Find Columns Shared By Two Data Frames

Pandas is the open-source Python library used for Data analysis and manipulation. It is fast, powerful, flexible, and easy to use. In this article, we will discuss how to find columns that are common between two Data Frames. Below is the different approach that can be used to find common columns.

Method 1: Using Numpy intersect1d method

In this example, we will create Pandas Dataframe from the list, and then we will use Numpy’s intersect1d() method which will return columns that are common between two Dataframes.

Python3

# Importing libraries
import pandas as pd
import numpy as np

# Creating Dataframes
a = [{'Name': 'abc', 'Age': 8, 'Grade': 3},{'Name': 'xyz', 'Age': 9, 'Grade': 3}]
df1 = pd.DataFrame(a)
b = [{'ID': 1,'Name': 'abc', 'Age': 8},{'ID': 2,'Name': 'xyz', 'Age': 9}]
df2 = pd.DataFrame(b)

# Printing Dataframes
display(df1)
display(df2)

# Finding Common columns
a = np.intersect1d(df2.columns, df1.columns)

# Printing common columns
print ("Common Columns:",a)

Output:

Method 2: Using Pandas intersection method

In this example, we will create Pandas Dataframe from the list, and then we will use Panda’s intersection() method which will return columns that are common between two Dataframes. 

Python3

# Importing libraries
import pandas as pd

# Creating Dataframes
a = [{'Name': 'abc', 'Age': 8, 'Grade': 3},
     {'Name': 'xyz', 'Age': 9, 'Grade': 3}]

df1 = pd.DataFrame(a)
b = [{'ID': 1,'Name': 'abc', 'Age': 8},
     {'ID': 2,'Name': 'xyz', 'Age': 9}]

df2 = pd.DataFrame(b)

# Printing Dataframes
display(df1)
display(df2)

# Finding Common columns
a = df2.columns.intersection(df1.columns)

# Printing common columns
print ("Common Columns:",a)

Output:

Method 3: In this example, we will use & operator to find common columns. 

Python3

# Importing libraries
import pandas as pd

# Creating Dataframes
a = [{'Name': 'abc', 'Age': 8, 'Grade': 3},
     {'Name': 'xyz', 'Age': 9, 'Grade': 3}]

df1 = pd.DataFrame(a)
b = [{'ID': 1,'Name': 'abc', 'Age': 8},
     {'ID': 2,'Name': 'xyz', 'Age': 9}]

df2 = pd.DataFrame(b)

# printing Dataframes
display(df1)
display(df2)

# Finding Common columns
a = df1.columns & df2.columns

# Printing common columns
print ("Common Columns:",a)

Output: