Source: 📖 Python Cookbook ch6.1 p175

Reading CSV data

Use the csv module. For simple csv data, you can read and write using csv.reader and csv.writer. We'll be working with the following csv data:

 Symbol,Price,Date,Time,Change,Volume "AA",39.48,"6/11/2007","9:36am",-0.18,181800 "AIG",71.38,"6/11/2007","9:36am",-0.15,195500 "AXP",62.58,"6/11/2007","9:36am",-0.46,935000 "BA",98.31,"6/11/2007","9:36am",+0.12,104800 "C",53.08,"6/11/2007","9:36am",-0.25,360900 "CAT",78.29,"6/11/2007","9:36am",-0.23,225400

import csv


with open('stocks.csv') as f:
	f_csv = csv.reader(f)	# create reader
	headers = next(f_csv)
	for row in f_csv:
		...	# process row

To avoid confusing indexing, such as row[0] for symbol or row[5] for volume, csv.DictReader can be used which allows us to access the data in each row using the header name of each column as a key.

with open('stocks.csv') as f:
	f_csv = csv.DictReader(f)
	for row in f_csv:
		...	# process row

Using DictReader assumes that there is a header column, which it will automatically consume so next() does not have to be called on f_csv to extract the headers. The data can now be accessed for each row by using header names as dictionary keys, such as row['Symbol'] or row['Volume'].