A CSV (Comma Separated Values) is a simple file format, used to store data in a tabular format. CSV file stores tabular data (numbers and text) in plain text. Each line of the file is a data record. Each record consists of one or more fields, separated by commas. The use of the comma as a field separator is the source of the name for this file format.
There are various methods to save lists to CSV which we will see in this article.
Method 1 : Using CSV Module
import csv # field names fields = ['Name', 'Branch', 'Year', 'CGPA'] # data rows of csv file rows = [ ['Nikhil', 'COE', '2', '9.0'], ['Sanchit', 'COE', '2', '9.1'], ['Aditya', 'IT', '2', '9.3'], ['Sagar', 'SE', '1', '9.5'], ['Prateek', 'MCE', '3', '7.8'], ['Sahil', 'EP', '2', '9.1']] with open('GFG', 'w') as f: # using csv.writer method from CSV package write = csv.writer(f) write.writerow(fields) write.writerows(rows) |
Output:
Method 2 : Using Pandas
# importing pandas as pd import pandas as pd # list of name, degree, score nme = ["aparna", "pankaj", "sudhir", "Geeku"] deg = ["MBA", "BCA", "M.Tech", "MBA"] scr = [90, 40, 80, 98] # dictionary of lists dict = {'name': nme, 'degree': deg, 'score': scr} df = pd.DataFrame(dict) # saving the dataframe df.to_csv('GFG.csv') |
Output:
Method 3 : Using Numpy
import numpy as np # data rows of csv file rows = [ ['Nikhil', 'COE', '2', '9.0'], ['Sanchit', 'COE', '2', '9.1'], ['Aditya', 'IT', '2', '9.3'], ['Sagar', 'SE', '1', '9.5'], ['Prateek', 'MCE', '3', '7.8'], ['Sahil', 'EP', '2', '9.1']] # using the savetxt # from the numpy module np.savetxt("GFG.csv", rows, delimiter =", ", fmt ='% s') |
Output:
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