Reindexing in Pandas DataFrame

Michael Zippo 18.07.2021

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Reindexing in Pandas can be used to change the index of rows and columns in a DataFrame. Indexes can be used with reference to multiple DataStructure indexes associated with multiple panda series or panda DataFrame. Let’s see how we can reindex columns and rows in a Pandas DataFrame.

Reindex Rows

You can reindex one or more rows using reindex () . The default values ‚Äã‚Äãin the new index that are not in the data frame are assigned NaN.

Example # 1:

# import numpy and pandas module

import pandas as pd

import numpy as np

column = [ ’a’ , ’ b’ , ’c’ , ’ d’ , ’e’ ]

index = [ ’A’ , ’ B’ , ’C’ , ’ D’ , ’E’ ]

# create a data frame of random array values ‚Äã‚Äã

df1 = pd.DataFrame (np.random.rand ( 5 , 5 ),

columns = column, index = index)

print (df1)

print ( ’Dataframe after reindexing rows:’ ,

df1.reindex ([ ’B’ , ’ D’ , ’ A’ , ’C’ , ’E’ ]))

Output:

Example # 2:

       # import numpy and pandas modules  
   import   pandas as pd 
   import   numpy as np 
  
   column   =   [  ’a’  ,  ’ b’  ,   ’c’  ,  ’ d’  ,   ’e’  ] 
   index   =   [  ’A’  ,   ’B’  ,  ’ C’  ,   ’D’  ,  ’ E ’ ] 
    
  # create data frame of random array values ‚Äã‚Äã 
   df1   =   pd.DataFrame (np.random.rand (  5  ,   5  ), 
   columns   =   column, index   =   index ) 
  
  # create a new index for rows   
  new_index   =   [  ’U’  ,  ’ A’  ,   ’B’  ,  ’ C’   ,   ’Z’  ] 
  
   print   (df1.reindex (new_index))

Output:

Re-indexing columns using keyword axis

It is possible to reindex one column or multiple columns using reindex () and specifying the axis we want to reindex. The default values ‚Äã‚Äãin the new index that are not in the data frame are assigned NaN.

Example # 1:

# import numpy and pandas module

import pandas as pd

import numpy as np

column = [ ’a’ , ’ b’ , ’c’ , ’ d’ , ’e’ ]

index = [ ’A’ , ’ B’ , ’C’ , ’ D’ , ’E’ ]

# create a data frame of random array values ‚Äã‚Äã

df1 = pd.DataFrame (np.random.rand ( 5 , 5 ),

columns = column, index = index)

colum = [ ’e’ , ’ a’ , ’b’ , ’c’ , ’ d’ ]

# create a new index for columns

print (df1.reindex (colum, axis = ’ columns’ ))

Output:

Example # 2:

# import numpy and pandas module

import pandas as pd

import numpy as np

column = [ ’a’ , ’b’ , ’ c’ , ’ d’ , ’e’ ]

index = [ ’A’ , ’ B’ , ’C’ , ’ D’ , ’E’ ]

# create a data frame of random array values ‚Äã‚Äã

df1 = pd.DataFrame (np.random.rand ( 5 , 5 ),

columns = column, index = index)

colum = [ ’a’ , ’ b’ , ’c’ , ’ g’ , ’ h’ ]

# create a new index for columns

print (df1.reindex (colum, axis = ’columns’ ))

Output:

Replacing missing values ‚Äã‚Äã

Code # 1: You can fill in missing values ‚Äã‚Äãfrom a data frame by passing a value to the keyword fill_value . This keyword replaces NaN values.

# import numpy and pandas module

import pandas as pd

import numpy as np

column = [ ’ a’ , ’b’ , ’ c’ , ’d’ , ’ e’ ]

index = [ ’ A’ , ’B’ , ’ C’ , ’D’ , ’ E’ ]

# create a data frame of random array values ‚Äã‚Äã

df1 = pd.DataFrame (np.random.rand ( 5 , 5 ) ,

columns = column, index = index)

colum = [ ’a’ , ’ b’ , ’c’ , ’g’ , ’h’ ]

# create a new index for columns

print (df1.reindex (colum, axis = ’columns’ , fill_value = 1.5 ))

Output:

Code # 2: Replace missing data with a string.

# import numpy and pandas module

import pandas as pd

import numpy as np

column = [ ’a’ , ’ b’ , ’ c’ , ’d’ , ’e’ ]

index = [ ’A’ , ’B’ , ’ C’ , ’D’ , ’E’ ]

    
  # create a data frame of random array values ‚Äã‚Äã 
   df1   =   pd.DataFrame (np.random.rand (  5  ,   5  ), 
     columns   =   column, index   =   index) 
  
   colum   =   [  ’a’  ,   ’b’  ,  ’ c’  ,   ’ g’  ,   ’h’  ]   
 
  # create a new index for columns  
   print   (df1.reindex (colum, axis   =   ’columns’  , fill_value   =  ’ data missing’  ))

Output:

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We hope this article has helped you to resolve the problem. Apart from Reindexing in Pandas DataFrame, check other array Python module-related topics.

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Chen Richtgofen

San Francisco | 2023-02-01

Thanks for explaining! I was stuck with Reindexing in Pandas DataFrame for some hours, finally got it done 🤗. I am just not quite sure it is the best method

Javier Williams

Milan | 2023-02-01

Thanks for explaining! I was stuck with Reindexing in Pandas DataFrame for some hours, finally got it done 🤗. Checked yesterday, it works!

Cornwall Ungerschaft

Prague | 2023-02-01

string Python module is always a bit confusing 😭 Reindexing in Pandas DataFrame is not the only problem I encountered. I am just not quite sure it is the best method