{ "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", "We can change the noun, verb, and conjunction used in the popup text such that it is relevant for our visualisation. We can also remove them entirely and display names only.\n", "\n", "The default looks like this:\n", "\n", "

\"Modified

\n", "\n", "An example modification looks like this:\n", "\n", "

\"Modified

\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, 5, 6, 4, 7, 4],\n", " [5, 0, 5, 4, 6, 5],\n", " [6, 5, 0, 4, 5, 5],\n", " [4, 4, 4, 0, 5, 5],\n", " [7, 6, 5, 5, 0, 4],\n", " [4, 5, 5, 5, 4, 0],\n", "]\n", "\n", "names = [\"Action\", \"Adventure\", \"Comedy\", \"Drama\", \"Fantasy\", \"Thriller\"]" ] }, { "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": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ActionAdventureComedyDramaFantasyThriller
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" ], "text/plain": [ " Action Adventure Comedy Drama Fantasy Thriller\n", "Action 0 5 6 4 7 4\n", "Adventure 5 0 5 4 6 5\n", "Comedy 6 5 0 4 5 5\n", "Drama 4 4 4 0 5 5\n", "Fantasy 7 6 5 5 0 4\n", "Thriller 4 5 5 5 4 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": [ "## Conjunction, verb, and noun\n", "\n", "We can modify the popup text template with the `conjunction`, `verb`, and `noun` parameters.\n", "\n", "Be sure to interact with the visualisation to see what the default settings can do!
" ] }, { "cell_type": "code", "execution_count": 4, "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", "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Chord(matrix, names, colors=\"turbo\",\n", " conjunction=\"&\", verb=\"appear together in\", noun=\"cases\").show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Showing names only" ] }, { "cell_type": "code", "execution_count": 9, "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", "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Chord(matrix, names, colors=\"cool\",\n", " popup_names_only=True).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 (ipykernel)", "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 }