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Numbers

Random Percentage List Generator

Used by developers, writers, and creators worldwide.

A random percentage list generator lets you produce batches of realistic percentage values in seconds — no scripting required. Set your min and max to scope the range (60–95 for pass rates, 0.5–4.5 for interest simulations), choose decimal precision from zero to four places, and set a count up to whatever your project needs. The output is ready to copy straight into a spreadsheet, seed file, or design tool. Developers use it to populate UI components before a backend exists — progress bars, KPI cards, and completion rings all need varied numbers to expose real layout issues. A hardcoded 75% hides problems that 3% and 99.8% would catch immediately. Data and design teams reach for it equally.

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How to use

  1. Choose your options above
  2. Click Generate
  3. Copy your result

Detailed instructions

  1. Set the count field to how many percentage values you need in the output list.
  2. Enter your minimum and maximum values to define the range your percentages will fall within.
  3. Choose decimal places: 0 for whole numbers, 1–2 for general use, 3–4 for high-precision data.
  4. Click Generate to produce the list, then copy the output directly into your project or spreadsheet.

Use Cases

  • •Populating Figma dashboard mockups with varied KPI completion rates before any real data exists
  • •Testing React progress bar components at edge values like 1.5% and 98.7% to catch layout overflow bugs
  • •Generating 200 dummy discount rates for seeding a WooCommerce staging database
  • •Creating a synthetic student score dataset with two decimal places for a statistics course exercise
  • •Simulating quarterly revenue growth rates between 80% and 140% for a financial model prototype

Tips

  • →For realistic survey data, use a range of 30–90 with one decimal — true extremes near 0 or 100 are statistically rare.
  • →Set decimals to 0 when testing UI components; fractional labels often break fixed-width designs at small font sizes.
  • →Generate two separate lists — one with min 0–10 and one with 90–100 — to specifically test edge-case rendering.
  • →Match decimal precision to your target system: SQL float columns, JSON APIs, and CSV imports each have format expectations.
  • →Use a count of exactly 12 or 24 when seeding monthly or hourly chart placeholders to avoid obvious data gaps.
  • →If values feel too uniform, run the generator twice and interleave both lists to break any perceived pattern.

FAQ

can I generate percentages above 100 for things like growth rates

Yes — the max field accepts any number, so you can generate figures like 120% or 250% for overcapacity or growth-rate scenarios. If you need strict proportions, keep the default 0–100 range. For open-ended rates, just raise the max to whatever ceiling fits your data.

how many decimal places should I use for financial vs UI data

Two decimal places is standard for financial figures like interest rates and discount percentages. Use zero decimals for UI labels where 43.0% looks awkward, and three or four decimals when feeding data into statistical models where rounding error compounds across large datasets.

why do my generated percentages keep repeating with a narrow range and zero decimals

With zero decimals and a tight range — say, 80 to 85 — there are only six possible distinct integers, so repetition is inevitable in a longer list. Widen the range, add one or two decimal places to expand the value pool, or reduce the count to match the number of unique values available.