{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
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Title
Distribution Element
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Dependencies
Plotly
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Backends
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 ``Distribution`` Element is a quick way of visualize the distribution of some data visualizing it as a a histogram or kernel density estimate. Unlike the ``Histogram`` Element ``Distribution`` wraps the raw data rather than representing the already binned data.\n", "\n", "Here we will wrap a simple numpy array containing 1000 samples of a normal distribution." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "hv.Distribution(np.random.randn(1000))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "``Distribution`` Elements like all other Elements can be overlaid allowing us to compare two distributions:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "hv.Distribution(np.random.randn(1000), label='#1') * hv.Distribution(np.random.randn(1000)+2, label='#2')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For full documentation and the available style and plot options, use ``hv.help(hv.Distribution).``" ] } ], "metadata": { "language_info": { "name": "python", "pygments_lexer": "ipython3" } }, "nbformat": 4, "nbformat_minor": 1 }