Shape · Statistics

Describe

Summarizes each column in one row: count, blanks, mean, standard deviation, min, percentiles and max. A quick first look at a new dataset.

Also known as: Summary statistics, profile

How it works

Columns limits the summary; leave it empty to profile every numeric column. The output has one row per column with count, null_count, mean, std (sample), min, one column per percentile and max. Percentiles are fractions between 0 and 1, 0.25, 0.5, 0.75 by default, and appear as p25, p50, p75. Tick Include non-numeric columns to add text columns too; they get unique, top (the most common value) and freq (its count) while their numeric statistics are NULL, and numeric rows have those three columns NULL.

Inputs and outputs

Settings

{
  columns: string[]
  includeNonNumeric: boolean
  percentiles: number[]
}

Example

First look at a new orders file: leave Columns empty, set Percentiles to 0.05, 0.5, 0.95 to see the tails, and include non-numeric columns to check how many distinct statuses and countries there are.

More in Statistics

• Value Counts — Counts how often each value, or combination of values, appears: one row per distinct value with its count or share.
• Column Profile — Counts the distinct values in each chosen column, as long rows of column, value and count. Useful for spotting typos or dominant categories.
• Correlation Matrix — Shows how strongly each pair of number columns moves together, as a grid of values from −1 to 1.
• Covariance Matrix — Works out the covariance of every pair of number columns, as a grid.
• Linear Regression — Fits a straight-line model of one column from one or more others. Outputs the coefficients, or your rows with predictions and residuals.
• Standardize — Rescales number columns to a common scale: z-score or 0 to 1. Use it before comparing measures in different units.
• Outlier Flag — Adds a true/false column marking rows with unusually high or low values. Rows are kept, so you can filter or review them afterwards.