TripPlanner.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#on the terminal:\n",
    "#sudo apt install git #git config --global user.name \"JAlcocerT\" #git config --global user.email \"jalcocert@fossengineer.com\"\n",
    "#sudo apt install python3 python3-pip\n",
    "#$ python3 -m pip install ipykernel\n",
    "#pip list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install dash\n",
    "# !pip install dash_leaflet\n",
    "# !pip install meteostat #apt install libatlas3-base \n",
    "# !pip install openmeteo-py\n",
    "# !pip install jupyter_dash\n",
    "# !pip install nbformat>=4.2.0\n",
    "#pip install dash; pip install dash_leaflet; pip install jupyter_dash; pip install meteostat; pip install openmeteo-py\n",
    "#pip install --upgrade nbformat; pip install --upgrade numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.2.1\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "print(np.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dash\n",
    "from dash import html \n",
    "from dash import dcc\n",
    "from dash.dependencies import Input, Output\n",
    "\n",
    "from datetime import datetime, timedelta, date\n",
    "\n",
    "from meteostat import Point#, Daily\n",
    "from meteostat import Daily as MeteoDaily\n",
    "from meteostat import Stations #new in v1.2\n",
    "\n",
    "#from openmeteo_py import Hourly,Options,OWmanager #new in V2\n",
    "#from openmeteo_py import Daily as OpenMeteoDaily\n",
    "\n",
    "import pandas as pd  #new in V2\n",
    "\n",
    "import plotly.graph_objects as go  #new in V2\n",
    "import plotly.express as px\n",
    "import dash_leaflet as dl\n",
    "\n",
    "from jupyter_dash import JupyterDash"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DASH version: 1.3.4\n",
      "DASH version: 2.7.0\n",
      "HTML version: 2.0.6\n",
      "Meteostat version: 1.6.5\n",
      "Plotly version: 5.11.0\n",
      "Dash Leaflet version: 0.1.23\n",
      "Jupyter DASH version: 0.4.2\n",
      "nbformat version: 5.1.3\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "print(f'DASH version: {pd.__version__}')\n",
    "\n",
    "\n",
    "#print the versions of the libraries\n",
    "print(f'DASH version: {dash.__version__}')\n",
    "print(f'HTML version: {html.__version__}')\n",
    "\n",
    "import meteostat\n",
    "print(f'Meteostat version: {meteostat.__version__}')\n",
    "#import openmeteo_py\n",
    "#print(f'OpenMeteo version: {openmeteo_py.__version__}')\n",
    "\n",
    "import plotly\n",
    "print(f'Plotly version: {plotly.__version__}')\n",
    "print(f'Dash Leaflet version: {dl.__version__}')\n",
    "\n",
    "import jupyter_dash\n",
    "print(f'Jupyter DASH version: {jupyter_dash.__version__}')\n",
    "\n",
    "import nbformat\n",
    "print(f'nbformat version: {nbformat.__version__}')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Open-Meteo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install openmeteo-py\n",
    "#https://pypi.org/project/openmeteo-py/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'latitude': 52.1875, 'longitude': 20.0, 'generationtime_ms': 2.617001533508301, 'utc_offset_seconds': 0, 'timezone': 'UTC', 'timezone_abbreviation': 'UTC', 'elevation': 97.0, 'hourly_units': {'time': 'iso8601', 'relativehumidity_2m': '%', 'dewpoint_2m': '°C', 'apparent_temperature': '°C', 'pressure_msl': 'hPa', 'cloudcover': '%', 'cloudcover_low': '%', 'cloudcover_mid': '%', 'cloudcover_high': '%', 'windspeed_10m': 'km/h', 'windspeed_80m': 'km/h', 'windspeed_120m': 'km/h', 'windspeed_180m': 'km/h', 'winddirection_10m': '°', 'winddirection_80m': '°', 'winddirection_120m': '°', 'winddirection_180m': '°', 'windgusts_10m': 'km/h', 'shortwave_radiation': 'W/m²', 'direct_radiation': 'W/m²', 'diffuse_radiation': 'W/m²', 'vapor_pressure_deficit': 'kPa', 'evapotranspiration': 'mm', 'precipitation': 'mm', 'weathercode': 'wmo code', 'snow_height': 'm', 'freezinglevel_height': 'm', 'soil_temperature_0cm': '°C', 'soil_temperature_6cm': '°C', 'soil_temperature_18cm': '°C', 'soil_temperature_54cm': '°C', 'soil_moisture_0_1cm': 'm³/m³', 'soil_moisture_1_3cm': 'm³/m³', 'soil_moisture_3_9cm': 'm³/m³', 'soil_moisture_9_27cm': 'm³/m³', 'soil_moisture_27_81cm': 'm³/m³'}, 'hourly': {'time': ['2023-06-30T00:00', '2023-06-30T01:00', '2023-06-30T02:00', '2023-06-30T03:00', '2023-06-30T04:00', '2023-06-30T05:00', '2023-06-30T06:00', '2023-06-30T07:00', '2023-06-30T08:00', '2023-06-30T09:00', '2023-06-30T10:00', '2023-06-30T11:00', '2023-06-30T12:00', '2023-06-30T13:00', '2023-06-30T14:00', '2023-06-30T15:00', '2023-06-30T16:00', '2023-06-30T17:00', '2023-06-30T18:00', '2023-06-30T19:00', '2023-06-30T20:00', '2023-06-30T21:00', '2023-06-30T22:00', '2023-06-30T23:00', '2023-07-01T00:00', '2023-07-01T01:00', '2023-07-01T02:00', '2023-07-01T03:00', '2023-07-01T04:00', '2023-07-01T05:00', '2023-07-01T06:00', '2023-07-01T07:00', '2023-07-01T08:00', '2023-07-01T09:00', '2023-07-01T10:00', '2023-07-01T11:00', '2023-07-01T12:00', '2023-07-01T13:00', '2023-07-01T14:00', '2023-07-01T15:00', '2023-07-01T16:00', '2023-07-01T17:00', '2023-07-01T18:00', '2023-07-01T19:00', '2023-07-01T20:00', '2023-07-01T21:00', '2023-07-01T22:00', '2023-07-01T23:00', '2023-07-02T00:00', '2023-07-02T01:00', '2023-07-02T02:00', '2023-07-02T03:00', '2023-07-02T04:00', '2023-07-02T05:00', '2023-07-02T06:00', '2023-07-02T07:00', '2023-07-02T08:00', '2023-07-02T09:00', '2023-07-02T10:00', '2023-07-02T11:00', '2023-07-02T12:00', '2023-07-02T13:00', '2023-07-02T14:00', '2023-07-02T15:00', '2023-07-02T16:00', '2023-07-02T17:00', '2023-07-02T18:00', '2023-07-02T19:00', '2023-07-02T20:00', '2023-07-02T21:00', '2023-07-02T22:00', '2023-07-02T23:00', '2023-07-03T00:00', '2023-07-03T01:00', '2023-07-03T02:00', '2023-07-03T03:00', '2023-07-03T04:00', '2023-07-03T05:00', '2023-07-03T06:00', '2023-07-03T07:00', '2023-07-03T08:00', '2023-07-03T09:00', '2023-07-03T10:00', '2023-07-03T11:00', '2023-07-03T12:00', '2023-07-03T13:00', '2023-07-03T14:00', '2023-07-03T15:00', '2023-07-03T16:00', '2023-07-03T17:00', '2023-07-03T18:00', '2023-07-03T19:00', '2023-07-03T20:00', '2023-07-03T21:00', '2023-07-03T22:00', '2023-07-03T23:00', '2023-07-04T00:00', '2023-07-04T01:00', '2023-07-04T02:00', '2023-07-04T03:00', '2023-07-04T04:00', '2023-07-04T05:00', '2023-07-04T06:00', '2023-07-04T07:00', '2023-07-04T08:00', '2023-07-04T09:00', '2023-07-04T10:00', '2023-07-04T11:00', '2023-07-04T12:00', '2023-07-04T13:00', '2023-07-04T14:00', '2023-07-04T15:00', '2023-07-04T16:00', '2023-07-04T17:00', '2023-07-04T18:00', '2023-07-04T19:00', '2023-07-04T20:00', '2023-07-04T21:00', '2023-07-04T22:00', '2023-07-04T23:00', '2023-07-05T00:00', '2023-07-05T01:00', '2023-07-05T02:00', '2023-07-05T03:00', '2023-07-05T04:00', '2023-07-05T05:00', '2023-07-05T06:00', '2023-07-05T07:00', '2023-07-05T08:00', '2023-07-05T09:00', '2023-07-05T10:00', '2023-07-05T11:00', '2023-07-05T12:00', '2023-07-05T13:00', '2023-07-05T14:00', '2023-07-05T15:00', '2023-07-05T16:00', '2023-07-05T17:00', '2023-07-05T18:00', '2023-07-05T19:00', '2023-07-05T20:00', '2023-07-05T21:00', '2023-07-05T22:00', '2023-07-05T23:00', '2023-07-06T00:00', '2023-07-06T01:00', '2023-07-06T02:00', '2023-07-06T03:00', '2023-07-06T04:00', '2023-07-06T05:00', '2023-07-06T06:00', '2023-07-06T07:00', '2023-07-06T08:00', '2023-07-06T09:00', '2023-07-06T10:00', '2023-07-06T11:00', '2023-07-06T12:00', '2023-07-06T13:00', '2023-07-06T14:00', '2023-07-06T15:00', '2023-07-06T16:00', '2023-07-06T17:00', '2023-07-06T18:00', '2023-07-06T19:00', '2023-07-06T20:00', '2023-07-06T21:00', '2023-07-06T22:00', '2023-07-06T23:00'], 'relativehumidity_2m': [92, 92, 94, 95, 91, 84, 71, 67, 58, 45, 45, 42, 44, 42, 41, 42, 44, 54, 64, 79, 89, 93, 95, 96, 95, 95, 95, 95, 93, 93, 90, 86, 87, 84, 82, 79, 72, 67, 64, 63, 52, 54, 62, 69, 73, 72, 77, 78, 77, 78, 83, 86, 87, 86, 80, 83, 86, 90, 88, 85, 65, 59, 48, 47, 48, 52, 60, 66, 72, 75, 83, 86, 86, 86, 85, 84, 81, 76, 67, 60, 52, 48, 45, 42, 41, 39, 38, 39, 42, 46, 51, 56, 62, 68, 73, 78, 81, 83, 84, 82, 77, 69, 61, 53, 44, 38, 36, 36, 36, 36, 37, 39, 43, 49, 55, 62, 70, 77, 82, 85, 88, 91, 94, 95, 91, 85, 81, 78, 74, 69, 61, 52, 45, 41, 40, 41, 46, 53, 60, 64, 67, 70, 73, 76, 79, 81, 83, 83, 80, 75, 69, 62, 53, 46, 41, 38, 36, 34, 32, 33, 36, 41, 47, 54, 61, 67, 69, 69], 'dewpoint_2m': [12.7, 12.1, 12.0, 11.7, 12.9, 14.1, 14.3, 15.5, 14.8, 12.2, 12.2, 11.5, 12.2, 12.2, 12.5, 12.3, 12.5, 13.9, 14.7, 15.9, 16.7, 16.7, 16.6, 16.6, 16.3, 16.0, 15.3, 15.1, 15.2, 15.7, 16.2, 16.4, 16.5, 16.9, 16.9, 16.8, 16.5, 16.1, 15.7, 15.7, 13.0, 13.2, 14.0, 14.1, 14.3, 13.5, 13.4, 13.1, 12.6, 12.5, 12.9, 13.2, 13.7, 14.2, 14.2, 14.6, 15.2, 15.5, 15.4, 15.4, 13.7, 12.9, 10.8, 10.3, 10.4, 11.0, 11.8, 11.6, 11.9, 12.1, 12.3, 12.2, 11.9, 11.7, 11.5, 11.1, 11.4, 11.9, 11.9, 11.3, 10.9, 10.5, 10.3, 10.1, 9.8, 9.3, 9.1, 9.3, 9.8, 10.2, 10.6, 10.7, 10.8, 10.9, 10.8, 10.8, 10.5, 9.9, 9.3, 9.2, 10.1, 11.3, 12.0, 12.0, 11.1, 10.4, 10.4, 10.7, 10.9, 11.1, 11.5, 12.1, 13.0, 14.1, 14.8, 14.9, 14.7, 14.5, 14.5, 14.5, 14.7, 15.0, 15.6, 16.0, 15.8, 15.4, 15.2, 13.2, 13.7, 13.9, 13.3, 12.0, 10.6, 9.6, 9.4, 9.5, 10.8, 12.2, 13.1, 12.8, 11.8, 11.0, 10.6, 10.4, 10.3, 9.9, 9.6, 9.8, 10.8, 12.2, 13.2, 13.4, 12.7, 11.9, 11.0, 10.3, 9.9, 9.4, 8.7, 9.1, 9.9, 10.9, 11.8, 11.9, 11.4, 10.9, 10.6, 10.4], 'apparent_temperature': [14.2, 13.4, 12.8, 12.3, 14.3, 17.2, 20.0, 22.6, 23.8, 24.6, 23.9, 24.1, 24.6, 25.5, 26.1, 25.3, 24.8, 23.8, 20.9, 20.3, 19.7, 19.3, 19.0, 18.6, 18.5, 17.9, 16.8, 16.6, 17.1, 17.9, 18.9, 19.8, 19.7, 21.1, 21.3, 21.7, 22.7, 23.4, 23.8, 23.7, 23.0, 22.6, 22.0, 20.5, 19.3, 18.2, 17.3, 16.8, 16.3, 15.8, 15.4, 15.2, 15.6, 16.1, 16.1, 16.7, 16.8, 16.8, 16.5, 17.1, 18.0, 18.6, 19.1, 19.0, 19.3, 19.6, 19.0, 17.2, 16.2, 15.7, 14.5, 13.8, 13.4, 13.0, 12.7, 12.4, 13.3, 15.0, 16.5, 17.4, 18.7, 19.1, 19.1, 20.5, 20.2, 20.3, 20.5, 20.9, 21.1, 20.8, 20.2, 19.1, 17.7, 16.2, 15.0, 14.0, 13.0, 11.9, 11.0, 11.1, 13.1, 16.2, 19.0, 20.9, 22.5, 24.1, 25.1, 25.4, 25.4, 25.4, 25.7, 25.8, 25.9, 25.8, 25.1, 23.4, 21.1, 19.2, 18.3, 17.7, 17.4, 17.1, 16.9, 16.8, 17.0, 17.3, 17.5, 16.3, 17.9, 19.3, 20.4, 21.9, 22.8, 22.9, 22.5, 22.0, 22.2, 22.3, 21.9, 20.3, 18.1, 16.3, 15.1, 14.2, 13.5, 12.6, 11.8, 12.1, 14.0, 16.9, 19.6, 21.6, 23.4, 25.3, 26.4, 27.0, 27.3, 27.3, 26.6, 25.8, 25.7, 25.1, 23.8, 21.7, 18.9, 16.8, 16.0, 15.9], 'pressure_msl': [1012.0, 1011.8, 1011.5, 1011.4, 1011.1, 1010.7, 1011.3, 1010.9, 1010.8, 1010.7, 1010.1, 1009.4, 1008.8, 1008.5, 1008.1, 1007.5, 1007.3, 1007.2, 1007.7, 1008.4, 1008.4, 1008.5, 1008.1, 1007.8, 1007.5, 1007.2, 1007.5, 1007.4, 1007.1, 1006.9, 1007.2, 1007.2, 1007.3, 1007.3, 1007.1, 1006.6, 1006.2, 1006.0, 1005.6, 1005.2, 1004.2, 1004.2, 1004.2, 1004.5, 1004.5, 1004.6, 1004.6, 1004.4, 1004.4, 1004.4, 1004.3, 1004.1, 1004.0, 1004.2, 1004.3, 1004.3, 1004.6, 1004.9, 1005.2, 1005.1, 1005.2, 1005.5, 1005.4, 1005.4, 1005.4, 1005.7, 1006.1, 1006.7, 1007.2, 1007.7, 1008.2, 1008.4, 1008.5, 1008.4, 1008.8, 1009.0, 1009.1, 1009.4, 1009.6, 1009.8, 1009.8, 1009.8, 1009.7, 1009.6, 1009.5, 1009.5, 1009.5, 1009.6, 1009.8, 1010.1, 1010.5, 1011.0, 1011.5, 1011.9, 1012.1, 1012.2, 1012.3, 1012.4, 1012.5, 1012.6, 1012.8, 1012.9, 1012.9, 1012.6, 1012.2, 1011.8, 1011.4, 1011.1, 1010.7, 1010.4, 1010.0, 1009.8, 1009.7, 1009.6, 1009.6, 1009.8, 1010.0, 1010.2, 1010.2, 1010.3, 1010.4, 1010.8, 1011.3, 1011.9, 1012.7, 1013.5, 1014.1, 1014.2, 1014.5, 1014.7, 1014.7, 1014.6, 1014.5, 1014.4, 1014.2, 1014.2, 1014.3, 1014.4, 1014.7, 1015.2, 1015.7, 1016.2, 1016.5, 1016.6, 1016.7, 1016.8, 1016.8, 1016.9, 1017.2, 1017.7, 1018.0, 1018.2, 1018.2, 1018.2, 1018.1, 1017.9, 1017.7, 1017.5, 1017.3, 1017.2, 1017.3, 1017.4, 1017.7, 1018.1, 1018.7, 1019.1, 1019.3, 1019.5], 'cloudcover': [38, 37, 35, 47, 72, 91, 25, 100, 63, 96, 96, 92, 93, 91, 63, 98, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 78, 100, 98, 95, 92, 98, 97, 92, 96, 85, 86, 79, 70, 75, 74, 74, 78, 83, 85, 91, 100, 100, 100, 98, 97, 98, 100, 97, 99, 100, 100, 99, 97, 98, 93, 67, 61, 56, 47, 43, 38, 73, 84, 53, 41, 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0.158, 0.16, 0.16, 0.158, 0.156, 0.153, 0.142, 0.14, 0.138, 0.137, 0.136, 0.135, 0.134, 0.134, 0.134, 0.133, 0.133, 0.133, 0.133, 0.133, 0.132, 0.132, 0.133, 0.14, 0.165, 0.179, 0.183, 0.18, 0.175, 0.171, 0.167, 0.163, 0.16, 0.158, 0.157, 0.155, 0.154, 0.154, 0.153, 0.153, 0.152, 0.152, 0.151, 0.151, 0.15, 0.148, 0.147, 0.145, 0.142, 0.14, 0.137, 0.135, 0.133, 0.131, 0.129, 0.127, 0.126, 0.125, 0.124, 0.124, 0.124, 0.123, 0.123, 0.123, 0.124, 0.124, 0.124, 0.124, 