What placeholder value does each column type produce?

Number columns get sequential integers starting at 1. Boolean columns alternate true/false starting with true. Date columns start at your chosen start date and increment by one day per row. Text columns get the column name plus a row number, e.g. "City 1", "City 2".

Is this the same as Empty CSV Creator?

No, Empty CSV Creator only writes a header row with zero data. This tool fills in a full, typed placeholder dataset for every row you request.

Why does the date column need a start date instead of just using today?

Using an explicit start date keeps the output fully deterministic and reproducible, generating the same input twice always produces the same CSV, rather than silently shifting with whatever day you happen to run it.

Is there a limit on rows or columns?

Yes, generation is capped at 200,000 total cells (rows × columns) and 100 columns, both to keep the browser tab responsive while generating and to keep the output manageable to review.

Custom CSV Creator - Build a CSV File with Typed Columns Online

Overview

Introduction

Sometimes an empty template or purely random bulk data isn't quite right, you know the shape of the data you need (a name column, a signup date, an "active" flag) and want a realistic-looking, ready-to-use CSV without typing rows by hand.

Custom CSV Creator is the flagship "build a CSV from scratch" tool in this category: define your columns and their types, choose a row count, and get a full, correctly-typed placeholder dataset instantly.

What Is Custom CSV Creator?

A CSV builder that lets you define an arbitrary number of columns, each with a name and one of four types (text, number, boolean, date), then fills in a chosen number of rows with plausible values matching each column's type.

Unlike Empty CSV Creator (header only) or Large CSV Generator (single value style across all columns, aimed at load testing), this tool's placeholder values are type-aware and vary per column definition, making the output closer to what a real dataset with that shape would look like.

How Custom CSV Creator Works

Each column definition (name + type) is validated, then for every row index, a placeholder value is generated according to that column's type: sequential numbers, alternating booleans, incrementing dates from your chosen start date, or a short labeled text string.

The completed grid, header row plus every generated data row, is serialized with the shared RFC 4180-aware CSV writer, so any generated value that happens to need quoting (unlikely, but possible for text columns) is escaped correctly.

When To Use Custom CSV Creator

Use this when you're building or testing something that consumes a CSV with a specific column shape (a database import, a reporting script, a spreadsheet template) and want a realistic-looking, correctly-typed sample file without writing rows by hand.

It's also useful for quickly prototyping what a dataset with a given schema would look like before real data exists.

Often used alongside Empty CSV Creator, Large CSV Generator and CSV Viewer.

Features

Advantages

Placeholder values are type-aware, numbers, booleans, and dates all look like what you'd expect from that type, not generic blanks or random junk.
Fully deterministic: the same column definitions, row count, and start date always produce the exact same output.
Supports an arbitrary number of columns with independent types, closer to a real schema than a single-value-style generator.

Limitations

Text placeholder values are simple "ColumnName N" strings, not realistic names, addresses, or other real-world text, use the `random` category's generators if you need that.
Capped at 200,000 total cells and 100 columns to keep generation fast and the browser tab responsive.

Examples

A 3-column, 3-row CSV

Input

columns: [{name: "id", type: "number"}, {name: "active", type: "boolean"}, {name: "signup_date", type: "date"}], rows: 3, startDate: "2024-01-01"

Output

id,active,signup_date
1,true,2024-01-01
2,false,2024-01-02
3,true,2024-01-03

The number column counts up from 1, the boolean column alternates starting true, and the date column increments by one day per row from the start date.

Best Practices & Notes

Best Practices

Pick a start date that's meaningful for your test scenario if the date column's exact values matter downstream.
Give columns descriptive names, they double as the prefix for text-column placeholder values, e.g. "City 1", "City 2".
Start with a small row count to sanity-check the column shape before generating a large file.

Developer Notes

Each column's placeholder generator is a small pure switch on `column.type`, keeping the row-building loop O(rows × columns) with no per-cell randomness for number/boolean/date (only sequential math), so output is fully reproducible; the start date is threaded through explicitly rather than read from `Date.now()` inside the generator, avoiding any dependency on when the tool happens to run.

Custom CSV Creator Use Cases

Prototyping what a dataset with a specific column schema would look like before real data exists
Generating a realistic-shaped fixture file for a database import script or reporting pipeline test
Building a quick sample CSV to demo a spreadsheet template's expected column types

Common Mistakes

Expecting text-column placeholders to look like realistic names or addresses, they're simple labeled placeholders by design.
Forgetting to set a start date before generating date columns and being confused by the default.

Tips

Combine multiple column types in one definition to mirror a real schema, e.g. a number ID, a boolean flag, and a date together.
Feed the output into CSV Viewer afterward to quickly eyeball the generated shape in a table.

Custom CSV Creator