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Distribution Reference
Every int/float column carries a distribution in its distribution_params. Pick the shape that matches the real-world quantity; pass the listed parameters. All distributions honour min/max clamping and decimals.
Python
{"type": "integer", "distribution": "poisson", "lambda": 4, "min": 0}Continuous#
| Distribution | Params | Use for |
|---|---|---|
normal | mean, std | Symmetric quantities: age, height, test scores. |
lognormal | mu, sigma | Right-skewed money: price, salary, order amount. |
uniform | min, max | Flat ranges: latitude, a 1–5 rating. |
exponential | scale | Wait times, inter-arrival gaps. |
beta | a, b (scaled to min/max) | Bounded proportions, scores in a fixed band. |
gamma | shape, scale | Positive skewed durations, insurance claim sizes. |
Discrete#
| Distribution | Params | Use for |
|---|---|---|
poisson | lambda (alias lam) | Counts per interval: items per order, calls per hour. |
binomial | n, p | Successes out of n trials: conversions, defects. |
Heavy-tailed (power-law)#
For "a few get most, most get very few" — views, followers, wealth, file sizes:
| Distribution | Params | Notes |
|---|---|---|
zipf | a | Discrete power-law; larger a ⇒ steeper tail. |
pareto / power_law | alpha, scale | Continuous heavy tail. |
Python
{"type": "integer", "distribution": "zipf", "a": 2.0, "min": 1} # view counts
{"type": "integer", "distribution": "binomial", "n": 10, "p": 0.3} # successesConditional & correlated shapes#
Distributions describe a single column's marginal. To make columns relate:
- One column switches another's distribution →
depends_on. - Two numeric columns move together → correlations.
- A quantity changes over time → outcome curves (magnitude) or rate curves (proportion).
Parameter aliases#
A couple of names are accepted both ways so hand-written and tool-generated schemas both work:
- Poisson rate:
lambdaorlam. - Zipf shape:
a; Pareto shape:alpha.
In the studio#
The column Inspector auto-suggests a distribution from the column name (e.g. views → power-law, price → log-normal) as a one-click preset, and the Engine params panel exposes the full distribution picker with the relevant shape fields.