Working with CSV Files in Python

CSV (Comma Separated Values) is a common format for tabular data, like what you’d see in spreadsheets or simple databases. Python’s built-in csv module makes it straightforward to read from and write to CSV files without having to manually split strings.

Import the CSV Module

import csv

Reading CSV Files

To read a CSV, you typically:

1. Open the file with open() in text mode ('r' for read).
2. Create a csv.reader object using that file.
3. Loop through the reader to get rows (as lists of values).

Example – Reading a CSV file Assume students.csv contains:

Name,Age,Grade
Alice,14,A
Bob,15,B
Charlie,14,C

file = open('students.csv', 'r')
csv_reader = csv.reader(file)
# If the CSV has a header and we want to skip it:
# header = next(csv_reader)  # uncomment to skip the first line
for row in csv_reader:
    print(row)
file.close()

Output:

['Alice', '14', 'A']
['Bob', '15', 'B']
['Charlie', '14', 'C']

• Each row is a list of strings.
• csv.reader handles splitting at commas and managing quotes.
• Skip the header with next(csv_reader) if needed.

Using csv.DictReader

Returns each row as a dictionary, using the header row as keys:

file = open('students.csv', 'r')
dict_reader = csv.DictReader(file)
for row in dict_reader:
    print(row["Name"], "is", row["Age"], "years old.")
file.close()

Output Example:

Alice is 14 years old.

Writing CSV Files

To write data to CSV:

1. Open the file in write mode.
2. Create a csv.writer object.
3. Use writer.writerow() for single rows or writer.writerows() for multiple rows.

Important: When writing CSV on Windows, pass newline='' to open() to avoid extra blank lines. Example – Writing CSV data:

data = [
    ["Name", "Branch", "Year", "CGPA"],  # header
    ["Nikhil", "COE", "2", "9.0"],
    ["Sanchit", "COE", "2", "9.1"],
    ["Aditya", "IT", "2", "9.3"],
]
csvfile = open('university_records.csv', 'w', newline='')
csv_writer = csv.writer(csvfile)
for row in data:
    csv_writer.writerow(row)
csvfile.close()

# Equivalent code using Write Rows
csvfile = open('university_records.csv', 'w', newline='')
csv_writer = csv.writer(csvfile)
csv_writer.writerows(data)
csvfile.close()

Equivalent using writer.writerows():

csvfile = open('university_records.csv', 'a', newline='')
csv_writer = csv.writer(csvfile)
csv_writer.writerows(data)
csvfile.close()

Using csv.DictWriter

Similar to reading, you can write using dictionaries.

fieldnames = ["Name", "Branch", "Year", "CGPA"]
rows = [
    {"Name": "Nikhil", "Branch": "COE", "Year": "2", "CGPA": "9.0"},
    {"Name": "Sanchit", "Branch": "COE", "Year": "2", "CGPA": "9.1"},
]

csvfile = open('university_records.csv', 'w', newline='')
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()        # write the header row
writer.writerows(rows)      # write all rows from the list of dicts
csvfile.close()

• Each dictionary’s keys match the fieldnames.
• writeheader() writes the header row automatically.

CSV Dialects & Delimiters

By default:

• Separator: comma
• Quoting: automatic when needed
• Dialect: "excel"

If your file uses a different delimiter:

csv_reader = csv.reader(file, delimiter=';')
csv_writer = csv.writer(csvfile, delimiter='t')

Summary:

• Use csv.reader / csv.writer for basic reading/writing.
• Always use newline='' when writing.
• For named access, use DictReader / DictWriter.
• csv handles quoting, newlines, and delimiters automatically.