Delete a CSV Column in Python

The comma-separated values ​​(CSV) file is a delimited text file that uses commas for individual values. Each line of the file is a data record in CSV. This format used for tabular data, rows, and columns, exactly like a spreadsheet. The CSV file stores data in rows and the values ​​in each row are separated with a comma(separator), also known as a delimiter.

There are 2 ways to remove a column entirely from a CSV in python. Let us now focus on the techniques :

1. With pandas library — drop() or pop()
2. Without pandas library

Here, a simple CSV file is used i.e;input.csv

Method 1: Using pandas library

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas consist of a drop function that is used in removing rows or columns from the CSV files. Pandas Pop() method is common in most of the data structures but the pop() method is a little different from the rest. In a stack, pop doesn’t require any parameters, it pops the last element every time. But the pandas pop method can take input of a column from a data frame and pop that directly.

Example 1: Using drop()

data.drop( labels=None, axis=0, index=None, columns=None, level=None, inplace=False,errors='raise')

1. Import Pandas
2. Read CSV File
3. Use drop() function for removing or deleting rows or columns from the CSV files
4. Print Data

# import pandas with shortcut 'pd'
import pandas as pd  

# read_csv function which is used to read the required CSV file
data = pd.read_csv('input.csv')

# display 
print("Original 'input.csv' CSV Data: \n")
print(data)

# drop function which is used in removing or deleting rows or columns from the CSV files
data.drop('year', inplace=True, axis=1)

# display 
print("\nCSV Data after deleting the column 'year':\n")
print(data)

Output:

Example 2: Using pop()

We can use the panda pop () method to remove columns from CSV by naming the column as an argument.

data.pop('column-name')

1. Import Pandas
2. Read CSV File
3. Use pop() function for removing or deleting rows or columns from the CSV files
4. Print Data

# import pandas with shortcut 'pd'
import pandas as pd

# read_csv function which is used to read the required CSV file
data = pd.read_csv('input.csv')

# display
print("Original 'input.csv' CSV Data: \n")
print(data)

# pop function which is used in removing or deleting columns from the CSV files
data.pop('year')

# display
print("\nCSV Data after deleting the column 'year':\n")
print(data)

Output:

Method 2: Using CSV library

Example 3: Using CSV read and write

1. Open Input CSV file as source
2. Read Source CSV File
3. Open Output CSV File as a result
4. Put source CSV data in result CSV using indexes

# import csv
import csv

# open input CSV file as source
# open output CSV file as result
with open("input.csv", "r") as source:
    reader = csv.reader(source)
    
    with open("output.csv", "w") as result:
        writer = csv.writer(result)
        for r in reader:
          
            # Use CSV Index to remove a column from CSV
            #r[3] = r['year']
            writer.writerow((r[0], r[1], r[2], r[4], r[5]))

Output: