Skip to content
Novus Examples
csv211 B

CSV with Mixed Null Representations

A CSV where missing values are written seven different ways — empty string, NULL, NA, N/A, null, None, and a dash — across text and numeric columns. A fixture for testing null-detection and coercion in CSV importers.

Preview — first 10 linescsv
id,name,score,joined,notes
1,Ada,91,2025-03-01,ok
2,,NULL,2025-04-11,NA
3,Chen,N/A,,null
4,None,74,2025-06-30,-
5,Priya,,null,
6,NA,88,2025-08-19,n/a
7,Omar,None,2025-09-02,NULL
8,Sofia,67,2025-10-15,-

Specifications

Rows
8
Null Tokens
'', NULL, NA, N/A, null, None, -
Note
missing values written seven different ways

What is a .csv file?

CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.

How to use this file

Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.

Code examples

import pandas as pd

df = pd.read_csv("nulls-and-missing.csv")
print(df.head())
print(df.dtypes)

Generated by generation/data_edgecases.py. Free for any use, no attribution required — license.