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DistPlot Examples

This page demonstrates distribution visualization combining histogram, box plot, and rug plot.

Single distribution: Basic histogram + box plot + rug plot
Group comparison: Compare distributions across multiple groups
Interactive filters: Multi-select dropdown controls for categorical and numeric variables
Customization: Toggle histogram, box, and rug plot visibility

Use multi-select dropdown controls to filter and explore the data!

Simple Distribution Plot

Basic distribution showing histogram, box plot, and rug plot for a normal distribution

Plot Attributes

Axes

X: value

X Transform:

Aspect Ratio: 0.6 (0.25 - 2.5)

Number of bins: 30

Data: df1

Treatment Effect Comparison

Compare distributions across different treatment groups using color_cols

Plot Attributes

Axes

X: value

X Transform:

Aspect Ratio: 0.6 (0.25 - 2.5)

Number of bins: 30

Data: df2

Score Distribution with Interactive Filters

Use age and department filters to filter data dynamically

Filters

department:

age: 18 - 80

Plot Attributes

Axes

X: score

X Transform:

Aspect Ratio: 0.6 (0.25 - 2.5)

Number of bins: 40

Data: df3

Multi-Variable Distribution with Dropdowns

Select different variables and grouping columns using the dropdowns above. This example demonstrates the full flexibility of the DistPlot.

Plot Attributes

Group by:

Axes

X Transform:

Aspect Ratio: 0.6 (0.25 - 2.5)

Number of bins: 30

Data: df4

Customized DistPlot - Longitudinal Study

Demonstrates customization options: rug plot hidden, increased box opacity, custom bin count

Plot Attributes

Axes

X: measurement

X Transform:

Aspect Ratio: 0.6 (0.25 - 2.5)

Number of bins: 30

Data: df5

Date/Time Filtering Test

This example tests continuous range filters for Date, DateTime, ZonedDateTime, and Time columns. All temporal types use range sliders for intuitive filtering. Try adjusting the range sliders to filter the data!

Filters

time_col: 00:10:00 - 16:40:00

datetime_col: 2024-01-01T01:00:00 - 2024-01-05T04:00:00

date_col: 2024-01-02 - 2024-04-10

zoneddatetime_col: 2024-01-01T01:00:00 - 2024-01-05T04:00:00

Plot Attributes

Axes

X: value

X Transform:

Aspect Ratio: 0.6 (0.25 - 2.5)

Number of bins: 30

Data: df6

Date/Time Range Slider Filters Test

This example tests range slider filters for Date, DateTime, ZonedDateTime, and Time columns. All temporal types use range sliders regardless of the number of unique values, providing a consistent filtering experience.

Filters

datetime_cat: 2024-01-01T02:00:00 - 2024-01-01T20:00:00

zoneddatetime_cat: 2024-01-01T02:00:00 - 2024-01-01T20:00:00

date_cat: 2024-01-02 - 2024-01-11

time_cat: 01:00:00 - 10:00:00

Plot Attributes

Axes

X: value

X Transform:

Aspect Ratio: 0.6 (0.25 - 2.5)

Number of bins: 30

Data: df7

Struct Data Source Example

This distribution plot uses data from a struct containing multiple DataFrames. The SurveyData struct holds both responses and demographics. Charts reference the responses DataFrame using Symbol("survey.responses").

Survey Results from Struct Data Source

This example shows how to use a struct as a data source. The SurveyData struct contains responses and demographics DataFrames. Access struct fields via dot notation.

Plot Attributes

Group by:

Axes

X Transform:

Aspect Ratio: 0.6 (0.25 - 2.5)

Number of bins: 30

Data: survey.responses

Key Features Summary

Three-in-one visualization: Histogram, box plot, and rug plot combined
Group comparison: Overlay distributions for different groups with color coding
Interactive filtering: Multi-select dropdown filters for both numeric and categorical columns
Customization options: Control visibility and appearance of each component
Statistical insight: See shape, central tendency, spread, and outliers at once

Tip: The rug plot (tick marks at the bottom) shows individual data points!

This page was created using JSPlots.jl v0.4.0.