeh. I didn't explain the question properly. I've amended it now
  
  – jonboy
  Mar 8 at 0:20
  

  
  
  
  

add a comment | 

cols = ['X']
otherCols = [i for i in range(1,len(df.columns))]
cols.extend(otherCols)

df.columns = cols

share|improve this answer

edited Mar 8 at 0:33

answered Mar 8 at 0:09

kudehkudeh

350110

cols = ['X']
otherCols = [i for i in range(1,len(df.columns))]
cols.extend(otherCols)

df.columns = cols

share|improve this answer

edited Mar 8 at 0:33

answered Mar 8 at 0:09

kudehkudeh

350110

answered Mar 8 at 0:09

kudehkudeh

350110

answered Mar 8 at 0:09

kudehkudeh

350110