0.124, 0.123, 0.122, 0.121, 0.119, 0.118, 0.116, 0.115, 0.113, 0.112, 0.111, 0.11, 0.109, 0.108, 0.108, 0.108, 0.108, 0.108, 0.108, 0.108, 0.108, 0.108, 0.109, 0.11, 0.111, 0.208, 0.202, 0.197, 0.191, 0.185, 0.179, 0.174, 0.169, 0.165, 0.162, 0.159, 0.157, 0.156, 0.157, 0.157, 0.157, 0.158, 0.158, 0.158, 0.158, 0.158, 0.158, 0.159, 0.158, 0.156, 0.154, 0.151, 0.148, 0.144, 0.14, 0.136, 0.133, 0.13, 0.127, 0.125, 0.123, 0.122, 0.121, 0.121, 0.121, 0.121], 'soil_moisture_3_9cm': [0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.136, 0.136, 0.135, 0.135, 0.134, 0.134, 0.133, 0.133, 0.132, 0.132, 0.131, 0.131, 0.131, 0.131, 0.131, 0.131, 0.13, 0.13, 0.131, 0.131, 0.131, 0.131, 0.132, 0.132, 0.132, 0.133, 0.133, 0.133, 0.134, 0.134, 0.135, 0.135, 0.136, 0.136, 0.136, 0.136, 0.136, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.137, 0.138, 0.14, 0.141, 0.142, 0.142, 0.143, 0.143, 0.143, 0.144, 0.144, 0.145, 0.145, 0.145, 0.145, 0.146, 0.146, 0.146, 0.146, 0.146, 0.146, 0.146, 0.145, 0.145, 0.144, 0.144, 0.143, 0.142, 0.142, 0.141, 0.141, 0.14, 0.14, 0.14, 0.139, 0.139, 0.139, 0.139, 0.139, 0.139, 0.138, 0.138, 0.138, 0.138, 0.138, 0.137, 0.136, 0.135, 0.134, 0.134, 0.133, 0.132, 0.132, 0.131, 0.131, 0.13, 0.13, 0.13, 0.13, 0.13, 0.13, 0.129, 0.129, 0.129, 0.129, 0.129, 0.129, 0.128, 0.128, 0.191, 0.192, 0.192, 0.192, 0.19, 0.189, 0.187, 0.186, 0.184, 0.183, 0.181, 0.18, 0.179, 0.179, 0.178, 0.177, 0.177, 0.176, 0.175, 0.175, 0.174, 0.174, 0.174, 0.173, 0.172, 0.17, 0.169, 0.168, 0.166, 0.165, 0.164, 0.162, 0.161, 0.16, 0.159, 0.158, 0.157, 0.157, 0.156, 0.156, 0.155], 'soil_moisture_9_27cm': [0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.159, 0.159, 0.159, 0.158, 0.158, 0.158, 0.157, 0.157, 0.157, 0.156, 0.156, 0.156, 0.156, 0.156, 0.156, 0.157, 0.157, 0.157, 0.157, 0.157, 0.157, 0.157, 0.157, 0.157, 0.157, 0.157, 0.157, 0.156, 0.156, 0.156, 0.156, 0.156, 0.155, 0.154, 0.154, 0.154, 0.154, 0.154, 0.154, 0.154, 0.154, 0.155, 0.155, 0.155, 0.155, 0.155, 0.155, 0.155, 0.155, 0.155, 0.154, 0.154, 0.154, 0.154, 0.154, 0.154, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.153, 0.152, 0.152, 0.152, 0.151, 0.151, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.149, 0.149, 0.149, 0.148, 0.148, 0.148, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.148, 0.148, 0.148, 0.148, 0.148, 0.148, 0.148, 0.147, 0.147, 0.147, 0.147, 0.147, 0.147, 0.148, 0.148, 0.148, 0.148, 0.148, 0.148, 0.149, 0.149, 0.149, 0.149, 0.149, 0.149, 0.148, 0.148, 0.148, 0.147, 0.147, 0.147, 0.146, 0.146, 0.146, 0.146, 0.146, 0.146, 0.146, 0.146, 0.146, 0.147], 'soil_moisture_27_81cm': [0.229, 0.229, 0.229, 0.229, 0.229, 0.229, 0.229, 0.229, 0.228, 0.228, 0.228, 0.228, 0.228, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.227, 0.226, 0.226, 0.226, 0.226, 0.226, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.224, 0.223, 0.223, 0.223, 0.223, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.222, 0.221, 0.221, 0.221, 0.221, 0.221, 0.221, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.22, 0.219, 0.219, 0.219, 0.219, 0.219, 0.219, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.218, 0.217, 0.217, 0.217, 0.217, 0.217, 0.217, 0.216, 0.216, 0.216, 0.216, 0.216, 0.216, 0.216, 0.216, 0.216, 0.216]}, 'daily_units': {'time': 'iso8601', 'temperature_2m_max': '°C', 'temperature_2m_min': '°C', 'apparent_temperature_max': '°C', 'apparent_temperature_min': '°C', 'precipitation_sum': 'mm', 'precipitation_hours': 'h', 'weathercode': 'wmo code', 'sunrise': 'iso8601', 'sunset': 'iso8601', 'windspeed_10m_max': 'km/h', 'windgusts_10m_max': 'km/h', 'winddirection_10m_dominant': '°', 'shortwave_radiation_sum': 'MJ/m²'}, 'daily': {'time': ['2023-06-30', '2023-07-01', '2023-07-02', '2023-07-03', '2023-07-04', '2023-07-05', '2023-07-06'], 'temperature_2m_max': [26.8, 23.5, 22.4, 24.4, 27.5, 23.8, 26.8], 'temperature_2m_min': [12.5, 15.9, 14.6, 13.8, 11.9, 14.6, 12.4], 'apparent_temperature_max': [26.1, 23.8, 19.6, 21.1, 25.9, 22.9, 27.3], 'apparent_temperature_min': [12.3, 16.6, 13.8, 12.4, 11.0, 14.2, 11.8], 'precipitation_sum': [1.4, 1.1, 2.5, 0.0, 0.0, 0.3, 0.0], 'precipitation_hours': [5.0, 5.0, 7.0, 0.0, 0.0, 3.0, 0.0], 'weathercode': [61, 80, 61, 3, 3, 3, 3], 'sunrise': ['2023-06-30T02:22', '2023-07-01T02:23', '2023-07-02T02:23', '2023-07-03T02:24', '2023-07-04T02:25', '2023-07-05T02:26', '2023-07-06T02:27'], 'sunset': ['2023-06-30T19:04', '2023-07-01T19:04', '2023-07-02T19:04', '2023-07-03T19:03', '2023-07-04T19:03', '2023-07-05T19:02', '2023-07-06T19:02'], 'windspeed_10m_max': [17.4, 10.7, 25.7, 28.9, 18.4, 18.6, 4.4], 'windgusts_10m_max': [32.4, 25.6, 50.0, 56.9, 37.4, 34.6, 9.4], 'winddirection_10m_dominant': [265, 258, 256, 253, 210, 271, 198], 'shortwave_radiation_sum': [18.73, 14.78, 13.18, 22.96, 22.42, 23.08, 26.41]}}\n",
      "<class 'dict'>\n"
     ]
    }
   ],
   "source": [
    "from openmeteo_py import Hourly,Daily,Options,OWmanager\n",
    "\n",
    "# Latitude, Longitude for Rabat,Morocco\n",
    "latitude = 52.2\n",
    "longitude = 20\n",
    "\n",
    "hourly = Hourly()\n",
    "daily = Daily()\n",
    "options = Options(latitude,longitude)\n",
    "\n",
    "mgr = OWmanager(options,\n",
    "    hourly.all(),\n",
    "    daily.all())\n",
    "\n",
    "\n",
    "# Download data\n",
    "meteo = mgr.get_data()\n",
    "\n",
    "print(meteo)\n",
    "print(type(meteo))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'latitude': 'float', 'longitude': 'float', 'generationtime_ms': 'float', 'utc_offset_seconds': 'int', 'timezone': 'str', 'timezone_abbreviation': 'str', 'elevation': 'float', 'hourly_units': 'dict', 'hourly': 'dict', 'daily_units': 'dict', 'daily': 'dict'}\n"
     ]
    }
   ],
   "source": [
    "def get_schema(dictionary):\n",
    "    schema = {}\n",
    "    for key, value in dictionary.items():\n",
    "        schema[key] = type(value).__name__\n",
    "    return schema\n",
    "\n",
    "print(get_schema(meteo))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "latitude: float\n",
      "longitude: float\n",
      "generationtime_ms: float\n",
      "utc_offset_seconds: int\n",
      "timezone: str\n",
      "timezone_abbreviation: str\n",
      "elevation: float\n",
      "hourly_units.time: str\n",
      "hourly_units.relativehumidity_2m: str\n",
      "hourly_units.dewpoint_2m: str\n",
      "hourly_units.apparent_temperature: str\n",
      "hourly_units.pressure_msl: str\n",
      "hourly_units.cloudcover: str\n",
      "hourly_units.cloudcover_low: str\n",
      "hourly_units.cloudcover_mid: str\n",
      "hourly_units.cloudcover_high: str\n",
      "hourly_units.windspeed_10m: str\n",
      "hourly_units.windspeed_80m: str\n",
      "hourly_units.windspeed_120m: str\n",
      "hourly_units.windspeed_180m: str\n",
      "hourly_units.winddirection_10m: str\n",
      "hourly_units.winddirection_80m: str\n",
      "hourly_units.winddirection_120m: str\n",
      "hourly_units.winddirection_180m: str\n",
      "hourly_units.windgusts_10m: str\n",
      "hourly_units.shortwave_radiation: str\n",
      "hourly_units.direct_radiation: str\n",
      "hourly_units.diffuse_radiation: str\n",
      "hourly_units.vapor_pressure_deficit: str\n",
      "hourly_units.evapotranspiration: str\n",
      "hourly_units.precipitation: str\n",
      "hourly_units.weathercode: str\n",
      "hourly_units.snow_height: str\n",
      "hourly_units.freezinglevel_height: str\n",
      "hourly_units.soil_temperature_0cm: str\n",
      "hourly_units.soil_temperature_6cm: str\n",
      "hourly_units.soil_temperature_18cm: str\n",
      "hourly_units.soil_temperature_54cm: str\n",
      "hourly_units.soil_moisture_0_1cm: str\n",
      "hourly_units.soil_moisture_1_3cm: str\n",
      "hourly_units.soil_moisture_3_9cm: str\n",
      "hourly_units.soil_moisture_9_27cm: str\n",
      "hourly_units.soil_moisture_27_81cm: str\n",
      "hourly.time: list\n",
      "hourly.relativehumidity_2m: list\n",
      "hourly.dewpoint_2m: list\n",
      "hourly.apparent_temperature: list\n",
      "hourly.pressure_msl: list\n",
      "hourly.cloudcover: list\n",
      "hourly.cloudcover_low: list\n",
      "hourly.cloudcover_mid: list\n",
      "hourly.cloudcover_high: list\n",
      "hourly.windspeed_10m: list\n",
      "hourly.windspeed_80m: list\n",
      "hourly.windspeed_120m: list\n",
      "hourly.windspeed_180m: list\n",
      "hourly.winddirection_10m: list\n",
      "hourly.winddirection_80m: list\n",
      "hourly.winddirection_120m: list\n",
      "hourly.winddirection_180m: list\n",
      "hourly.windgusts_10m: list\n",
      "hourly.shortwave_radiation: list\n",
      "hourly.direct_radiation: list\n",
      "hourly.diffuse_radiation: list\n",
      "hourly.vapor_pressure_deficit: list\n",
      "hourly.evapotranspiration: list\n",
      "hourly.precipitation: list\n",
      "hourly.weathercode: list\n",
      "hourly.snow_height: list\n",
      "hourly.freezinglevel_height: list\n",
      "hourly.soil_temperature_0cm: list\n",
      "hourly.soil_temperature_6cm: list\n",
      "hourly.soil_temperature_18cm: list\n",
      "hourly.soil_temperature_54cm: list\n",
      "hourly.soil_moisture_0_1cm: list\n",
      "hourly.soil_moisture_1_3cm: list\n",
      "hourly.soil_moisture_3_9cm: list\n",
      "hourly.soil_moisture_9_27cm: list\n",
      "hourly.soil_moisture_27_81cm: list\n",
      "daily_units.time: str\n",
      "daily_units.temperature_2m_max: str\n",
      "daily_units.temperature_2m_min: str\n",
      "daily_units.apparent_temperature_max: str\n",
      "daily_units.apparent_temperature_min: str\n",
      "daily_units.precipitation_sum: str\n",
      "daily_units.precipitation_hours: str\n",
      "daily_units.weathercode: str\n",
      "daily_units.sunrise: str\n",
      "daily_units.sunset: str\n",
      "daily_units.windspeed_10m_max: str\n",
      "daily_units.windgusts_10m_max: str\n",
      "daily_units.winddirection_10m_dominant: str\n",
      "daily_units.shortwave_radiation_sum: str\n",
      "daily.time: list\n",
      "daily.temperature_2m_max: list\n",
      "daily.temperature_2m_min: list\n",
      "daily.apparent_temperature_max: list\n",
      "daily.apparent_temperature_min: list\n",
      "daily.precipitation_sum: list\n",
      "daily.precipitation_hours: list\n",
      "daily.weathercode: list\n",
      "daily.sunrise: list\n",
      "daily.sunset: list\n",
      "daily.windspeed_10m_max: list\n",
      "daily.windgusts_10m_max: list\n",
      "daily.winddirection_10m_dominant: list\n",
      "daily.shortwave_radiation_sum: list\n"
     ]
    }
   ],
   "source": [
    "def get_schema(dictionary, parent_key=''):\n",
    "    schema = {}\n",
    "    for key, value in dictionary.items():\n",
    "        full_key = f'{parent_key}.{key}' if parent_key else key\n",
    "        if isinstance(value, dict):\n",
    "            schema.update(get_schema(value, full_key))\n",
    "        else:\n",
    "            schema[full_key] = type(value).__name__\n",
    "    return schema\n",
    "\n",
    "# Usage\n",
    "schema = get_schema(meteo)\n",
    "for key, value in schema.items():\n",
    "    print(f\"{key}: {value}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# assuming that your dictionary is called `meteo`\n",
    "daily_data = meteo[\"daily\"]\n",
    "\n",
    "# check if 'time' and 'apparent_temperature_max' are in daily_data\n",
    "if 'time' in daily_data and 'apparent_temperature_max' in daily_data:\n",
    "    df = pd.DataFrame({\n",
    "        'time': daily_data['time'],\n",
    "        'apparent_temperature_max': daily_data['apparent_temperature_max']\n",
    "    })\n",
    "else:\n",
    "    print(\"'time' or 'apparent_temperature_max' not found in daily data\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# assuming that your dictionary is called `meteo`\n",
    "daily_data = meteo[\"daily\"]\n",
    "\n",
    "# check if 'time', 'apparent_temperature_max' and 'apparent_temperature_min' are in daily_data\n",
    "if 'time' in daily_data and 'apparent_temperature_max' in daily_data and 'apparent_temperature_min' in daily_data:\n",
    "    df_meteo = pd.DataFrame({\n",
    "        'time': daily_data['time'],\n",
    "        'apparent_temperature_max': daily_data['apparent_temperature_max'],\n",
    "        'apparent_temperature_min': daily_data['apparent_temperature_min'],\n",
    "        'precipitation_sum': daily_data['precipitation_sum'],\n",
    "        'windspeed_10m_max': daily_data['windspeed_10m_max'],\n",
    "    })\n",
    "else:\n",
