Leaflet Example DASH.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import leafmap.plotlymap as leafmap\n",
    "from jupyter_dash import JupyterDash\n",
    "from dash import Dash, html,dcc,Input, Output\n",
    "#import json\n",
    "#import httpx\n",
    "\n",
    "import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "from ipywidgets import widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = leafmap.Map()\n",
    "m.add_basemap(\"Stamen.Terrain\")\n",
    "\n",
    "m.add_controls\n",
    "#m.add_cog_layer(url=url,colormap_name =\"viridis\" )\n",
    "m.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7615dd527b2a4005a4f63d1359f9de6b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(Checkbox(value=True, description='Date: '), IntSlider(value=1, continuous_update…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\site-packages\\flask\\app.py:1523\u001b[0m, in \u001b[0;36mFlask.full_dispatch_request\u001b[1;34m(self=<Flask '__main__'>)\u001b[0m\n",
      "\u001b[0;32m   1521\u001b[0m     rv \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpreprocess_request()\n",
      "\u001b[0;32m   1522\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m rv \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "\u001b[1;32m-> 1523\u001b[0m         rv \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdispatch_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "        rv \u001b[1;34m= None\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mself \u001b[1;34m= <Flask '__main__'>\u001b[0m\n",
      "\u001b[0;32m   1524\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "\u001b[0;32m   1525\u001b[0m     rv \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_user_exception(e)\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\site-packages\\flask\\app.py:1509\u001b[0m, in \u001b[0;36mFlask.dispatch_request\u001b[1;34m(self=<Flask '__main__'>)\u001b[0m\n",
      "\u001b[0;32m   1507\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmake_default_options_response()\n",
      "\u001b[0;32m   1508\u001b[0m \u001b[38;5;66;03m# otherwise dispatch to the handler for that endpoint\u001b[39;00m\n",
      "\u001b[1;32m-> 1509\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mensure_sync(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mview_functions[rule\u001b[38;5;241m.\u001b[39mendpoint])(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mreq\u001b[38;5;241m.\u001b[39mview_args)\n",
      "        req \u001b[1;34m= <Request 'http://127.0.0.1:8050/_dash-layout' [GET]>\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mrule \u001b[1;34m= <Rule '/_dash-layout' (HEAD, OPTIONS, GET) -> /_dash-layout>\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mself.view_functions[rule.endpoint] \u001b[1;34m= <bound method Dash.serve_layout of <jupyter_dash.jupyter_app.JupyterDash object at 0x000001AA1B4664F0>>\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mreq.view_args \u001b[1;34m= {}\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mself \u001b[1;34m= <Flask '__main__'>\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mself.view_functions \u001b[1;34m= {'static': <function Flask.__init__.<locals>.<lambda> at 0x000001AA10B8AAF0>, '_dash_assets.static': <bound method Scaffold.send_static_file of <Blueprint '_dash_assets'>>, '/_dash-component-suites/<string:package_name>/<path:fingerprinted_path>': <bound method Dash.serve_component_suites of <jupyter_dash.jupyter_app.JupyterDash object at 0x000001AA1B4664F0>>, '/_dash-layout': <bound method Dash.serve_layout of <jupyter_dash.jupyter_app.JupyterDash object at 0x000001AA1B4664F0>>, '/_dash-dependencies': <bound method Dash.dependencies of <jupyter_dash.jupyter_app.JupyterDash object at 0x000001AA1B4664F0>>, '/_dash-update-component': <bound method Dash.dispatch of <jupyter_dash.jupyter_app.JupyterDash object at 0x000001AA1B4664F0>>, '/_reload-hash': <bound method Dash.serve_reload_hash of <jupyter_dash.jupyter_app.JupyterDash object at 0x000001AA1B4664F0>>, '/_favicon.ico': <function Dash._serve_default_favicon at 0x000001AA10B51AF0>, '/': <bound method Dash.index of <jupyter_dash.jupyter_app.JupyterDash object at 0x000001AA1B4664F0>>, '/<path:path>': <bound method Dash.index of <jupyter_dash.jupyter_app.JupyterDash object at 0x000001AA1B4664F0>>, 'alive': <function JupyterDash.__init__.<locals>.alive at 0x000001AA1B45A940>}\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mrule.endpoint \u001b[1;34m= '/_dash-layout'\u001b[0m\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\site-packages\\dash\\dash.py:647\u001b[0m, in \u001b[0;36mDash.serve_layout\u001b[1;34m(\n",
