{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
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Title
Violin Element
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Dependencies
Plotly
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Backends
Bokeh
Matplotlib
Plotly
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" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import holoviews as hv\n", "hv.extension('plotly')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A ``Violin`` element is used to visualise the distribution of a dataset by displaying its probability density. It is very similar to the ``BoxWhisker`` element but provides a more faithful representation even for bi- or multimodal data. The probability density is shown by the area akin to a vertical and mirrored ``Distribution`` element. The thick black bar in the centre represents the interquartile range, the thin black line extended from it represents the 95% confidence intervals, and the white dot is the median.\n", "\n", "The data of a ``Violin`` Element may have any number of key dimensions representing the grouping of the value dimension and a single value dimensions representing the distribution of values within each group. See the [Tabular Datasets](../../../user_guide/08-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays.\n", "\n", "In the simplest case a ``Violin`` can be used to display a single distribution of values, such as a NumPy array of normally distributed values:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "np.random.seed(37)\n", "violin = hv.Violin(np.random.randn(100), vdims='Value')\n", "violin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The ``Violin`` element is particularly useful to compare multiple distribution across different categories. As a simple example we can create a dataset of values with randomly assigned Group and Category values and compare the distributions." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "groups = [chr(65+g) for g in np.random.randint(0, 3, 200)]\n", "violin = hv.Violin((groups, np.random.randint(0, 5, 200), np.random.randn(200)),\n", " ['Group', 'Category'], 'Value')\n", "\n", "violin.opts(height=400, width=600)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For full documentation and the available style and plot options, use ``hv.help(hv.Violin).``" ] } ], "metadata": { "language_info": { "name": "python", "pygments_lexer": "ipython3" } }, "nbformat": 4, "nbformat_minor": 2 }