    "    print(\"'time', 'apparent_temperature_max' or 'apparent_temperature_min' not found in daily data\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>apparent_temperature_max</th>\n",
       "      <th>apparent_temperature_min</th>\n",
       "      <th>precipitation_sum</th>\n",
       "      <th>windspeed_10m_max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-06-30</td>\n",
       "      <td>26.1</td>\n",
       "      <td>12.3</td>\n",
       "      <td>1.4</td>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-07-01</td>\n",
       "      <td>23.8</td>\n",
       "      <td>16.6</td>\n",
       "      <td>1.1</td>\n",
       "      <td>10.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-07-02</td>\n",
       "      <td>19.6</td>\n",
       "      <td>13.8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>25.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-07-03</td>\n",
       "      <td>21.1</td>\n",
       "      <td>12.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-07-04</td>\n",
       "      <td>25.9</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2023-07-05</td>\n",
       "      <td>22.9</td>\n",
       "      <td>14.2</td>\n",
       "      <td>0.3</td>\n",
       "      <td>18.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2023-07-06</td>\n",
       "      <td>27.3</td>\n",
       "      <td>11.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.4</td>\n",
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       "         time  apparent_temperature_max  apparent_temperature_min  \\\n",
       "0  2023-06-30                      26.1                      12.3   \n",
       "1  2023-07-01                      23.8                      16.6   \n",
       "2  2023-07-02                      19.6                      13.8   \n",
       "3  2023-07-03                      21.1                      12.4   \n",
       "4  2023-07-04                      25.9                      11.0   \n",
       "5  2023-07-05                      22.9                      14.2   \n",
       "6  2023-07-06                      27.3                      11.8   \n",
       "\n",
       "   precipitation_sum  windspeed_10m_max  \n",
       "0                1.4               17.4  \n",
       "1                1.1               10.7  \n",
       "2                2.5               25.7  \n",
       "3                0.0               28.9  \n",
       "4                0.0               18.4  \n",
       "5                0.3               18.6  \n",
       "6                0.0                4.4  "
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     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df_meteo"
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  },
  {
   "cell_type": "code",
   "execution_count": 9,
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            "gridcolor": "white",
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           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
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          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
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           "yaxis": {
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            "gridcolor": "white",
            "gridwidth": 2,
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            "showbackground": true,
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           "zaxis": {
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            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
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           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Temperature Forecast"
        },
        "xaxis": {
         "title": {
          "text": "Time"
         }
        },
        "yaxis": {
         "title": {
          "text": "Temperature (Celsius)"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "#pip install --upgrade nbformat\n",
    "\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=df_meteo['time'], y=df_meteo['apparent_temperature_max'], name='Max Temperature', line=dict(color='red')))\n",
    "fig.add_trace(go.Scatter(x=df_meteo['time'], y=df_meteo['apparent_temperature_min'], name='Min Temperature', line=dict(color='blue')))\n",
    "\n",
    "fig.update_layout(\n",
    "    title='Temperature Forecast',\n",
    "    xaxis=dict(title='Time'),\n",
    "    yaxis=dict(title='Temperature (Celsius)')\n",
    ")\n",
    "\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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          "title": {
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          "xaxis": {
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           "linecolor": "white",
           "ticks": "",
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           "zerolinewidth": 2
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        },
        "title": {
         "text": "Temperature Forecast"
        },
        "xaxis": {
         "title": {
          "text": "Time"
         }
        },
        "yaxis": {
         "title": {
          "text": "Precipitation (mm)"
         }
        },
        "yaxis2": {
         "overlaying": "y",
         "side": "right",
         "title": {
          "text": "Wind (km/h)"
         }
        }
       }
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     },
     "metadata": {},
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   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "#  'precipitation_sum': daily_data['precipitation_sum'],\n",
    "#         'windspeed_10m_max': daily_data['windspeed_10m_max'],\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=df_meteo['time'], y=df_meteo['precipitation_sum'], name='Precip', line=dict(color='#2B61A1')))\n",
    "fig.add_trace(go.Scatter(x=df_meteo['time'], y=df_meteo['windspeed_10m_max'], name='Wind', line=dict(color='#003399'), yaxis='y2'))\n",
    "\n",
    "fig.update_layout(\n",
    "    title='Temperature Forecast',\n",
    "    xaxis=dict(title='Time'),\n",
    "    yaxis=dict(title='Precipitation (mm)'),\n",
    "    yaxis2=dict(title='Wind (km/h)', overlaying='y',side='right')\n",
    ")\n",
    "\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# assuming that your dictionary is called `meteo`\n",
    "hourly_data = meteo[\"hourly\"]\n",
    "\n",
    "# check if 'time', 'apparent_temperature_max' and 'apparent_temperature_min' are in daily_data\n",
    "if 'time' in daily_data and 'apparent_temperature' in hourly_data:\n",
    "    df_meteo_h = pd.DataFrame({\n",
    "        'time': hourly_data['time'],\n",
    "        'apparent_temperature': hourly_data['apparent_temperature'],\n",
    "        'windspeed_10m': hourly_data['windspeed_10m'],\n",
    "        'winddirection_10m': hourly_data['winddirection_10m'],\n",
    "        'precipitation': hourly_data['precipitation']\n",
    "    })\n",
    "else:\n",
    "    print(\"'time', 'apparent_temperature' not found in daily data\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>apparent_temperature</th>\n",
       "      <th>windspeed_10m</th>\n",
       "      <th>winddirection_10m</th>\n",
       "      <th>precipitation</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>2023-06-30T00:00</td>\n",
       "      <td>14.2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>12.3</td>\n",
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       "      <td>242</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-06-30T04:00</td>\n",
       "      <td>14.3</td>\n",
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       "      <th>164</th>\n",
       "      <td>2023-07-06T20:00</td>\n",
       "      <td>18.9</td>\n",
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       "      <th>167</th>\n",
       "      <td>2023-07-06T23:00</td>\n",
       "      <td>15.9</td>\n",
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       "      <td>219</td>\n",
       "      <td>0.0</td>\n",
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       "</table>\n",
       "<p>168 rows × 5 columns</p>\n",
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      "text/plain": [
       "                 time  apparent_temperature  windspeed_10m  winddirection_10m  \\\n",
       "0    2023-06-30T00:00                  14.2            4.3                294   \n",
       "1    2023-06-30T01:00                  13.4            4.7                261   \n",
       "2    2023-06-30T02:00                  12.8            5.5                247   \n",
       "3    2023-06-30T03:00                  12.3            5.3                242   \n",
       "4    2023-06-30T04:00                  14.3            5.9                232   \n",
       "..                ...                   ...            ...                ...   \n",
       "163  2023-07-06T19:00                  21.7            3.4                122   \n",
       "164  2023-07-06T20:00                  18.9            4.0                153   \n",
       "165  2023-07-06T21:00                  16.8            4.3                175   \n",
       "166  2023-07-06T22:00                  16.0            3.7                191   \n",
       "167  2023-07-06T23:00                  15.9            2.3                219   \n",
       "\n",
       "     precipitation  \n",
       "0              0.0  \n",
       "1              0.0  \n",
       "2              0.0  \n",
       "3              0.0  \n",
       "4              0.0  \n",
       "..             ...  \n",
       "163            0.0  \n",
       "164            0.0  \n",
       "165            0.0  \n",
       "166            0.0  \n",
       "167            0.0  \n",
       "\n",
       "[168 rows x 5 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_meteo_h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "#pip install --upgrade nbformat\n",
    "#restart kernel\n",
    "\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=df_meteo_h['time'], y=df_meteo_h['apparent_temperature'], name='Temperature', line=dict(color='green')))\n",
    "\n",
    "fig.update_layout(\n",
    "    title='Temperature Forecast',\n",
    "    xaxis=dict(title='Time'),\n",
    "    yaxis=dict(title='Temperature (Celsius)')\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
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           "bgcolor": "#E5ECF6",
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          "title": {
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          "xaxis": {
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     "metadata": {},
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   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=df_meteo_h['time'], y=df_meteo_h['windspeed_10m'], name='Wind Speed', line=dict(color='green')))\n",
    "\n",
    "fig.update_layout(\n",
    "    title='Wind Speed Forecast',\n",
    "    xaxis=dict(title='Time'),\n",
    "    yaxis=dict(title='Wind (km/h)')\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
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            "linecolor": "white",
            "ticks": ""
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            "gridcolor": "white",
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            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
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           "linecolor": "white",
           "ticks": "",
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          },
          "yaxis": {
           "automargin": true,
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     },
     "metadata": {},
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   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=df_meteo_h['time'], y=df_meteo_h['winddirection_10m'], name='Wind Direction', line=dict(color='green')))\n",
    "\n",
    "fig.update_layout(\n",
    "    title='Wind Direction Forecast',\n",
    "    xaxis=dict(title='Time'),\n",
    "    yaxis=dict(title='Wind (Degrees)')\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=df_meteo_h['time'], y=df_meteo_h['precipitation'], name='Precipitation Speed', line=dict(color='green')))\n",
    "\n",
    "fig.update_layout(\n",
    "    title='Precipitation Forecast',\n",
    "    xaxis=dict(title='Time'),\n",
    "    yaxis=dict(title='Precipitation (mm)')\n",
    ")\n",
    "\n",
    "fig.show()"
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  },
