A python matplotlib implementation of the sinaplot A kind of hybrid between sns.violinplot and sns.stripplot. idea is from Sinaplot R package.

Sinaplot implementation in Python adapted from https://github.com/mparker2/seaborn_sinaplot. Adapted to include a boxplot in the middle of the sinaplot. Difference in implementation: …

A python implementation of the sinaplot using matplotlib and seaborn - mparker2/seaborn_sinaplot

Mar 20, 2024 · Purpose: A sinaplot is used to visualize the distribution of a continuous variable when the data has a high degree of scatter, while a violin plot is used to display the distribution of a continuous variable on a single dimension.

Sinaplot combines the goodness of jittered data points (or strippplot) and the violin plot. By letting the normalized density of points restrict the jitter along the x-axis the plot displays the same contour as a violin plot, but resemble a simple strip chart for small number of data points.

sinaplot# A kernel density estimation plot of the “lincoln” data using the sklearn.neighbors.KernelDensity function and Bokeh harea glyph. Details. Sampledata: bokeh.sampledata.lincoln. Bokeh APIs: figure.harea. More info: …

Python: Python users can produce sina plots with the help of the Plotnine library. R users can generate sina plots through the sina plot package according to this example implementation. # Install and load the sinaplot package. install.packages (“sinaplot” ) …

The sina plot is a data visualization chart suitable for plotting any single variable in a multiclass dataset. It is an enhanced jitter strip chart, where the width of the jitter is controlled by the density distribution of the data within each class. Set of aesthetic mappings created by aes().

There are a number of ways to create sina plots, in particular: The ggplot2 library of the R programming language used together with the ggforce package. [5] The sinaplot library of the R programming language. [6] The plotnine library of the Python programming language. [7]

Using a subset of the blood dataset we compare sinaplot with 5 popular plotting strategies, and show how our package integrates features from these methods to achieve truthful and yet simple representation of multiclass single variable data.