Writing CSV files in Python

1. Basic CSV Writing with csv.writer

import csv

with open("output.csv", "w", newline="") as file:
    writer = csv.writer(file)
    writer.writerow(["name", "age", "city"])
    writer.writerow(["Alice", 25, "New York"])

Creates a CSV file and writes rows as lists.

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2. Writing Multiple Rows at Once

import csv

data = [
    ["Bob", 30, "London"],
    ["Emma", 28, "Berlin"],
]

with open("people.csv", "w", newline="") as file:
    writer = csv.writer(file)
    writer.writerows(data)

Efficient approach for bulk row insertion.

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3. Writing CSV with Custom Delimiter

import csv

with open("data_pipe.csv", "w", newline="") as file:
    writer = csv.writer(file, delimiter="|")
    writer.writerow(["Name", "Age", "Country"])
    writer.writerow(["John", 35, "India"])

Allows CSV generation beyond comma-separated formatting.

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4. Writing CSV with Quoting

import csv

with open("quotes.csv", "w", newline="") as file:
    writer = csv.writer(file, quoting=csv.QUOTE_ALL)
    writer.writerow(["Alice", "Software Engineer", "New York"])

Ensures consistent quoting of all fields.

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5. Appending Data to Existing CSV

import csv

with open("users.csv", "a", newline="") as file:
    writer = csv.writer(file)
    writer.writerow(["Charlie", 40, "Canada"])

Appends without overwriting existing data.

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6. Writing Dictionaries with DictWriter

import csv

fieldnames = ["name", "age", "city"]

with open("users.csv", "w", newline="") as file:
    writer = csv.DictWriter(file, fieldnames=fieldnames)
    writer.writeheader()
    writer.writerow({"name": "Alice", "age": 25, "city": "Paris"})

Maps keys directly to column headers.

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7. Validating Data Before Writing

import csv

def validate_row(row):
    return all(row)

data = [
    ["John", 28, "Toronto"],
    ["", 35, "Berlin"]
]

with open("validated.csv", "w", newline="") as file:
    writer = csv.writer(file)
    for row in data:
        if validate_row(row):
            writer.writerow(row)

Prevents invalid or incomplete data from being written.

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8. Writing CSV with UTF-8 Encoding

import csv

with open("unicode.csv", "w", encoding="utf-8", newline="") as file:
    writer = csv.writer(file)
    writer.writerow(["Name", "City"])
    writer.writerow(["José", "München"])

Ensures proper handling of international characters.

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9. Generating CSV from List of Dictionaries

import csv

records = [
    {"name": "Alice", "age": 25, "city": "Rome"},
    {"name": "Bob", "age": 30, "city": "Madrid"}
]

with open("records.csv", "w", newline="") as file:
    writer = csv.DictWriter(file, fieldnames=records[0].keys())
    writer.writeheader()
    writer.writerows(records)

Ideal for exporting structured datasets.

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10. Writing CSV Using pandas (Advanced Workflow)

import pandas as pd

data = {
    "name": ["Alice", "Bob"],
    "age": [25, 30],
    "city": ["Paris", "London"]
}

df = pd.DataFrame(data)
df.to_csv("data.csv", index=False)

Pandas simplifies CSV creation in data-intensive applications.

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