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Merge two dataframes with same column names

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  • Last Updated : 05 Apr, 2021

In order to merge two data frames with the same column names, we are going to use the pandas.concat(). This function does all the heavy lifting of performing concatenation operations along with an axis of Pandas objects while performing optional set logic (union or intersection) of the indexes (if any) on the other axes.

Syntax: concat(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)

Approach

  • Import module
  • Create or load first dataframe
  • Create or load second dataframe
  • Concatenate on the basis of same column names
  • Display result

Below are various examples that depict how to merge two data frames with the same column names:

Example 1: 

Python3




# import module
import pandas as pd
  
# assign dataframes
data1 = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
                     columns=['A', 'B', 'C'])
  
data2 = pd.DataFrame([[3, 4], [5, 6]],
                     columns=['A', 'C'])
  
# display dataframes
print('Dataframes:')
display(data1)
display(data2)
  
# merge two data frames
print('After merging:')
pd.concat([data1, data2], axis=0)

Output:

Example 2:

Python3




# import module
import pandas as pd
  
# assign dataframes
data1 = pd.DataFrame([[25, 77.5, 'A'], [30, 60.2, 'B']],
                     columns=['Students', 'Avg Marks', 'Section'])
  
data2 = pd.DataFrame([[52, 'C'], [25, 'A']],
                     columns=['Students', 'Section'])
  
# display dataframes
print('Dataframes:')
display(data1)
display(data2)
  
# merge two data frames
print('After merging:')
pd.concat([data1, data2], axis=0)

Output:

Example 3:

Python3




# import module
import pandas as pd
  
# assign dataframes
data1 = pd.DataFrame([[25, 77.5, 'A'], [30, 60.2, 'B'],
                      [25, 70.7, 'C']],
                     columns=['Students', 'Avg Marks', 'Section'])
  
data2 = pd.DataFrame([[30, 70.2, 'A'], [25, 65.2, 'B'],
                      [35, 77.7, 'C']],
                     columns=['Students', 'Avg Marks', 'Section'])
  
  
# display dataframes
print('Dataframes:')
display(data1)
display(data2)
  
# merge two data frames
print('After merging:')
pd.concat([data1, data2], axis=0)

Output:


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