Introduction to CSV Processing in Python
CSV (Comma-Separated Values) is a widely used file format for storing and exchanging tabular data. It is a simple and lightweight format that can be easily read and written by both humans and machines. In the Python programming language, the built-in csv
module provides a convenient way to work with CSV files, allowing you to read, write, and manipulate CSV data.
Understanding CSV Files
A CSV file is a text file where each line represents a row of data, and the values in each row are separated by a delimiter, typically a comma (,
). The first row of a CSV file often contains the column headers, which describe the data in each column.
Here's an example of a simple CSV file:
Name,Age,City
John,25,New York
Jane,30,Los Angeles
Bob,35,Chicago
In this example, the CSV file has three columns: "Name", "Age", and "City", and three rows of data.
Using the csv
Module in Python
The csv
module in Python provides a set of functions and classes for working with CSV files. The main functions and classes are:
csv.reader()
: Reads a CSV file and returns an iterator that can be used to iterate over the rows.
csv.writer()
: Writes data to a CSV file.
csv.DictReader()
: Reads a CSV file and returns an iterator that can be used to iterate over the rows as dictionaries, where the keys are the column names.
csv.DictWriter()
: Writes data to a CSV file using dictionaries, where the keys are the column names.
Here's an example of how to read a CSV file using the csv.reader()
function:
import csv
with open('data.csv', 'r') as file:
reader = csv.reader(file)
for row in reader:
print(row)
This code will read the contents of the data.csv
file and print each row as a list of values.
By understanding the basics of CSV processing in Python, you can now move on to exploring common errors and implementing robust error handling in your CSV processing workflows.