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Delete a column from a Pandas DataFrame

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  • Last Updated : 17 Jan, 2022

Deletion is one of the primary operations when it comes to data analysis. Very often we see that a particular attribute in the data frame is not at all useful for us while working on a specific analysis, rather having it may lead to problems and unnecessary change in the prediction. For example, if we want to analyze the students’ BMI of a particular school, then there is no need to have the religion column/attribute for the students, so we prefer to delete the column. Let us now see the syntax of deleting a column from a dataframe.
Syntax: 
 

del df['column_name']

Let us now see few examples:
Example 1: 
 

Python3




# importing the module
import pandas as pd
 
# creating a DataFrame
my_df = {'Name': ['Rutuja', 'Anuja'],
         'ID': [1, 2], 'Age': [20, 19]}
df = pd.DataFrame(my_df)
display("Original DataFrame")
display(df)
 
# deleting a column
del df['Age']
 
display("DataFrame after deletion")
display(df)

Output : 
 

Note the column ‘Age” has been dropped.
Example 2: 
 

Python3




# importing the module
import pandas as pd
 
# creating a DataFrame
my_df = {'Students': ['A', 'B', 'C', 'D'],
         'BMI': [22.7, 18.0, 21.4, 24.1],
         'Religion': ['Hindu', 'Islam',
                      'Christian', 'Sikh']}
df = pd.DataFrame(my_df)
display("Original DataFrame")
display(df)
 
# deleting a column
del df['Religion']
 
display("DataFrame after deletion")
display(df)

Output : 
 

Note that the unnecessary column, ‘Religion’ has been deleted successfully.
 


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