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:
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.