      "    self=<jupyter_dash.jupyter_app.JupyterDash object>\n",
      ")\u001b[0m\n",
      "\u001b[0;32m    643\u001b[0m layout \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_layout_value()\n",
      "\u001b[0;32m    645\u001b[0m \u001b[38;5;66;03m# TODO - Set browser cache limit - pass hash into frontend\u001b[39;00m\n",
      "\u001b[0;32m    646\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m flask\u001b[38;5;241m.\u001b[39mResponse(\n",
      "\u001b[1;32m--> 647\u001b[0m     \u001b[43mto_json\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlayout\u001b[49m\u001b[43m)\u001b[49m,\n",
      "        layout \u001b[1;34m= Div([Graph(figure=HBox(children=(Dropdown(description='Origin Airport:', index=1, options=('EWR', 'LGA', 'JFK'), value='LGA'), Dropdown(description='Airline:   ', index=3, options=('UA', 'AA', 'B6', 'DL', 'EV', 'MQ', 'US', 'WN', 'VX', 'FL', 'AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\u001b[0m\n",
      "\u001b[0;32m    648\u001b[0m     mimetype\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapplication/json\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n",
      "\u001b[0;32m    649\u001b[0m )\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\site-packages\\dash\\_utils.py:22\u001b[0m, in \u001b[0;36mto_json\u001b[1;34m(\n",
      "    value=Div([Graph(figure=HBox(children=(Dropdown(descri..., '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\n",
      ")\u001b[0m\n",
      "\u001b[0;32m     18\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mto_json\u001b[39m(value):\n",
      "\u001b[0;32m     19\u001b[0m     \u001b[38;5;66;03m# pylint: disable=import-outside-toplevel\u001b[39;00m\n",
      "\u001b[0;32m     20\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mplotly\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mio\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mjson\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m to_json_plotly\n",
      "\u001b[1;32m---> 22\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mto_json_plotly\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m\n",
      "        value \u001b[1;34m= Div([Graph(figure=HBox(children=(Dropdown(description='Origin Airport:', index=1, options=('EWR', 'LGA', 'JFK'), value='LGA'), Dropdown(description='Airline:   ', index=3, options=('UA', 'AA', 'B6', 'DL', 'EV', 'MQ', 'US', 'WN', 'VX', 'FL', 'AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\u001b[0m\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\site-packages\\plotly\\io\\_json.py:123\u001b[0m, in \u001b[0;36mto_json_plotly\u001b[1;34m(\n",
      "    plotly_object=Div([Graph(figure=HBox(children=(Dropdown(descri..., '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))]),\n",
      "    pretty=False,\n",
      "    engine='json'\n",
      ")\u001b[0m\n",
      "\u001b[0;32m    119\u001b[0m         opts[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mseparators\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "\u001b[0;32m    121\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m_plotly_utils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m PlotlyJSONEncoder\n",
      "\u001b[1;32m--> 123\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m json\u001b[38;5;241m.\u001b[39mdumps(plotly_object, \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m=\u001b[39mPlotlyJSONEncoder, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mopts)\n",
