{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dash import Dash, html, dcc, callback, Output, Input\n",
    "import plotly.express as px\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder_unfiltered.csv')\n",
    "\n",
    "app = Dash(__name__)\n",
    "\n",
    "app.layout = html.Div([\n",
    "    html.H1(children='Dash Test App', style={'textAlign':'center'}),\n",
    "    dcc.Dropdown(df.country.unique(), 'Canada', id='dropdown-selection'),\n",
    "    dcc.Graph(id='graph-content')\n",
    "])\n",
    "\n",
    "@callback(\n",
    "    Output('graph-content', 'figure'),\n",
    "    Input('dropdown-selection', 'value')\n",
    ")\n",
    "def update_graph(value):\n",
    "    dff = df[df.country==value]\n",
    "    return px.line(dff, x='year', y='pop')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "app.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}