Descriptive statistics

Summarises one or more variables — central tendency, spread, distribution shape — and optionally produces frequency tables, normality tests, and a range of plots.

When to use it

To describe your sample before (or alongside) inferential tests: means and standard deviations for numeric variables, counts for categories, and figures that show each variable’s distribution.

Inputs

  • Variables — the columns to summarise. Numeric and ordinal columns get a quantitative summary; nominal columns get frequency tables and category charts.

  • Grouping (optional) — a categorical column to split every summary by group.

Options

Tables

Extended statistics adds skewness, kurtosis, quartiles, and more to the basic N / mean / SD / median. Frequency table lists category counts (for categorical variables, split by group when grouping is set). Normality test runs Shapiro–Wilk, Kolmogorov–Smirnov, or Anderson–Darling, with optional verbal indicators of normality.

Plots

Distribution (histogram, with an optional KDE smoothing curve and control over bin width), Box plot (optionally marking outliers), Q–Q plot, Frequency bars, and Pie chart. Ordinal variables can also get a pie chart in their defined order.

Verbal output

Two independent controls. Verbal indicators in tables adds in-table verbal columns (for example a Normal? conclusion in the normality table). Verbal report is a dropdown that sets how much written prose is added — the outlier report, normality summary, and grouped-frequency summary: None, Key findings / Significant only (in the normality summary, only the non-normal variables), or Full (every variable).

Other

Number columns for compact wide tables.

Output

  • A numeric summary table (per group when grouping is on).

  • An outlier report beneath the summary (when the plain-language summary is on), naming each outlier and listing their IDs for easy follow-up.

  • A normality table (if requested).

  • Frequency tables and the requested plots.

Notes

  • Ordinal columns are scored numerically for the quantitative summary but keep their labels and order in frequency tables and pie charts.

  • Pie-chart settings include a Colors palette (Auto plus matplotlib colormaps), Radial labels (rotate each label along its slice), and independent Show % / Show counts toggles — a bare count (no %) is shown as a plain number rather than in parentheses.

  • Bin-width and KDE controls only apply when the distribution plot is shown.