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   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Meteostat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install meteostat\n",
    "#https://github.com/meteostat/meteostat-python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          name country region    wmo  icao  latitude  longitude  elevation  \\\n",
      "id                                                                           \n",
      "17300  Antalya      TR    ANT  17300  LTAI      36.7    30.7333       50.0   \n",
      "\n",
      "              timezone hourly_start hourly_end daily_start  daily_end  \\\n",
      "id                                                                      \n",
      "17300  Europe/Istanbul   1951-01-01 2023-06-28  1951-01-01 2023-06-25   \n",
      "\n",
      "      monthly_start monthly_end      distance  \n",
      "id                                             \n",
      "17300    1949-01-01  2022-01-01  24491.521703  \n",
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    }
   ],
   "source": [
    "### The Stations Class: latitude, longitude\n",
    "#https://dev.meteostat.net/python/stations.html\n",
    "\n",
    "# Import Meteostat library\n",
    "from meteostat import Stations\n",
    "\n",
    "# Get nearby weather stations\n",
    "stations = Stations()\n",
    "stations = stations.nearby(36.92, 30.72) \n",
    "station = stations.fetch(1) #the closest station to the input location\n",
    "\n",
    "# Print DataFrame\n",
    "print(station)\n",
    "print(type(station))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "nearest_alt = station['latitude'].values[0]\n",
    "nearest_lon = station['longitude'].values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            tavg  tmin  tmax  prcp  snow   wdir  wspd  wpgt    pres  tsun\n",
      "time                                                                     \n",
      "2022-01-01  14.1  12.0  16.1   NaN   NaN  335.0  11.2  13.0  1018.7   NaN\n",
      "2022-01-02  14.3  11.9  16.4   NaN   NaN    0.0  18.1  22.2  1021.5   NaN\n",
      "2022-01-03  14.2  11.4  17.9   NaN   NaN  254.0   9.9  16.7  1019.5   NaN\n",
      "2022-01-04  14.4  12.6  17.7   NaN   NaN  226.0  10.4  18.5  1015.5   NaN\n",
      "2022-01-05  15.8  12.6  18.6   NaN   NaN  199.0  25.2  20.4  1014.0   NaN\n",
      "...          ...   ...   ...   ...   ...    ...   ...   ...     ...   ...\n",
      "2022-12-27  13.6  10.7  18.3   0.0   NaN  220.0   3.8  16.7  1024.4   NaN\n",
      "2022-12-28  13.6  11.2  16.8   0.0   NaN    7.0   3.8  13.0  1024.2   NaN\n",
      "2022-12-29  13.5  10.7  16.4   0.0   NaN  356.0   7.1  13.0  1025.4   NaN\n",
      "2022-12-30  12.6   9.8  16.8   1.3   NaN  173.0   2.2  16.7  1026.5   NaN\n",
      "2022-12-31  13.0  10.4  16.3   4.3   NaN  315.0   3.5  14.8  1028.4   NaN\n",
      "\n",
      "[365 rows x 10 columns]\n",
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    }
   ],
   "source": [
    "### The Point Class: latitude, longitude, altitude\n",
    "#https://dev.meteostat.net/python/point.html\n",
    "\n",
    "from meteostat import Point, Daily\n",
    "from datetime import datetime\n",
    "\n",
    "import plotly.express as px\n",
    "\n",
    "\n",
    "# Set time period\n",
    "start = datetime(2022, 1, 1)\n",
    "end = datetime(2022, 12, 31)\n",
    "\n",
    "# Create Point (KOS island in Greece)\n",
    "#location = Point(36.8925871 , 27.2877926, 70) #lat, long, altitude (optional)\n",
    "location = Point(36.8925871 , 27.2877926)\n",
    "\n",
    "# Get daily data\n",
    "data = Daily(location, start, end)\n",
    "data = data.fetch()\n",
    "\n",
    "print(data)\n",
    "print(type(data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
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         "hovertemplate": "variable=tmin<br>Date=%{x}<br>value=%{y}<extra></extra>",
         "legendgroup": "tmin",
         "line": {
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          "dash": "solid"
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Tmin",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
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           "#636efa",
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           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
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          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Temperature Min/Max for the Given Location",
         "x": 0.5,
         "xanchor": "center"
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "Date"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "Temperature (°C)"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.line(data.reset_index(), x='time', y=['tmin','tmax'],\n",
    "                title=f'Temperature Min/Max for the Given Location',\n",
    "                labels={'time': 'Date', 'tmin': 'Min Temp', 'tmax': 'Max Temp'})\n",
    "\n",
    "fig.data[0].name = 'Tmin'\n",
    "fig.data[1].name = 'Tmax'\n",
    "\n",
    "\n",
    "# Update the legend title\n",
    "fig.update_layout(legend_title='Legend')\n",
    "\n",
    "fig.update_yaxes(title_text='Temperature (°C)')\n",
    "\n",
    "# Center the plot title\n",
    "fig.update_layout(title={'x': 0.5, 'xanchor': 'center'})\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./images/Temperature-Trend.html'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# imports\n",
    "import plotly\n",
    "# Export as static image\n",
    "\n",
    "# # Assuming your plot is in the 'fig' variable\n",
    "#fig.write_image(\"yourfile.png\") \n",
    "\n",
    "\n",
    "# Export as HTML\n",
    "\n",
    "# # Assuming your plot is in the 'fig' variable\n",
    "plotly.offline.plot(fig, filename='./images/Temperature-Trend.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "variable=wspd<br>Date=%{x}<br>value=%{y}<extra></extra>",
         "legendgroup": "wspd",
         "line": {
          "color": "#636efa",
          "dash": "solid"
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Wind",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
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            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Windspeed for the Given Location",
         "x": 0.5,
         "xanchor": "center"
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "Date"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "Wind Speed (km/h)"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.line(data.reset_index(), x='time', y=['wspd'],\n",
    "                title=f'Windspeed for the Given Location',\n",
    "                labels={'time': 'Date', 'wspd': 'Wind Speed'})\n",
    "\n",
    "fig.data[0].name = 'Wind'\n",
    "\n",
    "# Update the legend title\n",
    "fig.update_layout(legend_title='Legend')\n",
    "\n",
    "fig.update_yaxes(title_text='Wind Speed (km/h)')\n",
    "\n",
    "# Center the plot title\n",
    "fig.update_layout(title={'x': 0.5, 'xanchor': 'center'})\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
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         "x": 0.5,
         "xanchor": "center"
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         "anchor": "y",
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          0,
          1
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     "metadata": {},
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   ],
   "source": [
    "fig = px.line(data.reset_index(), x='time', y=['prcp'],\n",
    "              title=f'Precipitation for the Given Location',\n",
    "              labels={'time': 'Date', 'prcp': 'Rain'})\n",
    "\n",
    "fig.data[0].name = 'Rain'\n",
    "\n",
    "fig.update_yaxes(title_text='Rainfall (mm)')\n",
    "\n",
    "# Update the legend title\n",
    "fig.update_layout(legend_title='Legend')\n",
    "\n",
    "# Center the plot title\n",
    "fig.update_layout(title={'x': 0.5, 'xanchor': 'center'})\n",
    "\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from datetime import date, timedelta\n",
    "\n",
    "# today = date.today()\n",
    "# five_days_ago = date.today() - timedelta(days=5)\n",
    "# print(five_days_ago)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Data columns:\n",
      " Index(['time', 'tavg', 'tmin', 'tmax', 'prcp', 'snow', 'wdir', 'wspd', 'wpgt',\n",
      "       'pres', 'tsun'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "lat = 35.0\n",
    "lon = 25.0\n",
    "start = datetime(2021, 1, 1)\n",
    "end = datetime(2021, 12, 31)\n",
    "\n",
    "\n",
    "location = Point(lat, lon, 70)\n",
    "\n",
    "data = Daily(location, start, end)\n",
    "data = data.fetch()\n",
    "\n",
    "data = data.reset_index()\n",
    "\n",
    "print(\"\\nData columns:\\n\", data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'data' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[13], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[39m# Rename the columns\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[39mprint\u001b[39m(data\u001b[39m.\u001b[39mrename(columns\u001b[39m=\u001b[39m{\u001b[39m'\u001b[39m\u001b[39mtmin\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mTmin\u001b[39m\u001b[39m'\u001b[39m,\n\u001b[1;32m      3\u001b[0m                            \u001b[39m'\u001b[39m\u001b[39mtmax\u001b[39m\u001b[39m'\u001b[39m: \u001b[39m'\u001b[39m\u001b[39mTmax\u001b[39m\u001b[39m'\u001b[39m}))\t\n",
      "\u001b[0;31mNameError\u001b[0m: name 'data' is not defined"
     ]
    }
   ],
   "source": [
    "# Rename the columns\n",
    "print(data.rename(columns={'tmin': 'Tmin',\n",
    "                           'tmax': 'Tmax'}))\t"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Not all coordinates have data in meteostat"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using nearby stations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty DataFrame\n",
      "Columns: [tavg, tmin, tmax, prcp, snow, wdir, wspd, wpgt, pres, tsun]\n",
      "Index: []\n",
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    }
   ],
   "source": [
    "### The Point Class: latitude, longitude, altitude\n",
    "#https://dev.meteostat.net/python/point.html\n",
    "\n",
    "from meteostat import Point, Daily\n",
    "from datetime import datetime\n",
    "\n",
    "import plotly.express as px\n",
    "\n",
    "\n",
    "# Set time period\n",
    "start = datetime(2022, 1, 1)\n",
    "end = datetime(2022, 12, 31)\n",
    "\n",
    "# Create Point (near Istambul in Turkey)\n",
    "location = Point(40 , 30)\n",
    "\n",
    "# Get daily data\n",
    "data = Daily(location, start, end)\n",
    "data = data.fetch()\n",
    "\n",
    "print(data) #no data is queried\n",
    "print(type(data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from meteostat import Stations\n",
    "\n",
    "lat=40\n",
    "lon=30\n",
    "\n",
    "# Get nearby weather stations\n",
    "stations = Stations()\n",
    "stations = stations.nearby(lat , lon)\n",
    "station = stations.fetch(1) \n",
    "\n",
    "nearest_lat = station['latitude'].values[0]\n",
    "nearest_lon = station['longitude'].values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            tavg  tmin  tmax  prcp  snow   wdir  wspd  wpgt    pres  tsun\n",
      "time                                                                     \n",
      "2022-01-01   7.4   6.0  10.0   2.6   NaN   10.0   3.0   NaN  1019.4   NaN\n",
      "2022-01-02   7.8   4.0  11.0   2.1   NaN  357.0   4.4   NaN  1023.0   NaN\n",
      "2022-01-03   3.5   0.0   9.0   0.0   NaN  169.0   3.8   NaN  1019.7   NaN\n",
      "2022-01-04   2.3   0.0   8.0   0.0   NaN  252.0   2.8   NaN  1016.8   NaN\n",
      "2022-01-05   4.7  -2.0  17.0   0.0   NaN  226.0   3.2   NaN  1014.1   NaN\n",
      "...          ...   ...   ...   ...   ...    ...   ...   ...     ...   ...\n",
      "2022-12-27   2.3  -3.0  13.0   0.0   NaN  322.0   1.8   NaN  1026.4   NaN\n",
      "2022-12-28   7.0   3.1  13.0   1.4   NaN   28.0   4.4   NaN  1027.1   NaN\n",
      "2022-12-29   6.0   0.0  13.8   0.0   NaN  251.0   2.9   NaN  1026.8   NaN\n",
      "2022-12-30   3.6  -1.0  13.0   0.0   NaN   17.0   2.4   NaN  1027.7   NaN\n",
      "2022-12-31   4.5   0.0  11.0   0.0   NaN   83.0   2.1   NaN  1030.3   NaN\n",
      "\n",
      "[365 rows x 10 columns]\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "40.25 29.55 versus:  40 30\n"
     ]
    }
   ],
   "source": [
