{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "eeef6f0b-7e42-4193-9b89-721fd3f06ac5",
   "metadata": {},
   "source": [
    "From https://towardsdatascience.com/tooltips-with-pythons-matplotlib-dcd8db758846"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "233af177-7175-4e2c-a486-f3aebf7940fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "635c8457-cba9-4e20-b225-aa9e9d7afb1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import mplcursors\n",
    "import seaborn as sns\n",
    "tips = sns.load_dataset(\"tips\")\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "sns.scatterplot(data=tips, x=\"total_bill\", y=\"tip\", hue=\"smoker\")\n",
    "\n",
    "@mplcursors.cursor(ax, hover=True).connect(\"add\")\n",
    "def on_add(sel):\n",
    "    sel.annotation.set(text=tips.sex[sel.target.index])\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b101c777-00ea-41f5-a76c-ff69973cd276",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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