      "        opts \u001b[1;34m= {'separators': (',', ':')}\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mplotly_object \u001b[1;34m= Div([Graph(figure=HBox(children=(Dropdown(description='Origin Airport:', index=1, options=('EWR', 'LGA', 'JFK'), value='LGA'), Dropdown(description='Airline:   ', index=3, options=('UA', 'AA', 'B6', 'DL', 'EV', 'MQ', 'US', 'WN', 'VX', 'FL', 'AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\u001b[0m\n",
      "\u001b[0;32m    124\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m engine \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124morjson\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
      "\u001b[0;32m    125\u001b[0m     JsonConfig\u001b[38;5;241m.\u001b[39mvalidate_orjson()\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\json\\__init__.py:234\u001b[0m, in \u001b[0;36mdumps\u001b[1;34m(\n",
      "    obj=Div([Graph(figure=HBox(children=(Dropdown(descri..., '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))]),\n",
      "    skipkeys=False,\n",
      "    ensure_ascii=True,\n",
      "    check_circular=True,\n",
      "    allow_nan=True,\n",
      "    cls=<class '_plotly_utils.utils.PlotlyJSONEncoder'>,\n",
      "    indent=None,\n",
      "    separators=(',', ':'),\n",
      "    default=None,\n",
      "    sort_keys=False,\n",
      "    **kw={}\n",
      ")\u001b[0m\n",
      "\u001b[0;32m    232\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "\u001b[0;32m    233\u001b[0m     \u001b[38;5;28mcls\u001b[39m \u001b[38;5;241m=\u001b[39m JSONEncoder\n",
      "\u001b[1;32m--> 234\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\n",
      "        cls \u001b[1;34m= <class '_plotly_utils.utils.PlotlyJSONEncoder'>\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mensure_ascii \u001b[1;34m= True\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mskipkeys \u001b[1;34m= False\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mcheck_circular \u001b[1;34m= True\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mallow_nan \u001b[1;34m= True\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mindent \u001b[1;34m= None\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mseparators \u001b[1;34m= (',', ':')\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mdefault \u001b[1;34m= None\u001b[0m\u001b[1;34m\n",
      "        \u001b[0msort_keys \u001b[1;34m= False\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mobj \u001b[1;34m= Div([Graph(figure=HBox(children=(Dropdown(description='Origin Airport:', index=1, options=('EWR', 'LGA', 'JFK'), value='LGA'), Dropdown(description='Airline:   ', index=3, options=('UA', 'AA', 'B6', 'DL', 'EV', 'MQ', 'US', 'WN', 'VX', 'FL', 'AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mkw \u001b[1;34m= {}\u001b[0m\n",
      "\u001b[0;32m    235\u001b[0m \u001b[43m    \u001b[49m\u001b[43mskipkeys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mskipkeys\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mensure_ascii\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_ascii\u001b[49m\u001b[43m,\u001b[49m\n",
      "\u001b[0;32m    236\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcheck_circular\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcheck_circular\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mallow_nan\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallow_nan\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindent\u001b[49m\u001b[43m,\u001b[49m\n",
      "\u001b[0;32m    237\u001b[0m \u001b[43m    \u001b[49m\u001b[43mseparators\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mseparators\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdefault\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdefault\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msort_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msort_keys\u001b[49m\u001b[43m,\u001b[49m\n",
      "\u001b[0;32m    238\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkw\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobj\u001b[49m\u001b[43m)\u001b[49m\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\site-packages\\_plotly_utils\\utils.py:59\u001b[0m, in \u001b[0;36mPlotlyJSONEncoder.encode\u001b[1;34m(\n",
      "    self=<_plotly_utils.utils.PlotlyJSONEncoder object>,\n",
