Extracting specific columns from pandas.dataframe

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by vsasikalabe dot icon Updated: Feb 26, 2023

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Here we are using a CSV file to extract the specific column. We have to read the data (information) from the CSV file. We can tell read_csv() to only import those columns by specifying columns by their index number (starting at 0) as a list to the usecols parameter. In Pandas, we can use double square brackets to select multiple columns from a data frame [[]]. To read a specific column from a CSV file, read_csv() is used. Call pd. read_csv(file_name, usecols=cols_list) with file_name as the name of the CSV file to read a CSV file. If you have a DataFrame, you can use square brackets or other advanced methods such as loc and iloc to access or select a specific few rows/columns from that DataFrame. 

Use square brackets [] with the column name to select a single column. When we create a Data Frame, columns contain different fields containing their particular values. We can also do certain operations on both row & column values. We can copy some specific columns of an old Data Frame in pandas. This is an easy task in pandas. 

We need to import the pandas' package first to work with pandas. Below is the syntax: 

import pandas as pd 

While processing data multiple times, extracting specific columns and storing them in a new data frame is important. The simplest way to extract columns is to select the columns from the original DataFrame using the [] operator and then copy it using the pandas.DataFrame.copy() function. 

Here is an example of how to extract a specific column from Pandas Dataframe: