In this article, we are going to see how to read CSV files into a list of lists in Python.
Method 1: Using CSV module
- We can read the CSV files into different data structures like a list, a list of tuples, or a list of dictionaries.
- We can use other modules like pandas which are mostly used in ML applications and cover scenarios for importing CSV contents to list with or without headers.
Example 1:
In this example, we are reading a CSV file and converting the string into the list.
Python3
import csv with open('sample.csv', 'r') as read_obj: # Return a reader object which will # iterate over lines in the given csvfile csv_reader = csv.reader(read_obj) # convert string to list list_of_csv = list(csv_reader) print(list_of_csv) |
Output:
[[‘JAN’, 34, 360, 417], [‘FEB’, 31, 342, 391], [‘MAR’, 36, 406, 419], [‘APR’, 34, 396, 461],
[‘MAY’, 36, 420, 472], [‘JUN’, 43, 472, 535], [‘JUL’, 49, 548, 622], [‘AUG’, 50, 559, 606],
[‘SEP’, 40, 463, 508], [‘OCT’, 35, 407, 461], [‘NOV’, 31, 362, 390], [‘DEC’, 33, 405, 432]]
Example 2:
In this example, we are reading a CSV file and iterating over lines in the given CSV.
Python3
import csv with open('example.csv') as csvfile: # Return a reader object which will # iterate over lines in the given csvfile. readCSV = csv.reader(csvfile, delimiter=',') for row in readCSV: print(row) print(row[0]) print(row[0], row[1], row[2],) print("\n") |
Output:
Method 2: Using Pandas
You can use the pandas library for this which has an inbuilt method to convert values to a list. Pandas.values property is used to get a numpy.array and then use the tolist() function to convert that array to list.
Note: For more information refer Read CSV Into List Using Pandas
Python3
# app.py import pandas as pd # Creating Dictionarydict = { 'series': ['Friends', 'Money Heist', 'Marvel'], 'episodes': [200, 50, 45], 'actors': [' David Crane', 'Alvaro', 'Stan Lee']} # Creating Dataframedf = pd.DataFrame(dict)print(df) |
Output:
