{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Tooltip\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Tooltip contents\n\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Contents of a tooltip can be controled by the `tooltip` argument.\n\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Add data by giving an array.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import plotly\nimport ptvis\n\n\nelements = list(ptvis.Element) * 2\ntooltip = {\n    \"atomic_number\": [element.value for element in elements],\n    \"is_first\": [True]*len(ptvis.Element) + [False]*len(ptvis.Element),\n}\n\nfig = plotly.graph_objects.Figure()\nptvis.attach_pie_cells(fig, elements, tooltip=tooltip)\n\nplotly.io.show(fig)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Change a position of a default item by giving ``True`` at a desired position.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import plotly\nimport ptvis\n\n\nelements = list(ptvis.Element) * 2\ntooltip = {\n    \"atomic_number\": [element.value for element in elements],\n    \"element\": True,\n}\n\nfig = plotly.graph_objects.Figure()\nptvis.attach_pie_cells(fig, elements, tooltip=tooltip)\n\nplotly.io.show(fig)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Remove a default item by giving ``False``.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import plotly\nimport ptvis\n\n\nelements = list(ptvis.Element) * 2\ntooltip = {\"element\": False}\n\nfig = plotly.graph_objects.Figure()\nptvis.attach_pie_cells(fig, elements, tooltip=tooltip)\n\nplotly.io.show(fig)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Changing labels\n\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "An alternative label can be given by the `labels` argument.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import plotly\nimport ptvis\n\n\nelements = list(ptvis.Element) * 2\n\nfig = plotly.graph_objects.Figure()\nptvis.attach_pie_cells(fig, elements, labels={\"element\": \"symbol\"})\n\nplotly.io.show(fig)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Format of values\n\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "A format of values can be specified by the `formats` argument.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import plotly\nimport ptvis\n\n\nelements = list(ptvis.Element) * 2\ntooltip = {\"atomic_number\": [element.value for element in elements]}\n\nfig = plotly.graph_objects.Figure()\nptvis.attach_pie_cells(\n    fig,\n    elements,\n    tooltip=tooltip,\n    formats={\"atomic_number\": \":.1f\"},\n)\n\nplotly.io.show(fig)"
      ]
    }
  ],
  "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": "3.13.3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}