randarium
Numbers

Numeric Series Generator

Create seeded numeric series for charts, fixtures, and demonstrations.

Also known as: number sequence · test series

seeded

Output

No output yet — set your options and hit .
About this tool, tips & examples

What it does

The Numeric Series Generator produces sequences that trend: pick a start value and a step, add optional noise, and get up to 10,000 points of reproducible series data at a chosen precision. It’s the quickest source of chart-shaped numbers — a clean line, a noisy trend, or anything in between.

Common use cases

  • Chart fixtures — line and area charts need trending data; this generates it in one step, exportable as CSV or JSON.
  • Regression testing — a known linear signal plus controlled noise is the ideal test input for trend-fitting code (you know the right answer).
  • Dashboard demos — plausible KPIs-over-time without waiting for real metrics.
  • Classroom examples — slope, intercept, and noise as three knobs students can turn.

Settings

  • Points — 1 to 10,000 values.
  • Start / Step — the line’s intercept and slope; step 0 gives a flat baseline, negative steps trend down.
  • Noise — the amplitude of random jitter added to each point; 0 gives a perfectly clean series.
  • Decimal places — 0 to 10.
  • Seed — identical seed + settings = identical series, so chart snapshots and regression tests stay stable.

Privacy note

Series are computed locally in your browser and never uploaded. The numbers are synthetic — a mathematical construction, not measurements.

FAQ

How do I make realistic-looking metrics? Start near your metric’s typical value, use a small step for gradual growth, and add noise around 5–10% of the value. Instant “daily active users.”

Can I generate a flat noisy signal? Yes — step 0 with noise on gives fluctuation around a constant baseline, the classic “is this alert threshold right?” test input.

Need wandering instead of trending? Random Walk and Brownian Motion generate drift-free wandering series; Time Series (in the data section) adds seasonality patterns.