Answer: You can use the drop(), pop(), column index, df.loc(), and df.iloc() functions to remove the column from the pandas DataFrame.
Deleting a column from a Pandas DataFrame is important because it helps in cleaning and preparing the data. Let’s explore these functions in detail and learn how they are effective methods to delete a column from a Pandas DataFrame in Python.
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Methods to Delete a Column from a Pandas DataFrame in Python
Python provides various built-in methods to delete a column from a dataframe in pandas. Let’s learn more about these methods with examples:
Method 1: Using drop() Function to Delete a Column from a DataFrame in Python
1. Using the drop() function to delete the column by mentioning the column name
You can use the drop() function by stating the column name when you need to remove a certain column or row using Pandas DataFrame.
Example:
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2. Using the drop() function to delete the column by mentioning the index
You can also use the drop() function to delete the column by mentioning its index, by using Pandas DataFrame.
Example:
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Method 2: Using pop() Function to Delete a Column from a DataFrame in Python
Compared to other functions, pop() is different. While the Pandas pop function takes a column as input and pops it, the pop() function often removes the last element when working with a stack.
Example:
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Method 3: Using dropna() Function to Delete a Column from a DataFrame in Python
Depending on the specified criterion, we can remove a column from a pandas dataframe. The parameters for the dropna() function are a subset, thresh, how=any/all, and axis. In the parameter, how=any/all, ‘any’ will delete a row/column with any null value, and ‘all’ will delete all null values.
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Method 4: Using iloc() Function to Delete a Column from a DataFrame in Python
It is row/column specific, we can delete it based on its index position in Pandas. It is used to delete a range of columns that are respective to their position.
Example:
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Method 5: Using loc() Function to Delete a Column from a DataFrame in Python
If you want to remove the column between the two labeled columns this would be a great choice. We delete the column by mentioning its name. This can be done along with the loc() and drop() functions in Pandas.
Example:
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Conclusion
The above-mentioned functions are used to delete the column in pandas DataFrame and based on your demand the methods can be chosen. Understanding these approaches helps you effectively delete the column from Pandas DataFrame depending on the use cases.
Below are resources that walk you through the basics of Python programming.
Getting the index of a row in a pandas apply function – A simple guide to getting the index during apply() usage in pandas.
How to select rows from a DataFrame based on column values – Understand conditional row selection in pandas DataFrames.
Check whether a file exists without exceptions – Understand non-exception approaches for file existence checks.
Converting strings to datetime objects – Use Python to change strings into valid datetime values.
Checking if a string is an integer or float – Use Python to verify if a string contains a number or not.
Delete an element from a dictionary – Python techniques for removing specific dictionary keys.
Getting the class name of an instance – Discover which class an instance belongs to in Python.
Changing column type in pandas – How to use astype() to change pandas column data types.