Python Avoid Losing Types When Exporting CSV Data

CSV stores text, so column values need explicit types after import.

How It Works

When you write a CSV row, numbers, dates and booleans are serialized as text. When reading the file, csv.DictReader returns strings even when the column originally held an integer. Decide on a schema, validate incoming values and convert them before doing arithmetic. Empty cells also need an explicit policy.

CSV has no standardized schema or built-in type preservation; document your expected columns and formats.

Step-by-Step Example

import csv
from io import StringIO

buffer = StringIO(newline="")
writer = csv.DictWriter(buffer, fieldnames=["name", "quantity", "in_stock"])
writer.writeheader()
writer.writerow({"name": "Pencils", "quantity": 12, "in_stock": True})
buffer.seek(0)
record = next(csv.DictReader(buffer))
quantity = int(record["quantity"])
in_stock = record["in_stock"].lower() == "true"
print(quantity + 3, in_stock)

Understanding the Example

The expression 'StringIO(newline="")' supplies the value stored as 'buffer'. This value is then used or checked by the later statements.
The expression 'csv.DictWriter(buffer, fieldnames=["name", "quantity", "in_stock"])' supplies the value stored as 'writer'. This value is then used or checked by the later statements.

A successful run of this example prints the following output:

15 True

Where This Fits in a Real Program

In a real import pipeline, parsing is only the first stage. Convert each field to the intended type, reject missing or unexpected values and report which record failed. Keep the original source file unchanged until the normalized data has passed validation and an export has been checked.

Practice: Try It Yourself

Add a second CSV row with an empty quantity and decide whether to reject it or provide a default.

For this exercise, predict the result before running the changed code. Then explain the difference between the original and modified cases using the actual values, not just whether the program completed.

Common Beginner Mistakes

Treating the string "False" as a false Boolean with bool("False"), which actually returns True.
Adding a number to a raw CSV field without converting the field from str.

Key Takeaways

CSV stores text, so column values need explicit types after import.
When you write a CSV row, numbers, dates and booleans are serialized as text.
CSV has no standardized schema or built-in type preservation; document your expected columns and formats.