Distributional Charts

This shows examples of DistPlot, KernelDensity and PieChart.

Distributional Plots

Distribution Plot

This makes a historgram, box and whiskers and rugplot. So you can see differences in distribution for a variable between different groups of observations. Note at the bottom there is a slider for changing the number of bins in the histogram. See here for DistPlot examples

Filters

segment:

region:

product:

Plot Attributes

Select variable: Group by:

Number of bins: 30

Data: sales_data.parquet

Kernel Density Plot

This shows kernel density estimates for a variable seperated by groups in the observations. It also has faceting available (unlike DistPlot). There is a slider at the bottom for controlling the bandwidth of the kernel density estimate. See here for KernelDensity examples

Filters

segment:

region:

product:

Plot Attributes

Select variable: Group by:

Faceting

Facet 1:

Facet 2:

Bandwidth: auto (0 = auto, max ≈ 7438.1)

Data: sales_data.parquet

Pie Chart

This gives piecharts. Note that piecharts are generally pretty bad (google it to see more on this) but up to you if you like them. There is faceting available, filtering and you can change the grouping variable and the numeric variable being aggregated over to determine pie width. See here for PieChart examples

Plot Attributes

Slice size:

Slice grouping:

Data: sales_data.parquet

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