    "# Create Point of nearby location for a station\n",
    "location = Point(nearest_lat , nearest_lon) # ---> 42.25 and 29.55 is the closest to our (40,30) input.\n",
    "\n",
    "# Get daily data\n",
    "data = Daily(location, start, end)\n",
    "data = data.fetch()\n",
    "\n",
    "print(data) #no data is queried\n",
    "print(type(data))\n",
    "print(nearest_lat,nearest_lon,'versus: ',lat,lon)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Downloading csv with valid coordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning: Cannot load daily/11722.csv.gz from https://bulk.meteostat.net/v2/\n",
      "Warning: Cannot load daily/12425.csv.gz from https://bulk.meteostat.net/v2/\n",
      "Warning: Cannot load daily/12106.csv.gz from https://bulk.meteostat.net/v2/\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(49, 14), (49, 15), (49, 16), (49, 17), (49, 20), (49, 21), (49, 22), (49, 24), (50, 14), (50, 15), (50, 16), (50, 18), (50, 19), (50, 20), (50, 21), (50, 22), (50, 23), (50, 24), (51, 14), (51, 15), (51, 16), (51, 17), (51, 19), (51, 21), (51, 24), (52, 14), (52, 15), (52, 16), (52, 18), (52, 19), (52, 21), (52, 22), (52, 24), (53, 14), (53, 15), (53, 17), (53, 19), (53, 20), (53, 22), (53, 23), (54, 14), (54, 16), (54, 19), (54, 21), (54, 23)]\n"
     ]
    }
   ],
   "source": [
    "from meteostat import Point, Daily\n",
    "from datetime import datetime\n",
    "import pandas as pd\n",
    "\n",
    "def find_valid_coordinates(lat_range, lon_range, start, end):\n",
    "    valid_coordinates = []\n",
    "\n",
    "    for lat in lat_range:\n",
    "        for lon in lon_range:\n",
    "            location = Point(lat, lon)\n",
    "            data = Daily(location, start, end)\n",
    "            data = data.fetch()\n",
    "\n",
    "            if not data.empty:\n",
    "                valid_coordinates.append((lat, lon))\n",
    "\n",
    "    return valid_coordinates\n",
    "\n",
    "# Set the range of Polish latitude and longitude\n",
    "polish_lat_range = [49, 50, 51, 52, 53, 54]\n",
    "polish_lon_range = [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]\n",
    "\n",
    "# Set time period\n",
    "start = datetime(2023, 1, 1)\n",
    "end = datetime(2023, 1, 31)\n",
    "\n",
    "# Find valid coordinates\n",
    "valid_coords = find_valid_coordinates(polish_lat_range, polish_lon_range, start, end)\n",
    "print(valid_coords)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(valid_coords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(valid_coords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# writing the existing locations in csv\n",
    "\n",
    "import csv\n",
    "\n",
    "with open('valid_coords.csv', 'w', newline='') as csvfile:\n",
    "    coord_writer = csv.writer(csvfile)\n",
    "    coord_writer.writerow(['lat', 'lon'])\n",
    "    for coord in valid_coords:\n",
    "        coord_writer.writerow(coord)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Load valid coordinates from the CSV file\n",
    "valid_coords = pd.read_csv('valid_coords.csv')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DASH"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### V1"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### V1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8054/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x26984574d00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import dash\n",
    "# from dash import html #import dash_core_components as dcc\n",
    "# from dash import dcc\n",
    "# from dash.dependencies import Input, Output\n",
    "# from datetime import datetime, timedelta, date\n",
    "# from meteostat import Point, Daily\n",
    "\n",
    "# import plotly.express as px\n",
    "# import dash_leaflet as dl\n",
    "# from jupyter_dash import JupyterDash\n",
    "\n",
    "app = JupyterDash(__name__, external_stylesheets=['https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css'])\n",
    "\n",
    "def plot_tmax_boxplot(lat, lon, start, end, variable):\n",
    "    location = Point(lat, lon, 70)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data=data.reset_index()\n",
    "\n",
    "    data['Month'] = data['time'].dt.month\n",
    "\n",
    "    fig = px.box(data, x='Month', y=variable, title='Monthly Tmax Boxplot')\n",
    "    return fig\n",
    "\n",
    "def plot_weather_data(lat, lon, start, end):\n",
    "    location = Point(lat, lon, 70)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data=data.reset_index()\n",
    "\n",
    "    fig = px.line(data, x='time', y=['tmin','tmax'],\n",
    "                  title=f'Temperature min/max for the Given Location ({lat:.2f},{lon:.2f})',\n",
    "                  labels={'time': 'Date', 'tmin': 'Min Temp', 'tmax': 'Max Temp'})\n",
    "\n",
    "    fig.update_yaxes(title_text='Temperature')\n",
    "\n",
    "\n",
    "    return (fig)\n",
    "\n",
    "app.layout = html.Div([\n",
    "    html.H1('Trip Planner', style={'textAlign': 'center', 'padding': '20px'}),\n",
    "    dcc.DatePickerRange(\n",
    "        id='date-picker',\n",
    "        min_date_allowed=datetime(2000, 1, 1),\n",
    "        max_date_allowed= date.today() - timedelta(days=7), #datetime(2022, 12, 31),\n",
    "        start_date=datetime(2021, 1, 1),\n",
    "        end_date=datetime(2022, 12, 31),\n",
    "        display_format='MMM DD, YYYY'\n",
    "    ),\n",
    "    dl.Map(\n",
    "        [dl.TileLayer(), dl.LayerGroup(id=\"layer\")],\n",
    "        id='map',\n",
    "        style={'width': '100%', 'height': '50vh', 'margin': \"auto\", \"display\": \"block\"},\n",
    "        center=[35, 25],\n",
    "        zoom=4,\n",
    "        #click_lat_lng=True,\n",
    "    ),\n",
    "    dcc.Graph(id='weather-plot'),\n",
    "    html.Label('Select variable for boxplot:'),\n",
    "    dcc.Dropdown(\n",
    "        id='boxplot-variable',\n",
    "        options=[\n",
    "            {'label': 'Tmax', 'value': 'tmax'},\n",
    "            {'label': 'Tmin', 'value': 'tmin'}\n",
    "        ],\n",
    "        value='tmax'\n",
    "    ),\n",
    "    dcc.Graph(id='tmax-boxplot')\n",
    "])\n",
    "\n",
    "@app.callback(\n",
    "    Output('layer', 'children'),\n",
    "    [Input('map', 'click_lat_lng')],\n",
    ")\n",
    "def update_markers(click_lat_lng):\n",
    "    if not click_lat_lng:\n",
    "        click_lat_lng = [35, 25]\n",
    "    return [dl.Marker(position=click_lat_lng, children=dl.Tooltip(f\"({click_lat_lng[0]:.2f}, {click_lat_lng[1]:.2f})\"))]\n",
    "\n",
    "@app.callback(\n",
    "    [Output('weather-plot', 'figure'), Output('tmax-boxplot', 'figure')],\n",
    "    [Input('map', 'click_lat_lng'), Input('date-picker', 'start_date'), Input('date-picker', 'end_date'), Input('boxplot-variable', 'value')],\n",
    ")\n",
    "def update_weather_plots(click_lat_lng, start_date, end_date, boxplot_variable):\n",
    "    if not click_lat_lng:\n",
    "        lat, lon = 35, 25\n",
    "    else:\n",
    "        lat = int(click_lat_lng[0])\n",
    "        lon = int(click_lat_lng[1])\n",
    "    \n",
    "   \n",
    "    start = datetime(int(start_date[0:4]),\n",
    "                    int(start_date[5:7]),\n",
    "                    int(start_date[8:10]))\n",
    "    end = datetime(2022, 12, 31)\n",
    "    \n",
    "    line_plot = plot_weather_data(lat, lon, start, end)\n",
    "    \n",
    "    \n",
    "    box_plot = plot_tmax_boxplot(lat, lon, start, end, boxplot_variable)\n",
    "    \n",
    "    return line_plot, box_plot\n",
    "    \n",
    "\n",
    "# Start of the application\n",
    "if __name__ == '__main__':\n",
    "    app.run_server(mode=\"inline\", port=8054)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### V1.1: Temp, Wind, Rain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8054/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1f433c12e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import dash\n",
    "from dash import html \n",
    "from dash import dcc\n",
    "from dash.dependencies import Input, Output\n",
    "from datetime import datetime, timedelta, date\n",
    "from meteostat import Point, Daily\n",
    "\n",
    "import plotly.express as px\n",
    "import dash_leaflet as dl\n",
    "from jupyter_dash import JupyterDash\n",
    "\n",
    "app = JupyterDash(__name__, external_stylesheets=['https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css'])\n",
    "\n",
    "def plot_tmax_boxplot(lat, lon, start, end, variable):\n",
    "    location = Point(lat, lon, 70)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data = data.reset_index()\n",
    "\n",
    "    data['month'] = data['time'].dt.month_name()\n",
    "\n",
    "    fig = px.box(data, x='month', y=variable, title='Monthly Summaries -  Boxplot')\n",
    "\n",
    "    fig.update_xaxes(title_text='Month')\n",
    "    fig.update_yaxes(title_text=('Max Temperature (°C)' if variable == 'tmax' else\n",
    "                              'Min Temperature (°C)' if variable == 'tmin' else\n",
    "                              'Wind (km/h)' if variable == 'wspd' else\n",
    "                              'Rain (mm)'))\n",
    "    return fig\n",
    "\n",
    "def plot_weather_data(lat, lon, start, end):\n",
    "    location = Point(lat, lon, 70)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data = data.reset_index()\n",
    "\n",
    "    # Rename the columns\n",
    "    data = data.rename(columns={'tmin': 'Tmin',\n",
    "                           'tmax': 'Tmax'})\n",
    "\n",
    "    fig = px.line(data, x='time', y=['Tmin', 'Tmax'],\n",
    "                  title=f'Temperature Min/Max for the Given Location ({lat:.2f}, {lon:.2f})',\n",
    "                  labels={'time': 'Date'})\n",
    "    fig.update_yaxes(title_text='Temperature °C')\n",
    "\n",
    "    fig.data[0].name = 'Tmin'\n",
    "    fig.data[1].name = 'Tmax'\n",
    "\n",
    "    # Update the legend title\n",
    "    fig.update_layout(legend_title='Legend')\n",
    "\n",
    "    return fig\n",
    "\n",
    "\n",
    "app.layout = html.Div([\n",
    "    html.H1('Trip Planner', style={'textAlign': 'center', 'padding': '20px'}),\n",
    "    dcc.DatePickerRange(\n",
    "        id='date-picker',\n",
    "        min_date_allowed=datetime(2000, 1, 1),\n",
    "        max_date_allowed= date.today() - timedelta(days=7),\n",
    "        start_date=datetime(2021, 1, 1),\n",
    "        end_date=datetime(2022, 12, 31),\n",
    "        display_format='MMM DD, YYYY',\n",
    "        style = {\n",
    "                        'font-size': '6px','display': 'inline-block', 'border-radius' : '2px', \n",
    "                        'border' : '1px solid #ccc', 'color': '#333', \n",
    "                        'border-spacing' : '0', 'border-collapse' :'separate'\n",
    "                        } \n",
    "    ),\n",
    "    dl.Map(\n",
    "        [dl.TileLayer(), dl.LayerGroup(id=\"layer\")],\n",
    "        id='map',\n",
    "        style={'width': '100%', 'height': '50vh', 'margin': \"auto\", \"display\": \"block\"},\n",
    "        center=[35, 25],\n",
    "        zoom=4,\n",
    "        #click_lat_lng=True,\n",
    "    ),\n",
    "    dcc.Graph(id='weather-plot'),\n",
    "    html.Label('Select a variable to display in the Boxplot:'),\n",
    "    dcc.Dropdown(\n",
    "        id='boxplot-variable',\n",
    "        options=[\n",
    "            {'label': 'Temperature Max °C', 'value': 'tmax'},\n",
    "            {'label': 'Temperature Min °C', 'value': 'tmin'},\n",
    "            {'label': 'Wind (km/h)', 'value': 'wspd'},\n",
    "            {'label': 'Rain (mm)', 'value': 'prcp'},\n",
    "        ],\n",
    "        value='tmax'\n",
    "    ),\n",
    "    dcc.Graph(id='tmax-boxplot'),\n",
    "    html.Div([\n",
    "        html.H4(\"About\"),\n",
    "        html.A(\"My Blog - FossEngineer\", href=\"https://fossengineer.com\", target=\"_blank\"),\n",
    "        html.Br(),\n",
    "        html.A(\"About this App - FossEngineer\", href=\"https://fossengineer.com/python-trip-planner/\", target=\"_blank\"),\n",
    "        html.Br(),\n",
    "        html.A(\"Source Code\", href=\"https://github.com/JAlcocerT/Py_Trip_Planner/\", target=\"_blank\"),\n",
    "    ], style={'float': 'right'})\n",
    "])\n",
    "\n",
    "@app.callback(\n",
    "    Output('layer', 'children'),\n",
    "    [Input('map', 'click_lat_lng')],\n",
    ")\n",
    "def update_markers(click_lat_lng):\n",
