Mesonet API.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mesonet API"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mesonet provide access to a network of weather stations.  For all but huge data volumes, the service is provided at no cost."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Replace with your Mesonet API token, obtainable here:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://developers.synopticdata.com"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "token = 'ff71330455da49468c2f7355070f2099'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipywidgets as ux\n",
    "from __future__ import print_function\n",
    "from ipywidgets import interact, interactive, fixed, interact_manual\n",
    "from ipywidgets import interactive_output\n",
    "import os\n",
    "import osmnx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "start_date_picker = ux.DatePicker(description=\"Start Date:\")\n",
    "end_date_picker = ux.DatePicker(description=\"End Date:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "def update_dates(start_date_picker, end_date_picker):\n",
    "    make_date_param(start_date_picker.value, end_date_picker.value)\n",
    "    print((start_date_picker, end_date_picker))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "def logo_widget(logo_file_path=''):\n",
    "    if len(logo_file_path) == 0:\n",
    "        logo_file_path = \"data/images/ecoacumen_logo.png\"\n",
    "    if os.path.exists(logo_file_path):\n",
    "        file = open(logo_file_path, \"rb\")\n",
    "        image = file.read()\n",
    "        logo_widget = widgets.Image(\n",
    "            value=image,\n",
    "            format='png',\n",
    "            width=300,\n",
    "            height=400,\n",
    "        )\n",
    "        return(logo_widget)\n",
    "    else:\n",
    "        print(f\"Logo {logo_file_path} not found\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logo data/images/ecoacumen_logo.png not found\n"
     ]
    }
   ],
   "source": [
    "logo = logo_widget()\n",
    "title = ux.HTML(\"<h2>EcoAccumen Weather Data</h2>\")\n",
    "subtitle = ux.HTML(\"<h4>Continuous Environmental Monitoring</h4>\")\n",
    "if logo is not None:\n",
    "    items = [logo, title, subtitle]\n",
    "else:\n",
    "    items = [title, subtitle]\n",
    "    \n",
    "header = ux.VBox(items)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "99f7eb4787a2401a93fba1abf0cb785e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Label(value='Specify a date range (defaults to last month)')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "date_label = ux.Label(\"Specify a date range (defaults to last month)\")\n",
    "display(date_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "99f7eb4787a2401a93fba1abf0cb785e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Label(value='Specify a date range (defaults to last month)')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "45a85ba2413a4b31a6aec49ceee9e7cb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(DatePicker(value=None, description='Start Date:'), DatePicker(value=None, description='End Date…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "date_pickers = ux.HBox([start_date_picker, end_date_picker])\n",
    "display(date_label,date_pickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fed7fecf3fef43caa896e20a7934b2cc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<h2>EcoAccumen Weather Data</h2>'), HTML(value='<h4>Continuous Environmental Monito…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "99f7eb4787a2401a93fba1abf0cb785e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Label(value='Specify a date range (defaults to last month)')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ff871269939946ecaad32ab9cd3c7582",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(DatePicker(value=datetime.date(2019, 6, 19), description='Start Date:'), DatePicker(value=datet…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out = ux.interactive_output(update_dates, {'start_date_picker': start_date_picker, 'end_date_picker': end_date_picker})\n",