      "    o=Div([Graph(figure=HBox(children=(Dropdown(descri..., '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\n",
      ")\u001b[0m\n",
      "\u001b[0;32m     52\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n",
      "\u001b[0;32m     53\u001b[0m \u001b[38;5;124;03mLoad and then dump the result using parse_constant kwarg\u001b[39;00m\n",
      "\u001b[0;32m     54\u001b[0m \n",
      "\u001b[0;32m     55\u001b[0m \u001b[38;5;124;03mNote that setting invalid separators will cause a failure at this step.\u001b[39;00m\n",
      "\u001b[0;32m     56\u001b[0m \n",
      "\u001b[0;32m     57\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n",
      "\u001b[0;32m     58\u001b[0m \u001b[38;5;66;03m# this will raise errors in a normal-expected way\u001b[39;00m\n",
      "\u001b[1;32m---> 59\u001b[0m encoded_o \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mPlotlyJSONEncoder\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mo\u001b[49m\u001b[43m)\u001b[49m\n",
      "        o \u001b[1;34m= Div([Graph(figure=HBox(children=(Dropdown(description='Origin Airport:', index=1, options=('EWR', 'LGA', 'JFK'), value='LGA'), Dropdown(description='Airline:   ', index=3, options=('UA', 'AA', 'B6', 'DL', 'EV', 'MQ', 'US', 'WN', 'VX', 'FL', 'AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mself \u001b[1;34m= <_plotly_utils.utils.PlotlyJSONEncoder object at 0x000001AA1B227B20>\u001b[0m\n",
      "\u001b[0;32m     60\u001b[0m \u001b[38;5;66;03m# Brute force guessing whether NaN or Infinity values are in the string\u001b[39;00m\n",
      "\u001b[0;32m     61\u001b[0m \u001b[38;5;66;03m# We catch false positive cases (e.g. strings such as titles, labels etc.)\u001b[39;00m\n",
      "\u001b[0;32m     62\u001b[0m \u001b[38;5;66;03m# but this is ok since the intention is to skip the decoding / reencoding\u001b[39;00m\n",
      "\u001b[0;32m     63\u001b[0m \u001b[38;5;66;03m# step when it's completely safe\u001b[39;00m\n",
      "\u001b[0;32m     65\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNaN\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m encoded_o \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInfinity\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m encoded_o):\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\json\\encoder.py:199\u001b[0m, in \u001b[0;36mJSONEncoder.encode\u001b[1;34m(\n",
      "    self=<_plotly_utils.utils.PlotlyJSONEncoder object>,\n",
      "    o=Div([Graph(figure=HBox(children=(Dropdown(descri..., '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\n",
      ")\u001b[0m\n",
      "\u001b[0;32m    195\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m encode_basestring(o)\n",
      "\u001b[0;32m    196\u001b[0m \u001b[38;5;66;03m# This doesn't pass the iterator directly to ''.join() because the\u001b[39;00m\n",
      "\u001b[0;32m    197\u001b[0m \u001b[38;5;66;03m# exceptions aren't as detailed.  The list call should be roughly\u001b[39;00m\n",
      "\u001b[0;32m    198\u001b[0m \u001b[38;5;66;03m# equivalent to the PySequence_Fast that ''.join() would do.\u001b[39;00m\n",
      "\u001b[1;32m--> 199\u001b[0m chunks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miterencode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_one_shot\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
      "        o \u001b[1;34m= Div([Graph(figure=HBox(children=(Dropdown(description='Origin Airport:', index=1, options=('EWR', 'LGA', 'JFK'), value='LGA'), Dropdown(description='Airline:   ', index=3, options=('UA', 'AA', 'B6', 'DL', 'EV', 'MQ', 'US', 'WN', 'VX', 'FL', 'AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mself \u001b[1;34m= <_plotly_utils.utils.PlotlyJSONEncoder object at 0x000001AA1B227B20>\u001b[0m\n",
      "\u001b[0;32m    200\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(chunks, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n",
      "\u001b[0;32m    201\u001b[0m     chunks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(chunks)\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\json\\encoder.py:257\u001b[0m, in \u001b[0;36mJSONEncoder.iterencode\u001b[1;34m(\n",