    "    if not click_lat_lng:\n",
    "        click_lat_lng = [35, 25]\n",
    "    return [dl.Marker(position=click_lat_lng, children=dl.Tooltip(f\"({click_lat_lng[0]:.2f}, {click_lat_lng[1]:.2f})\"))]\n",
    "\n",
    "@app.callback(\n",
    "    [Output('weather-plot', 'figure'), Output('tmax-boxplot', 'figure')],\n",
    "    [Input('map', 'click_lat_lng'), Input('date-picker', 'start_date'), Input('date-picker', 'end_date'), Input('boxplot-variable', 'value')],\n",
    ")\n",
    "def update_weather_plots(click_lat_lng, start_date, end_date, boxplot_variable):\n",
    "    if not click_lat_lng:\n",
    "        lat, lon = 35, 25\n",
    "    else:\n",
    "        lat = int(click_lat_lng[0])\n",
    "        lon = int(click_lat_lng[1])\n",
    "    \n",
    "   \n",
    "    start = datetime(int(start_date[0:4]),\n",
    "                    int(start_date[5:7]),\n",
    "                    int(start_date[8:10]))\n",
    "    end = datetime(2022, 12, 31)\n",
    "    \n",
    "    line_plot = plot_weather_data(lat, lon, start, end)\n",
    "    \n",
    "    \n",
    "    box_plot = plot_tmax_boxplot(lat, lon, start, end, boxplot_variable)\n",
    "    \n",
    "    return line_plot, box_plot\n",
    "    \n",
    "\n",
    "# Start of the application\n",
    "if __name__ == '__main__':\n",
    "    app.run_server(mode=\"inline\", port=8054)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### V1.2 Adding nearby locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/reisipi/.local/lib/python3.10/site-packages/dash/dash.py:516: UserWarning:\n",
      "\n",
      "JupyterDash is deprecated, use Dash instead.\n",
      "See https://dash.plotly.com/dash-in-jupyter for more details.\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8054/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7f4313fe80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8054/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7f43518790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)\n",
      "\u001b[1;31mNameError\u001b[0m: name 'nearest_alt' is not defined\n",
      "\n",
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)\n",
      "\u001b[1;31mNameError\u001b[0m: name 'nearest_alt' is not defined\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import dash\n",
    "from dash import html \n",
    "from dash import dcc\n",
    "from dash.dependencies import Input, Output\n",
    "\n",
    "from datetime import datetime, timedelta, date\n",
    "\n",
    "from meteostat import Point, Daily\n",
    "from meteostat import Stations #new in v1.2\n",
    "\n",
    "import plotly.express as px\n",
    "import dash_leaflet as dl\n",
    "\n",
    "from jupyter_dash import JupyterDash\n",
    "\n",
    "app = JupyterDash(__name__, external_stylesheets=['https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css'])\n",
    "\n",
    "def plot_tmax_boxplot(lat, lon, start, end, variable):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data = data.reset_index()\n",
    "\n",
    "    data['month'] = data['time'].dt.month_name()\n",
    "\n",
    "    fig = px.box(data, x='month', y=variable, title='Monthly Summaries -  Boxplot')\n",
    "\n",
    "    fig.update_xaxes(title_text='Month')\n",
    "    fig.update_yaxes(title_text=('Max Temperature (°C)' if variable == 'tmax' else\n",
    "                              'Min Temperature (°C)' if variable == 'tmin' else\n",
    "                              'Wind (km/h)' if variable == 'wspd' else\n",
    "                              'Rain (mm)'))\n",
    "    return fig\n",
    "\n",
    "def plot_weather_data(lat, lon, start, end):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data = data.reset_index()\n",
    "\n",
    "    # Rename the columns\n",
    "    data = data.rename(columns={'tmin': 'Tmin',\n",
    "                           'tmax': 'Tmax'})\n",
    "\n",
    "    fig = px.line(data, x='time', y=['Tmin', 'Tmax'],\n",
    "                  title=f'Temperature Min/Max for the Given Location ({lat:.2f}, {lon:.2f})',\n",
    "                  labels={'time': 'Date'})\n",
    "    fig.update_yaxes(title_text='Temperature °C')\n",
    "\n",
    "    fig.data[0].name = 'Tmin'\n",
    "    fig.data[1].name = 'Tmax'\n",
    "\n",
    "    # Update the legend title\n",
    "    fig.update_layout(legend_title='Legend')\n",
    "\n",
    "    return fig\n",
    "\n",
    "\n",
    "app.layout = html.Div([\n",
    "    html.H1('Trip Planner', style={'textAlign': 'center', 'padding': '20px'}),\n",
    "    dcc.DatePickerRange(\n",
    "        id='date-picker',\n",
    "        min_date_allowed=datetime(2000, 1, 1),\n",
    "        max_date_allowed= date.today() - timedelta(days=7),\n",
    "        start_date=datetime(2021, 1, 1),\n",
    "        end_date=datetime(2022, 12, 31),\n",
    "        display_format='MMM DD, YYYY',\n",
    "        style = {\n",
    "                        'font-size': '6px','display': 'inline-block', 'border-radius' : '2px', \n",
    "                        'border' : '1px solid #ccc', 'color': '#333', \n",
    "                        'border-spacing' : '0', 'border-collapse' :'separate'\n",
    "                        } \n",
    "    ),\n",
    "    dl.Map(\n",
    "        [dl.TileLayer(), dl.LayerGroup(id=\"layer\")],\n",
    "        id='map',\n",
    "        style={'width': '100%', 'height': '50vh', 'margin': \"auto\", \"display\": \"block\"},\n",
    "        center=[35, 25],\n",
    "        zoom=4,\n",
    "        #click_lat_lng=True,\n",
    "    ),\n",
    "    dcc.Graph(id='weather-plot'),\n",
    "    html.Label('Select a variable to display in the Boxplot:'),\n",
    "    dcc.Dropdown(\n",
    "        id='boxplot-variable',\n",
    "        options=[\n",
    "            {'label': 'Temperature Max °C', 'value': 'tmax'},\n",
    "            {'label': 'Temperature Min °C', 'value': 'tmin'},\n",
    "            {'label': 'Wind (km/h)', 'value': 'wspd'},\n",
    "            {'label': 'Rain (mm)', 'value': 'prcp'},\n",
    "        ],\n",
    "        value='tmax'\n",
    "    ),\n",
    "    dcc.Graph(id='tmax-boxplot'),\n",
    "    html.Div([\n",
    "        html.H4(\"About\"),\n",
    "        html.A(\"My Blog - FossEngineer\", href=\"https://fossengineer.com\", target=\"_blank\"),\n",
    "        html.Br(),\n",
    "        html.A(\"About this App - FossEngineer\", href=\"https://fossengineer.com/python-trip-planner/\", target=\"_blank\"),\n",
    "        html.Br(),\n",
    "        html.A(\"Source Code\", href=\"https://github.com/JAlcocerT/Py_Trip_Planner/\", target=\"_blank\"),\n",
    "    ], style={'float': 'right'})\n",
    "])\n",
    "\n",
    "@app.callback(\n",
    "    Output('layer', 'children'),\n",
    "    [Input('map', 'click_lat_lng')],\n",
    ")\n",
    "# def update_markers(click_lat_lng):\n",
    "#     if not click_lat_lng:\n",
    "#         click_lat_lng = [35, 25]\n",
    "#     return [dl.Marker(position=click_lat_lng, children=dl.Tooltip(f\"({click_lat_lng[0]:.2f}, {click_lat_lng[1]:.2f})\"))]\n",
    "\n",
    "def update_markers(click_lat_lng):\n",
    "    if not click_lat_lng:\n",
    "        click_lat_lng = [35, 25]\n",
    "    return [\n",
    "        dl.Marker(position=click_lat_lng, children=dl.Tooltip(f\"({click_lat_lng[0]:.2f}, {click_lat_lng[1]:.2f})\")),\n",
    "        #dl.Marker(position=[nearest_alt, nearest_lon], children=dl.Tooltip(f\"({nearest_alt:.2f}, {nearest_lon:.2f})\"))\n",
    "        dl.CircleMarker(center=[nearest_alt, nearest_lon], color=\"#188399\",)\n",
    "    ]\n",
    "\n",
    "@app.callback(\n",
    "    [Output('weather-plot', 'figure'), Output('tmax-boxplot', 'figure')],\n",
    "    [Input('map', 'click_lat_lng'), Input('date-picker', 'start_date'), Input('date-picker', 'end_date'), Input('boxplot-variable', 'value')],\n",
    ")\n",
    "def update_weather_plots(click_lat_lng, start_date, end_date, boxplot_variable):\n",
    "    global nearest_alt, nearest_lon\n",
    "    if not click_lat_lng:\n",
    "        lat, lon = 35, 25\n",
    "    else:\n",
    "        lat = int(click_lat_lng[0])\n",
    "        lon = int(click_lat_lng[1])\n",
    "    \n",
    "   # Get nearby weather stations  - V1.2\n",
    "    stations = Stations()\n",
    "    stations = stations.nearby(lat, lon) \n",
    "    station = stations.fetch(1) #the closest station to the input location\n",
    "\n",
    "    nearest_alt = station['latitude'].values[0]\n",
    "    nearest_lon = station['longitude'].values[0]\n",
    "    ###\n",
    "\n",
    "    start = datetime(int(start_date[0:4]),\n",
    "                    int(start_date[5:7]),\n",
    "                    int(start_date[8:10]))\n",
    "    end = datetime(2022, 12, 31)\n",
    "    \n",
    "    #line_plot = plot_weather_data(lat, lon, start, end)\n",
    "    line_plot = plot_weather_data(nearest_alt, nearest_lon, start, end)\n",
    "    \n",
    "    #box_plot = plot_tmax_boxplot(lat, lon, start, end, boxplot_variable)\n",
    "    box_plot = plot_tmax_boxplot(nearest_alt, nearest_lon, start, end, boxplot_variable)\n",
    "    \n",
    "    return line_plot, box_plot\n",
    "    \n",
    "\n",
    "# Start of the application\n",
    "if __name__ == '__main__':\n",
    "    app.run_server(mode=\"inline\", port=8054)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### V1.3 Improving UI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8035/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x22d3d8d4100>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import dash\n",
    "from dash import html \n",
    "from dash import dcc\n",
    "from dash.dependencies import Input, Output\n",
    "\n",
    "from datetime import datetime, timedelta, date\n",
    "\n",
    "from meteostat import Point, Daily\n",
    "from meteostat import Stations #new in v1.2\n",
    "\n",
    "import plotly.express as px\n",
    "import dash_leaflet as dl\n",
    "\n",
    "from jupyter_dash import JupyterDash\n",
    "\n",
    "colour_ext = 'cecece'\n",
    "colour_int='dbdbdb'\n",
    "\n",
    "app = JupyterDash(__name__, external_stylesheets=['https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css'])\n",
    "\n",
    "def plot_tmax_boxplot(lat, lon, start, end, variable):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    df_meteo_boxplot = data.reset_index()\n",
    "\n",
    "    #df_meteo_boxplot = data_meteostat(lat, lon, start, end)\n",
    "\n",
    "    df_meteo_boxplot['month'] = df_meteo_boxplot['time'].dt.month_name()\n",
    "\n",
    "    fig = px.box(df_meteo_boxplot, x='month', y=variable, title='Monthly Summaries -  Boxplot')\n",
    "\n",
    "    fig.update_xaxes(title_text='Month')\n",
    "    fig.update_yaxes(title_text=('Max Temperature (°C)' if variable == 'tmax' else\n",
    "                              'Min Temperature (°C)' if variable == 'tmin' else\n",
    "                              'Wind (km/h)' if variable == 'wspd' else\n",
    "                              'Rain (mm)'))\n",
    "\n",
    "    fig.update_traces(marker_color='#21B1CF', line_color='#21B1CF')\n",
    "\n",
    "\n",
    "    fig.update_layout(plot_bgcolor='#2E2E33',\n",
    "                      paper_bgcolor='#F5F5F5')\n",
    "    \n",
    "    return fig\n",
    "\n",
    "def plot_weather_data(lat, lon, start, end):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data = data.reset_index()\n",
    "\n",
    "    # Rename the columns\n",
    "    df_meteostat = data.rename(columns={'tmin': 'Tmin',\n",
    "                           'tmax': 'Tmax'})\n",
    "\n",
    "    #df_meteostat = data_meteostat(lat,lon,start,end)\n",
    "\n",
    "    fig = px.line(df_meteostat, x='time', y=['Tmin', 'Tmax'],\n",
    "                  title=f'Temperature Min/Max for the Given Location ({lat:.2f}, {lon:.2f})',\n",
    "                  labels={'time': 'Date'},\n",
    "                  color_discrete_sequence=['#66E5FF', 'orange'])\n",
    "    fig.update_yaxes(title_text='Temperature °C')\n",
    "\n",
    "    fig.data[0].name = 'Tmin'\n",
    "    fig.data[1].name = 'Tmax'\n",
    "\n",
    "    #Line colors\n",
    "    #fig.update_traces(line_color=['blue', 'orange']) \n",
    "\n",
    "    # Update the legend title\n",
    "    fig.update_layout(legend_title='Legend',\n",
    "                      plot_bgcolor='#2E2E33',\n",
    "                      paper_bgcolor='#F5F5F5')\n",
    "\n",
    "    return fig\n",
    "\n",
    "def data_meteostat(lat,lon,start,end):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data = data.reset_index()\n",