    "display(header, date_label, date_specification)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7ae321f9219142e083625cd7a535cbf9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output(outputs=({'output_type': 'error', 'ename': 'AttributeError', 'evalue': \"'NoneType' object has no attrib…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "year = 2018\n",
    "month = '11'\n",
    "start_day = '01'\n",
    "start_hour = '12'\n",
    "start_min = '00'\n",
    "end_day = '30'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "timeseries_url = 'https://api.synopticdata.com/v2/stations/timeseries'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import osmnx\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_date_param(start='', end=''):\n",
    "    if start == '' and end == '':\n",
    "        # default to last month in hours\n",
    "        return(f'&recent={24*30}')\n",
    "    else:\n",
    "        date_param = f'&start={year}{month}{start_day}{start_hour}{start_min}' \n",
    "        date_param += f'&end={year}{month}{end_day}{start_hour}{start_min}'\n",
    "        return(date_param)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'&recent=720'"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "make_date_param()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_url():\n",
    "    url = timeseries_url + '?&token=' + token \n",
    "    url += '&county=placer&state=ca' \n",
    "    url += make_date_param()\n",
    "    url += '&units=english'\n",
    "    url += '&vars=wind_speed,wind_direction'\n",
    "    return(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.synopticdata.com/v2/stations/timeseries?&token=ff71330455da49468c2f7355070f2099&county=placer&state=ca&recent=720&units=english&vars=wind_speed,wind_direction'"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = make_url()\n",
    "url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = requests.get(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_count = len(response.json()['STATION'])\n",
    "station_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'STATUS': 'ACTIVE',\n",
       " 'MNET_ID': '229',\n",
       " 'PERIOD_OF_RECORD': {'start': '2019-05-10T18:14:00Z',\n",
       "  'end': '2019-06-10T20:20:00Z'},\n",
       " 'ELEVATION': '1301',\n",
       " 'NAME': 'Cramer Road',\n",
       " 'STID': 'PG349',\n",
       " 'SENSOR_VARIABLES': {'wind_speed': {'wind_speed_set_1': {}},\n",
       "  'date_time': {'date_time': {}},\n",
       "  'wind_direction': {'wind_direction_set_1': {}}},\n",
       " 'ELEV_DEM': '1305.8',\n",
       " 'LONGITUDE': '-121.11579',\n",
       " 'STATE': 'CA',\n",
       " 'OBSERVATIONS': {'date_time': ['2019-06-11T11:40:00Z',\n",
       "   '2019-06-11T11:50:00Z',\n",
       "   '2019-06-11T12:00:00Z',\n",
       "   '2019-06-11T12:10:00Z',\n",
       "   '2019-06-11T12:20:00Z',\n",
       "   '2019-06-11T12:30:00Z',\n",
       "   '2019-06-11T12:40:00Z',\n",
       "   '2019-06-11T12:50:00Z',\n",
       "   '2019-06-11T13:00:00Z',\n",
       "   '2019-06-11T13:10:00Z',\n",
       "   '2019-06-11T13:20:00Z',\n",
       "   '2019-06-11T13:30:00Z',\n",
       "   '2019-06-11T13:40:00Z',\n",
       "   '2019-06-11T13:50:00Z',\n",
       "   '2019-06-11T14:00:00Z',\n",
       "   '2019-06-11T14:10:00Z',\n",
       "   '2019-06-11T14:20:00Z',\n",
       "   '2019-06-11T14:30:00Z',\n",
       "   '2019-06-11T14:40:00Z',\n",
       "   '2019-06-11T14:50:00Z',\n",
       "   '2019-06-11T15:00:00Z',\n",
       "   '2019-06-11T15:10:00Z',\n",
       "   '2019-06-11T15:20:00Z',\n",
       "   '2019-06-11T15:30:00Z',\n",
       "   '2019-06-11T15:40:00Z',\n",
       "   '2019-06-11T15:50:00Z',\n",
       "   '2019-06-11T16:00:00Z',\n",
       "   '2019-06-11T16:10:00Z',\n",
       "   '2019-06-11T16:20:00Z',\n",
       "   '2019-06-11T16:30:00Z',\n",
       "   '2019-06-11T16:40:00Z',\n",
       "   '2019-06-11T16:50:00Z',\n",
       "   '2019-06-11T17:00:00Z',\n",
       "   '2019-06-11T17:10:00Z',\n",
       "   '2019-06-11T17:20:00Z',\n",
       "   '2019-06-11T17:30:00Z',\n",
       "   '2019-06-11T17:40:00Z',\n",
       "   '2019-06-11T17:50:00Z',\n",
       "   '2019-06-11T18:00:00Z',\n",
       "   '2019-06-11T18:10:00Z',\n",