      "    self=<_plotly_utils.utils.PlotlyJSONEncoder object>,\n",
      "    o=Div([Graph(figure=HBox(children=(Dropdown(descri..., '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))]),\n",
      "    _one_shot=True\n",
      ")\u001b[0m\n",
      "\u001b[0;32m    252\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "\u001b[0;32m    253\u001b[0m     _iterencode \u001b[38;5;241m=\u001b[39m _make_iterencode(\n",
      "\u001b[0;32m    254\u001b[0m         markers, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdefault, _encoder, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mindent, floatstr,\n",
      "\u001b[0;32m    255\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkey_separator, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mitem_separator, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msort_keys,\n",
      "\u001b[0;32m    256\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mskipkeys, _one_shot)\n",
      "\u001b[1;32m--> 257\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_iterencode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "        _iterencode \u001b[1;34m= <_json.Encoder object at 0x000001AA1A398E20>\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mo \u001b[1;34m= Div([Graph(figure=HBox(children=(Dropdown(description='Origin Airport:', index=1, options=('EWR', 'LGA', 'JFK'), value='LGA'), Dropdown(description='Airline:   ', index=3, options=('UA', 'AA', 'B6', 'DL', 'EV', 'MQ', 'US', 'WN', 'VX', 'FL', 'AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL'))))])\u001b[0m\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\site-packages\\_plotly_utils\\utils.py:136\u001b[0m, in \u001b[0;36mPlotlyJSONEncoder.default\u001b[1;34m(\n",
      "    self=<_plotly_utils.utils.PlotlyJSONEncoder object>,\n",
      "    obj=HBox(children=(Dropdown(description='Origin Airp...AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL')))\n",
      ")\u001b[0m\n",
      "\u001b[0;32m    134\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m NotEncodable:\n",
      "\u001b[0;32m    135\u001b[0m         \u001b[38;5;28;01mpass\u001b[39;00m\n",
      "\u001b[1;32m--> 136\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_json\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mJSONEncoder\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdefault\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mobj\u001b[49m\u001b[43m)\u001b[49m\n",
      "        self \u001b[1;34m= <_plotly_utils.utils.PlotlyJSONEncoder object at 0x000001AA1B227B20>\u001b[0m\u001b[1;34m\n",
      "        \u001b[0mobj \u001b[1;34m= HBox(children=(Dropdown(description='Origin Airport:', index=1, options=('EWR', 'LGA', 'JFK'), value='LGA'), Dropdown(description='Airline:   ', index=3, options=('UA', 'AA', 'B6', 'DL', 'EV', 'MQ', 'US', 'WN', 'VX', 'FL', 'AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL')))\u001b[0m\u001b[1;34m\n",
      "        \u001b[0m_json \u001b[1;34m= <module 'json' from 'c:\\\\Users\\\\mdavi\\\\anaconda3\\\\envs\\\\PyRapidEPE\\\\lib\\\\json\\\\__init__.py'>\u001b[0m\n",
      "\n",
      "File \u001b[1;32mc:\\Users\\mdavi\\anaconda3\\envs\\PyRapidEPE\\lib\\json\\encoder.py:179\u001b[0m, in \u001b[0;36mJSONEncoder.default\u001b[1;34m(\n",
      "    self=<_plotly_utils.utils.PlotlyJSONEncoder object>,\n",
      "    o=HBox(children=(Dropdown(description='Origin Airp...AS', '9E', 'F9', 'HA', 'YV', 'OO'), value='DL')))\n",
      ")\u001b[0m\n",
      "\u001b[0;32m    160\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdefault\u001b[39m(\u001b[38;5;28mself\u001b[39m, o):\n",
      "\u001b[0;32m    161\u001b[0m     \u001b[38;5;124;03m\"\"\"Implement this method in a subclass such that it returns\u001b[39;00m\n",
      "\u001b[0;32m    162\u001b[0m \u001b[38;5;124;03m    a serializable object for ``o``, or calls the base implementation\u001b[39;00m\n",
      "\u001b[0;32m    163\u001b[0m \u001b[38;5;124;03m    (to raise a ``TypeError``).\u001b[39;00m\n",
      "\u001b[1;32m   (...)\u001b[0m\n",
      "\u001b[0;32m    177\u001b[0m \n",