    "\n",
    "    # Rename the columns\n",
    "    data = data.rename(columns={'tmin': 'Tmin',\n",
    "                           'tmax': 'Tmax'})\n",
    "    \n",
    "    return(data)\n",
    "\n",
    "\n",
    "app.layout = html.Div(\n",
    "    style={'backgroundColor': '#F5F5F5'},\n",
    "    children=[\n",
    "    html.H1('Trip Planner', style={'textAlign': 'center', 'padding': '20px','backgroundColor':'F5F5F5'}),\n",
    "    dcc.DatePickerRange(\n",
    "        id='date-picker',\n",
    "        min_date_allowed=datetime(2000, 1, 1),\n",
    "        max_date_allowed= date.today() - timedelta(days=7),\n",
    "        start_date=datetime(2021, 1, 1),\n",
    "        end_date=datetime(2022, 12, 31),\n",
    "        display_format='MMM DD, YYYY',\n",
    "        style = {\n",
    "                        'font-size': '6px','display': 'inline-block', 'border-radius' : '2px', \n",
    "                        'border' : '1px solid #ccc', 'color': '#2E2E33', \n",
    "                        'border-spacing' : '0', 'border-collapse' :'separate'\n",
    "                        } \n",
    "    ),\n",
    "    dl.Map(\n",
    "        [dl.TileLayer(), dl.LayerGroup(id=\"layer\")],\n",
    "        id='map',\n",
    "        style={'width': '100%', 'height': '50vh', 'margin': \"auto\", \"display\": \"block\"},\n",
    "        center=[35, 25],\n",
    "        zoom=4,\n",
    "        #click_lat_lng=True,\n",
    "    ),\n",
    "    dcc.Graph(id='weather-plot'),\n",
    "    html.Label('Select a variable to display in the Boxplot:'),\n",
    "    dcc.Dropdown(\n",
    "        id='boxplot-variable',\n",
    "        options=[\n",
    "            {'label': 'Temperature Max °C', 'value': 'tmax'},\n",
    "            {'label': 'Temperature Min °C', 'value': 'tmin'},\n",
    "            {'label': 'Wind (km/h)', 'value': 'wspd'},\n",
    "            {'label': 'Rain (mm)', 'value': 'prcp'},\n",
    "        ],\n",
    "        value='tmax'\n",
    "    ),\n",
    "    dcc.Graph(id='tmax-boxplot'),\n",
    "   \n",
    "   html.Div(\n",
    "    [\n",
    "        html.Div(\n",
    "            [\n",
    "                html.H4(\"About\"),\n",
    "                html.A(\"My Blog - FossEngineer\", href=\"https://fossengineer.com\", target=\"_blank\"),\n",
    "                html.Br(),\n",
    "                html.A(\"About this App - FossEngineer\", href=\"https://fossengineer.com/python-trip-planner/\", target=\"_blank\"),\n",
    "                html.Br(),\n",
    "                html.A(\"Source Code\", href=\"https://github.com/JAlcocerT/Py_Trip_Planner/\", target=\"_blank\"),\n",
    "            ],\n",
    "            style={'backgroundColor': '#F5F5F5', 'text-align': 'center'}\n",
    "        ),\n",
    "    ],\n",
    "    #style={'float': 'center', 'display': 'inline-block', 'backgroundColor': '#F5F5F5'}\n",
    "    style={'display': 'flex', 'justify-content': 'center', 'align-items': 'center', 'display': 'inline-block', 'backgroundColor': '#F5F5F5'}\n",
    "\n",
    ")\n",
    "\n",
    "    \n",
    "])\n",
    "\n",
    "@app.callback(\n",
    "    Output('layer', 'children'),\n",
    "    [Input('map', 'click_lat_lng')],\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "def update_markers(click_lat_lng):\n",
    "    if not click_lat_lng:\n",
    "        click_lat_lng = [35, 25]\n",
    "    return [\n",
    "        dl.Marker(position=click_lat_lng, children=dl.Tooltip(f\"({click_lat_lng[0]:.2f}, {click_lat_lng[1]:.2f})\")),\n",
    "        #dl.Marker(position=[nearest_alt, nearest_lon], children=dl.Tooltip(f\"({nearest_alt:.2f}, {nearest_lon:.2f})\"))\n",
    "        dl.CircleMarker(center=[nearest_lat, nearest_lon], color=\"#188399\",)\n",
    "    ]\n",
    "\n",
    "@app.callback(\n",
    "    [Output('weather-plot', 'figure'), Output('tmax-boxplot', 'figure')],\n",
    "    #[Output('weather-plot', 'figure'), Output('tmax-boxplot', 'figure'), Output('forecast-plot','figure')],\n",
    "    [Input('map', 'click_lat_lng'), Input('date-picker', 'start_date'), Input('date-picker', 'end_date'), Input('boxplot-variable', 'value')],\n",
    ")\n",
    "def update_weather_plots(click_lat_lng, start_date, end_date, boxplot_variable):\n",
    "    global nearest_lat, nearest_lon\n",
    "    if not click_lat_lng:\n",
    "        lat, lon = 35, 25\n",
    "    else:\n",
    "        lat = int(click_lat_lng[0])\n",
    "        lon = int(click_lat_lng[1])\n",
    "    \n",
    "   # Get nearby weather stations  - V1.2\n",
    "    stations = Stations()\n",
    "    stations = stations.nearby(lat, lon) \n",
    "    station = stations.fetch(1) #the closest station to the input location\n",
    "\n",
    "    nearest_lat = station['latitude'].values[0]\n",
    "    nearest_lon = station['longitude'].values[0]\n",
    "    ###\n",
    "    #print(nearest_lat,nearest_lon,'versus: ',lat,lon)\n",
    "\n",
    "\n",
    "    start = datetime(int(start_date[0:4]),\n",
    "                    int(start_date[5:7]),\n",
    "                    int(start_date[8:10]))\n",
    "    end = datetime(2022, 12, 31)\n",
    "    \n",
    "    #line_plot = plot_weather_data(lat, lon, start, end)\n",
    "    line_plot = plot_weather_data(nearest_lat, nearest_lon, start, end)\n",
    "    \n",
    "    #box_plot = plot_tmax_boxplot(lat, lon, start, end, boxplot_variable)\n",
    "    box_plot = plot_tmax_boxplot(nearest_lat, nearest_lon, start, end, boxplot_variable)\n",
    "    \n",
    "    return line_plot, box_plot\n",
    "    \n",
    "\n",
    "# Start of the application\n",
    "if __name__ == '__main__':\n",
    "    app.run_server(mode=\"inline\", port=8035)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8035/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1a88468fdc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import dash\n",
    "from dash import html \n",
    "from dash import dcc\n",
    "from dash.dependencies import Input, Output\n",
    "\n",
    "from datetime import datetime, timedelta, date\n",
    "\n",
    "from meteostat import Point, Daily\n",
    "from meteostat import Stations #new in v1.2\n",
    "\n",
    "import plotly.express as px\n",
    "import dash_leaflet as dl\n",
    "\n",
    "from jupyter_dash import JupyterDash\n",
    "\n",
    "#colour_ext = 'cecece'\n",
    "#colour_int='dbdbdb'\n",
    "\n",
    "app = JupyterDash(__name__, external_stylesheets=['https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css'])\n",
    "\n",
    "def plot_tmax_boxplot(lat, lon, start, end, variable):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    df_meteo_boxplot = data.reset_index()\n",
    "\n",
    "    df_meteo_boxplot['month'] = df_meteo_boxplot['time'].dt.month_name()\n",
    "\n",
    "    fig = px.box(df_meteo_boxplot, x='month', y=variable, title='Monthly Summaries -  Boxplot')\n",
    "\n",
    "    fig.update_xaxes(title_text='Month')\n",
    "    fig.update_yaxes(title_text=('Max Temperature (°C)' if variable == 'tmax' else\n",
    "                              'Min Temperature (°C)' if variable == 'tmin' else\n",
    "                              'Wind (km/h)' if variable == 'wspd' else\n",
    "                              'Rain (mm)'))\n",
    "\n",
    "    fig.update_traces(marker_color='#21B1CF', line_color='#21B1CF')\n",
    "\n",
    "\n",
    "    fig.update_layout(plot_bgcolor='#2E2E33',\n",
    "                      paper_bgcolor='#F5F5F5')\n",
    "    \n",
    "    return fig\n",
    "\n",
    "def plot_weather_data(lat, lon, start, end):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = Daily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data = data.reset_index()\n",
    "\n",
    "    # Rename the columns\n",
    "    df_meteostat = data.rename(columns={'tmin': 'Tmin',\n",
    "                           'tmax': 'Tmax'})\n",
    "\n",
    "    fig = px.line(df_meteostat, x='time', y=['Tmin', 'Tmax'],\n",
    "                  title=f'Temperature Min/Max for the Given Location ({lat:.2f}, {lon:.2f})',\n",
    "                  labels={'time': 'Date'},\n",
    "                  color_discrete_sequence=['#66E5FF', 'orange'])\n",
    "    fig.update_yaxes(title_text='Temperature °C')\n",
    "\n",
    "    fig.data[0].name = 'Tmin'\n",
    "    fig.data[1].name = 'Tmax'\n",
    "\n",
    "\n",
    "    # Update the legend title\n",
    "    fig.update_layout(legend_title='Legend',\n",
    "                      plot_bgcolor='#2E2E33',\n",
    "                      paper_bgcolor='#F5F5F5')\n",
    "\n",
    "    return fig\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "app.layout = html.Div(\n",
    "    style={'backgroundColor': '#F5F5F5'},\n",
    "    children=[\n",
    "    html.H1('Trip Planner', style={'textAlign': 'center', 'padding': '20px','backgroundColor':'F5F5F5'}),\n",
    "    dcc.DatePickerRange(\n",
    "        id='date-picker',\n",
    "        min_date_allowed=datetime(2000, 1, 1),\n",
    "        max_date_allowed= date.today() - timedelta(days=7),\n",
    "        start_date=datetime(2021, 1, 1),\n",
    "        end_date=datetime(2022, 12, 31),\n",
    "        display_format='MMM DD, YYYY',\n",
    "        style = {\n",
    "                        'font-size': '6px','display': 'inline-block', 'border-radius' : '2px', \n",
    "                        'border' : '1px solid #ccc', 'color': '#2E2E33', \n",
    "                        'border-spacing' : '0', 'border-collapse' :'separate'\n",
    "                        } \n",
    "    ),\n",
    "    dl.Map(\n",
    "        [dl.TileLayer(), dl.LayerGroup(id=\"layer\")],\n",
    "        id='map',\n",
    "        style={'width': '100%', 'height': '50vh', 'margin': \"auto\", \"display\": \"block\"},\n",
    "        center=[35, 25],\n",
    "        zoom=4,\n",
    "        #click_lat_lng=True,\n",
    "    ),\n",
    "    dcc.Graph(id='weather-plot'),\n",
    "    html.Label('Select a variable to display in the Boxplot:'),\n",
    "    dcc.Dropdown(\n",
    "        id='boxplot-variable',\n",
    "        options=[\n",
    "            {'label': 'Temperature Max °C', 'value': 'tmax'},\n",
    "            {'label': 'Temperature Min °C', 'value': 'tmin'},\n",
    "            {'label': 'Wind (km/h)', 'value': 'wspd'},\n",
    "            {'label': 'Rain (mm)', 'value': 'prcp'},\n",
    "        ],\n",
    "        value='tmax'\n",
    "    ),\n",
    "    dcc.Graph(id='tmax-boxplot'),\n",
    "   \n",
    "   html.Div(\n",
    "    [\n",
    "        html.Div(\n",
    "            [\n",
    "                html.H4(\"About\"),\n",
    "                html.A(\"My Blog - FossEngineer\", href=\"https://fossengineer.com\", target=\"_blank\"),\n",
    "                html.Br(),\n",
    "                html.A(\"About this App - FossEngineer\", href=\"https://fossengineer.com/python-trip-planner/\", target=\"_blank\"),\n",
    "                html.Br(),\n",
    "                html.A(\"Source Code\", href=\"https://github.com/JAlcocerT/Py_Trip_Planner/\", target=\"_blank\"),\n",
    "            ],\n",
    "            style={'backgroundColor': '#F5F5F5', 'text-align': 'center'}\n",
    "        ),\n",
    "    ],\n",
    "    #style={'float': 'center', 'display': 'inline-block', 'backgroundColor': '#F5F5F5'}\n",
    "    style={'display': 'flex', 'justify-content': 'center', 'align-items': 'center', 'display': 'inline-block', 'backgroundColor': '#F5F5F5'}\n",
    "\n",
    ")\n",
    "\n",
    "    \n",
    "])\n",
    "\n",
    "@app.callback(\n",
    "    Output('layer', 'children'),\n",
    "    [Input('map', 'click_lat_lng')],\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "def update_markers(click_lat_lng):\n",
    "    if not click_lat_lng:\n",
    "        click_lat_lng = [35, 25]\n",
    "    return [\n",
    "        dl.Marker(position=click_lat_lng, children=dl.Tooltip(f\"({click_lat_lng[0]:.2f}, {click_lat_lng[1]:.2f})\")),\n",
    "        #dl.Marker(position=[nearest_alt, nearest_lon], children=dl.Tooltip(f\"({nearest_alt:.2f}, {nearest_lon:.2f})\"))\n",
    "        dl.CircleMarker(center=[nearest_lat, nearest_lon], color=\"#188399\",)\n",
    "    ]\n",
    "\n",
    "@app.callback(\n",
    "    [Output('weather-plot', 'figure'), Output('tmax-boxplot', 'figure')],\n",
    "    [Input('map', 'click_lat_lng'), Input('date-picker', 'start_date'), Input('date-picker', 'end_date'), Input('boxplot-variable', 'value')],\n",
    ")\n",
