{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Preamble" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from plotapi import Chord\n", "\n", "Chord.set_license(\"your username\", \"your license key\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction\n", "\n", "It's often necessary to label either side of our bipartite Chord diagrams - Plotapi makes this easy.\n", "\n", "As we can see, we have set our license details in the preamble with `Chord.set_license()`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Dataset" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Chord expects a list of names (`list[str]`) and a co-occurence matrix (`list[list[float]]`) as input." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "matrix = [\n", " [0, 0, 0, 1, 4, 1],\n", " [0, 0, 0, 1, 3, 2],\n", " [0, 0, 0, 1, 2, 2],\n", " [1, 1, 1, 0, 0, 0],\n", " [4, 3, 2, 0, 0, 0],\n", " [1, 2, 2, 0, 0, 0],\n", "]\n", "\n", "names = [\"Right 1\", \"Right 2\", \"Right 3\", \"Left 3\", \"Left 2\", \"Left 1\"]\n", "colors = [\"#7400B8\", \"#5E60CE\", \"#5684D6\", \"#56CFE1\", \"#64DFDF\", \"#80FFDB\"]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It may look more clear if we present this as a table with the columns and indices labelled. This is entirely optional." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Right 1 Right 2 Right 3 Left 3 Left 2 Left 1\n", "Right 1 0 0 0 1 4 1\n", "Right 2 0 0 0 1 3 2\n", "Right 3 0 0 0 1 2 2\n", "Left 3 1 1 1 0 0 0\n", "Left 2 4 3 2 0 0 0\n", "Left 1 1 2 2 0 0 0" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "pd.DataFrame(matrix, columns=names, index=names)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Visualisation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To label both sides of the bipartite Chord diagram, we can set the `bipartite_left_label` and `bipartite_right_label`.\n", "\n", "Here we're using `.show()` which outputs to a Jupyter Notebook cell, however, we may want to output to a HTML file with `.to_html()` instead. More on the different output methods later!\n", "\n", "Be sure to interact with the visualisation to see what the default settings can do!\n", "
" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "Plotapi - Chord Diagram\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
\n", " \n", " \n", " \n", "\n", "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Chord(matrix, names, colors=colors, bipartite=True, bipartite_idx=3,\n", " bipartite_left_label=\"Left Side\", \n", " bipartite_right_label=\"Right Side\").show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can do so much more than what's presented in this example, and we'll cover this in later sections. If you want to see the full list of growing features, check out the Plotapi Documentation. and the Plotapi Gallery." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.1" } }, "nbformat": 4, "nbformat_minor": 4 }