      "\u001b[0;32m    178\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n",
      "\u001b[1;32m--> 179\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mObject of type \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mo\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\n",
      "\u001b[0;32m    180\u001b[0m                     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mis not JSON serializable\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "\n",
      "\u001b[1;31mTypeError\u001b[0m: Object of type HBox is not JSON serializable\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv(\n",
    "    'https://raw.githubusercontent.com/yankev/testing/master/datasets/nycflights.csv')\n",
    "df = df.drop(df.columns[[0]], axis=1)\n",
    "\n",
    "month = widgets.IntSlider(\n",
    "    value=1.0,\n",
    "    min=1.0,\n",
    "    max=12.0,\n",
    "    step=1.0,\n",
    "    description='Month:',\n",
    "    continuous_update=False\n",
    ")\n",
    "\n",
    "use_date = widgets.Checkbox(\n",
    "    description='Date: ',\n",
    "    value=True,\n",
    ")\n",
    "\n",
    "container = widgets.HBox(children=[use_date, month])\n",
    "\n",
    "textbox = widgets.Dropdown(\n",
    "    description='Airline:   ',\n",
    "    value='DL',\n",
    "    options=df['carrier'].unique().tolist()\n",
    ")\n",
    "\n",
    "origin = widgets.Dropdown(\n",
    "    options=list(df['origin'].unique()),\n",
    "    value='LGA',\n",
    "    description='Origin Airport:',\n",
    ")\n",
    "\n",
    "\n",
    "# Assign an empty figure widget with two traces\n",
    "trace1 = go.Histogram(x=df['arr_delay'], opacity=0.75, name='Arrival Delays')\n",
    "trace2 = go.Histogram(x=df['dep_delay'], opacity=0.75, name='Departure Delays')\n",
    "g = go.FigureWidget(data=[trace1, trace2],\n",
    "                    layout=go.Layout(\n",
    "                        title=dict(\n",
    "                            text='NYC FlightDatabase'\n",
    "                        ),\n",
    "                        barmode='overlay'\n",
    "                    ))\n",
    "\n",
    "def validate():\n",
    "    if origin.value in df['origin'].unique() and textbox.value in df['carrier'].unique():\n",
    "        return True\n",
    "    else:\n",
    "        return False\n",
    "\n",
    "\n",
    "def response(change):\n",
    "    if validate():\n",
    "        if use_date.value:\n",
    "            filter_list = [i and j and k for i, j, k in\n",
    "                           zip(df['month'] == month.value, df['carrier'] == textbox.value,\n",
    "                               df['origin'] == origin.value)]\n",
    "            temp_df = df[filter_list]\n",
    "\n",
    "        else:\n",
    "            filter_list = [i and j for i, j in\n",
    "                           zip(df['carrier'] == 'DL', df['origin'] == origin.value)]\n",
    "            temp_df = df[filter_list]\n",
    "        x1 = temp_df['arr_delay']\n",
    "        x2 = temp_df['dep_delay']\n",
    "        with g.batch_update():\n",
    "            g.data[0].x = x1\n",
    "            g.data[1].x = x2\n",
    "            g.layout.barmode = 'overlay'\n",
    "            g.layout.xaxis.title = 'Delay in Minutes'\n",
    "            g.layout.yaxis.title = 'Number of Delays'\n",
    "\n",
    "\n",
    "origin.observe(response, names=\"value\")\n",
    "textbox.observe(response, names=\"value\")\n",
    "month.observe(response, names=\"value\")\n",
    "use_date.observe(response, names=\"value\")\n",
    "\n",
    "container2 = widgets.HBox([origin, textbox])\n",
    "widgets.VBox([container,\n",
    "              container2,\n",
    "              g])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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   "source": [
    "fig= container2\n",
    "\n",
    "\n",
    "app = JupyterDash(__name__)\n",
    "\n",
    "app.layout = html.Div([dcc.Graph(figure=fig)])\n",
    "\n",
    "app.run_server(debug=True, use_reloader=False,mode=\"inline\")  # Turn off reloader if inside Jupyter"
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