    "def update_weather_plots(click_lat_lng, start_date, end_date, boxplot_variable):\n",
    "    global nearest_lat, nearest_lon\n",
    "    if not click_lat_lng:\n",
    "        lat, lon = 35, 25\n",
    "    else:\n",
    "        lat = int(click_lat_lng[0])\n",
    "        lon = int(click_lat_lng[1])\n",
    "    \n",
    "   # Get nearby weather stations  - V1.2\n",
    "    stations = Stations()\n",
    "    stations = stations.nearby(lat, lon) \n",
    "    station = stations.fetch(1) #the closest station to the input location\n",
    "\n",
    "    nearest_lat = station['latitude'].values[0]\n",
    "    nearest_lon = station['longitude'].values[0]\n",
    "    ###\n",
    "    #print(nearest_lat,nearest_lon,'versus: ',lat,lon)\n",
    "\n",
    "\n",
    "    start = datetime(int(start_date[0:4]),\n",
    "                    int(start_date[5:7]),\n",
    "                    int(start_date[8:10]))\n",
    "    end = datetime(2022, 12, 31)\n",
    "    \n",
    "    #line_plot = plot_weather_data(lat, lon, start, end)\n",
    "    line_plot = plot_weather_data(nearest_lat, nearest_lon, start, end)\n",
    "    \n",
    "    #box_plot = plot_tmax_boxplot(lat, lon, start, end, boxplot_variable)\n",
    "    box_plot = plot_tmax_boxplot(nearest_lat, nearest_lon, start, end, boxplot_variable)\n",
    "    \n",
    "    return line_plot, box_plot\n",
    "    \n",
    "\n",
    "# Start of the application\n",
    "if __name__ == '__main__':\n",
    "    app.run_server(mode=\"inline\", port=8035)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### V2 Adding Weather Forecast with OpenMeteo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# V2\n",
    "\n",
    "import dash\n",
    "from dash import html \n",
    "from dash import dcc\n",
    "from dash.dependencies import Input, Output\n",
    "\n",
    "from datetime import datetime, timedelta, date\n",
    "\n",
    "from meteostat import Point#, Daily\n",
    "from meteostat import Daily as MeteoDaily\n",
    "from meteostat import Stations #new in v1.2\n",
    "\n",
    "from openmeteo_py import Hourly,Options,OWmanager #new in V2\n",
    "from openmeteo_py import Daily as OpenMeteoDaily\n",
    "\n",
    "import pandas as pd  #new in V2\n",
    "\n",
    "import plotly.graph_objects as go  #new in V2\n",
    "import plotly.express as px\n",
    "import dash_leaflet as dl\n",
    "\n",
    "from jupyter_dash import JupyterDash\n",
    "\n",
    "\n",
    "\n",
    "app = JupyterDash(__name__, external_stylesheets=['https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css'])\n",
    "\n",
    "def plot_tmax_boxplot(lat, lon, start, end, variable):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = MeteoDaily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    df_meteo_boxplot = data.reset_index()\n",
    "\n",
    "    df_meteo_boxplot['month'] = df_meteo_boxplot['time'].dt.month_name()\n",
    "\n",
    "    fig = px.box(df_meteo_boxplot, x='month', y=variable, title='Monthly Summaries -  Boxplot')\n",
    "\n",
    "    fig.update_xaxes(title_text='Month')\n",
    "    fig.update_yaxes(title_text=('Max Temperature (°C)' if variable == 'tmax' else\n",
    "                              'Min Temperature (°C)' if variable == 'tmin' else\n",
    "                              'Wind (km/h)' if variable == 'wspd' else\n",
    "                              'Rain (mm)'))\n",
    "\n",
    "    fig.update_traces(marker_color='#21B1CF', line_color='#21B1CF')\n",
    "\n",
    "\n",
    "    fig.update_layout(plot_bgcolor='#2E2E33',\n",
    "                      paper_bgcolor='#F5F5F5')\n",
    "    \n",
    "    return fig\n",
    "\n",
    "def plot_weather_data(lat, lon, start, end):\n",
    "    location = Point(lat, lon)\n",
    "    \n",
    "    data = MeteoDaily(location, start, end)\n",
    "    data = data.fetch()\n",
    "\n",
    "    data = data.reset_index()\n",
    "\n",
    "    # Rename the columns\n",
    "    df_meteostat = data.rename(columns={'tmin': 'Tmin',\n",
    "                           'tmax': 'Tmax'})\n",
    "\n",
    "    fig = px.line(df_meteostat, x='time', y=['Tmin', 'Tmax'],\n",
    "                  title=f'Temperature Min/Max for the Given Location ({lat:.2f}, {lon:.2f})',\n",
    "                  labels={'time': 'Date'},\n",
    "                  color_discrete_sequence=['#66E5FF', 'orange'])\n",
    "    fig.update_yaxes(title_text='Temperature °C')\n",
    "\n",
    "    fig.data[0].name = 'Tmin'\n",
    "    fig.data[1].name = 'Tmax'\n",
    "\n",
    "\n",
    "    # Update the legend title\n",
    "    fig.update_layout(legend_title='Legend',\n",
    "                      plot_bgcolor='#2E2E33',\n",
    "                      paper_bgcolor='#F5F5F5')\n",
    "\n",
    "    return fig\n",
    "\n",
    "\n",
    "def plot_forecast_data_hourly(lat,lon): #new for V2\n",
    "    import plotly.graph_objects as go\n",
    "\n",
    "    hourly = Hourly()\n",
    "    daily = OpenMeteoDaily()\n",
    "    options = Options(lat,lon)\n",
    "\n",
    "    mgr = OWmanager(options,\n",
    "        hourly.all(),\n",
    "        daily.all())\n",
    "        \n",
    "    # Download data\n",
    "    meteo = mgr.get_data()\n",
    "\n",
    "    hourly_data = meteo[\"hourly\"]\n",
    "\n",
    "    df_meteo_h = pd.DataFrame({\n",
    "            'time': hourly_data['time'],\n",
    "            'apparent_temperature': hourly_data['apparent_temperature'],\n",
    "            'windspeed_10m': hourly_data['windspeed_10m'],\n",
    "            'winddirection_10m': hourly_data['winddirection_10m'],\n",
    "            'precipitation': hourly_data['precipitation']\n",
    "        })\n",
    "   \n",
    "\n",
    "    # fig = px.line(df_meteo_h, x='time', y=['apparent_temperature', 'windspeed_10m'],\n",
    "    #           labels={'value': 'Temperature (Celsius)', 'variable': 'Variables'},\n",
    "    #           color_discrete_sequence=['#21B1CF', '#b1b3b5'])\n",
    "\n",
    "    # fig.update_layout(\n",
    "    #     title='Forecast - Temperature and Wind Speed',\n",
    "    #     xaxis=dict(title='Time'),\n",
    "    #     yaxis=dict(title='Temperature (Celsius)', side='left', color='#21B1CF'),\n",
    "    #     yaxis2=dict(title='Wind Speed (km/h)', side='right', overlaying='y', color='#b1b3b5', showgrid=False)\n",
    "    # )\n",
    "\n",
    "    fig = go.Figure()\n",
    "\n",
    "    fig.add_trace(go.Scatter(x=df_meteo_h['time'], y=df_meteo_h['apparent_temperature'], name='Temperature', line=dict(color='#21B1CF')))\n",
    "    fig.add_trace(go.Scatter(x=df_meteo_h['time'], y=df_meteo_h['windspeed_10m'], name='Wind Speed', line=dict(color='#b1b3b5'), yaxis='y2'))\n",
    "\n",
    "    fig.update_layout(\n",
    "        title='Forecast - Temperature and Wind Speed',\n",
    "        xaxis=dict(title='Time'),\n",
    "        yaxis=dict(title='Temperature (Celsius)', side='left', color='#21B1CF'),\n",
    "        yaxis2=dict(title='Wind Speed (km/h)', side='right', overlaying='y', color='#b1b3b5')\n",
    "    )\n",
    "\n",
    "    fig.update_layout(plot_bgcolor='#2E2E33',\n",
    "                        paper_bgcolor='#F5F5F5')\n",
    "\n",
    "    return fig\n",
    "\n",
    "app.layout = html.Div(\n",
    "    style={'backgroundColor': '#F5F5F5'},\n",
    "    children=[\n",
    "    html.H1('Trip Planner', style={'textAlign': 'center', 'padding': '20px','backgroundColor':'F5F5F5'}),\n",
    "    dcc.DatePickerRange(\n",
    "        id='date-picker',\n",
    "        min_date_allowed=datetime(2000, 1, 1),\n",
    "        max_date_allowed= date.today() - timedelta(days=7),\n",
    "        start_date=datetime(2021, 1, 1),\n",
    "        end_date=datetime(2022, 12, 31),\n",
    "        display_format='MMM DD, YYYY',\n",
    "        style = {\n",
    "                        'font-size': '6px','display': 'inline-block', 'border-radius' : '2px', \n",
    "                        'border' : '1px solid #ccc', 'color': '#2E2E33', \n",
    "                        'border-spacing' : '0', 'border-collapse' :'separate'\n",
    "                        } \n",
    "    ),\n",
    "    dl.Map(\n",
    "        [dl.TileLayer(), dl.LayerGroup(id=\"layer\")],\n",
    "        id='map',\n",
    "        style={'width': '100%', 'height': '50vh', 'margin': \"auto\", \"display\": \"block\"},\n",
    "        center=[35, 25],\n",
    "        zoom=4,\n",
    "    ),\n",
    "    html.H2('Historical Weather Data', style={'textAlign': 'center', 'padding': '20px'}),\n",
    "    dcc.Graph(id='weather-plot'),\n",
    "    html.Label('Select a variable to display in the Boxplot:'),\n",
    "    dcc.Dropdown(\n",
    "        id='boxplot-variable',\n",
    "        options=[\n",
    "            {'label': 'Temperature Max °C', 'value': 'tmax'},\n",
    "            {'label': 'Temperature Min °C', 'value': 'tmin'},\n",
    "            {'label': 'Wind (km/h)', 'value': 'wspd'},\n",
    "            {'label': 'Rain (mm)', 'value': 'prcp'},\n",
    "        ],\n",
    "        value='tmax'\n",
    "    ),\n",
    "    dcc.Graph(id='tmax-boxplot'),\n",
    "    html.H2('Forecasted Weather Data', style={'textAlign': 'center', 'padding': '20px'}),\n",
    "    dcc.Graph(id='forecast-plot'),\n",
    "   html.Div(\n",
    "    [\n",
    "        html.Div(\n",
    "            [\n",
    "                html.H4(\"About\"),\n",
    "                html.A(\"My Blog - FossEngineer\", href=\"https://fossengineer.com\", target=\"_blank\"),\n",
    "                html.Br(),\n",
    "                html.A(\"About this App - FossEngineer\", href=\"https://fossengineer.com/python-trip-planner/\", target=\"_blank\"),\n",
    "                html.Br(),\n",
    "                html.A(\"Source Code\", href=\"https://github.com/JAlcocerT/Py_Trip_Planner/\", target=\"_blank\"),\n",
    "            ],\n",
    "            style={'backgroundColor': '#F5F5F5', 'text-align': 'center'}\n",
    "        ),\n",
    "    ],\n",
    "    style={'display': 'flex', 'justify-content': 'center', 'align-items': 'center', 'display': 'inline-block', 'backgroundColor': '#F5F5F5'}\n",
    ")\n",
    "])\n",
    "\n",
    "@app.callback(\n",
    "    Output('layer', 'children'),\n",
    "    [Input('map', 'click_lat_lng')],\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "def update_markers(click_lat_lng):\n",
    "    if not click_lat_lng:\n",
    "        click_lat_lng = [35, 25]\n",
    "    return [\n",
    "        dl.Marker(position=click_lat_lng, children=dl.Tooltip(f\"({click_lat_lng[0]:.2f}, {click_lat_lng[1]:.2f})\")),\n",
    "        dl.CircleMarker(center=[nearest_lat, nearest_lon], color=\"#188399\",)\n",
    "    ]\n",
    "\n",
    "@app.callback(\n",
    "    [Output('weather-plot', 'figure'), Output('tmax-boxplot', 'figure'), Output('forecast-plot','figure')],\n",
    "    [Input('map', 'click_lat_lng'), Input('date-picker', 'start_date'), Input('date-picker', 'end_date'), Input('boxplot-variable', 'value')],\n",
    ")\n",
    "def update_weather_plots(click_lat_lng, start_date, end_date, boxplot_variable):\n",
    "    global nearest_lat, nearest_lon\n",
    "    if not click_lat_lng:\n",
    "        lat, lon = 35, 25\n",
    "    else:\n",
    "        lat = int(click_lat_lng[0])\n",
    "        lon = int(click_lat_lng[1])\n",
    "    \n",
    "   # Get nearby weather stations  - V1.2\n",
    "    stations = Stations()\n",
    "    stations = stations.nearby(lat, lon) \n",
    "    station = stations.fetch(1) #the closest station to the input location\n",
    "\n",
    "    nearest_lat = station['latitude'].values[0]\n",
    "    nearest_lon = station['longitude'].values[0]\n",
    "    \n",
    "    start = datetime(int(start_date[0:4]),\n",
    "                    int(start_date[5:7]),\n",
    "                    int(start_date[8:10]))\n",
    "    end = datetime(2022, 12, 31)\n",
    "    \n",
    "    line_plot = plot_weather_data(nearest_lat, nearest_lon, start, end)\n",
    "    \n",
    "    box_plot = plot_tmax_boxplot(nearest_lat, nearest_lon, start, end, boxplot_variable)\n",
    "    \n",
    "    try:\n",
    "        forecast_plot = plot_forecast_data_hourly(nearest_lat, nearest_lon)\n",
    "    except:\n",
    "        forecast_plot = go.Figure()\n",
    "    \n",
    "    return line_plot, box_plot, forecast_plot\n",
    "    \n",
    "\n",
    "# Start of the application\n",
    "if __name__ == '__main__':\n",
    "    app.run_server(mode=\"inline\", port=8038)"
   ]
  }
 ],
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