Synthetic Time Series Generator

Why this synthetic time series generator?

Trend, seasonality, and noise components are configurable.
Inject missing values and outliers for robust testing.
Preview a line chart plus first 20 rows.
Export CSV/JSON and share settings safely.

Components

Trend: linear slope per step.
Seasonality: sine cycles or day-of-week pattern.
Noise: Gaussian or AR(1).
Quality: missing values + outlier spikes.

Quick presets

Start from common time-series shapes.

Generate

Configure index, signal, and quality, then generate data.

Preset

Index settings

Start (ISO) Frequency

Points Decimals

Signal settings

Base

Enable trend

Slope per step

Enable seasonality

Seasonality type Amplitude

Cycle

Noise

Noise type Sigma

Quality

Missing rate (0..1) Outlier rate (0..1)

Missing blocks (startIndex,length per line)

Outlier mode Magnitude Direction

Output

Format RNG

Preview

Chart shows the first 200 points; table shows the first 20 rows.

Timestamp	Value

Output

Copy or download the full output.

FAQ

What time series can I generate?

Combine trend, seasonality, noise, missing values, and outliers to create synthetic series.

How are missing values and outliers injected?

Missing values are set to null (CSV empty). Outliers are injected by rate and mode.

What is seeded mode?

Seeded mode makes results reproducible, but it is not secure.

CSV or JSON?

CSV is compact for spreadsheets; JSON keeps nulls and is API-friendly.

Synthetic Time Series Generator (trend/seasonality/noise)

Why this synthetic time series generator?

Components

Quick presets