       "   '2019-06-11T18:20:00Z',\n",
       "   '2019-06-11T18:30:00Z',\n",
       "   '2019-06-11T18:40:00Z',\n",
       "   '2019-06-11T18:50:00Z',\n",
       "   '2019-06-11T19:00:00Z',\n",
       "   '2019-06-11T19:10:00Z',\n",
       "   '2019-06-11T19:20:00Z',\n",
       "   '2019-06-11T19:30:00Z',\n",
       "   '2019-06-11T19:40:00Z',\n",
       "   '2019-06-11T19:50:00Z',\n",
       "   '2019-06-11T20:00:00Z',\n",
       "   '2019-06-11T20:10:00Z',\n",
       "   '2019-06-11T20:20:00Z',\n",
       "   '2019-06-11T20:30:00Z',\n",
       "   '2019-06-11T20:40:00Z',\n",
       "   '2019-06-11T20:50:00Z',\n",
       "   '2019-06-11T21:00:00Z',\n",
       "   '2019-06-11T21:10:00Z',\n",
       "   '2019-06-11T21:20:00Z',\n",
       "   '2019-06-11T21:30:00Z',\n",
       "   '2019-06-11T21:40:00Z',\n",
       "   '2019-06-11T21:50:00Z',\n",
       "   '2019-06-11T22:00:00Z',\n",
       "   '2019-06-11T22:10:00Z',\n",
       "   '2019-06-11T22:20:00Z',\n",
       "   '2019-06-11T22:30:00Z',\n",
       "   '2019-06-11T22:40:00Z',\n",
       "   '2019-06-11T22:50:00Z',\n",
       "   '2019-06-11T23:00:00Z',\n",
       "   '2019-06-11T23:10:00Z',\n",
       "   '2019-06-11T23:20:00Z',\n",
       "   '2019-06-11T23:30:00Z'],\n",
       "  'wind_speed_set_1': [4.18,\n",
       "   4.43,\n",
       "   4.45,\n",
       "   4.76,\n",
       "   4.47,\n",
       "   4.65,\n",
       "   4.63,\n",
       "   4.8,\n",
       "   4.53,\n",
       "   4.55,\n",
       "   4.28,\n",
       "   5.42,\n",
       "   4.74,\n",
       "   3.89,\n",
       "   2.94,\n",
       "   2.53,\n",
       "   3.09,\n",
       "   4.08,\n",
       "   3.91,\n",
       "   4.3,\n",
       "   3.3,\n",
       "   3.95,\n",
       "   3.54,\n",
       "   2.0,\n",
       "   1.44,\n",
       "   1.44,\n",
       "   1.96,\n",
       "   1.46,\n",
       "   0.17,\n",
       "   0.51,\n",
       "   1.42,\n",
       "   2.45,\n",
       "   2.72,\n",
       "   2.7,\n",
       "   1.13,\n",
       "   1.05,\n",
       "   1.96,\n",
       "   1.13,\n",
       "   1.83,\n",
       "   2.29,\n",
       "   1.36,\n",
       "   2.53,\n",
       "   2.49,\n",
       "   2.74,\n",
       "   2.99,\n",
       "   1.73,\n",
       "   2.12,\n",
       "   2.6,\n",
       "   3.69,\n",
       "   1.96,\n",
       "   1.56,\n",
       "   1.89,\n",
       "   3.85,\n",
       "   2.24,\n",
       "   2.64,\n",
       "   3.63,\n",
       "   3.54,\n",
       "   4.59,\n",
       "   3.81,\n",
       "   3.63,\n",
       "   3.93,\n",
       "   3.65,\n",
       "   3.07,\n",
       "   3.83,\n",
       "   4.22,\n",
       "   2.59,\n",
       "   3.19,\n",
       "   2.45,\n",
       "   3.3,\n",
       "   2.6,\n",
       "   2.02,\n",
       "   3.63],\n",
       "  'wind_direction_set_1': [9.17,\n",
       "   8.07,\n",
       "   10.78,\n",
       "   7.8,\n",
       "   11.92,\n",
       "   14.46,\n",
       "   8.86,\n",
       "   20.29,\n",
       "   9.92,\n",
       "   5.48,\n",
       "   29.15,\n",
       "   358.0,\n",
       "   3.76,\n",
       "   2.02,\n",
       "   357.0,\n",
       "   357.1,\n",
       "   354.6,\n",
       "   353.4,\n",
       "   353.7,\n",
       "   345.8,\n",
       "   346.0,\n",
       "   341.4,\n",
       "   6.57,\n",
       "   355.9,\n",
       "   353.5,\n",
       "   351.5,\n",
       "   334.5,\n",
       "   330.3,\n",
       "   326.3,\n",
       "   247.4,\n",
       "   158.0,\n",
       "   168.2,\n",
       "   168.7,\n",
       "   178.3,\n",
       "   230.7,\n",
       "   123.4,\n",
       "   232.7,\n",
       "   238.0,\n",
       "   243.9,\n",
       "   207.9,\n",
       "   190.5,\n",
       "   215.9,\n",
       "   205.0,\n",
       "   226.3,\n",
       "   320.1,\n",
       "   341.8,\n",
       "   232.4,\n",
       "   176.8,\n",
       "   195.1,\n",
       "   344.8,\n",
       "   290.6,\n",
       "   240.3,\n",
       "   197.6,\n",
       "   220.4,\n",
       "   209.1,\n",
       "   208.7,\n",
       "   204.8,\n",
       "   186.2,\n",
       "   188.0,\n",
       "   178.7,\n",
       "   180.8,\n",
       "   203.7,\n",
       "   173.3,\n",
       "   193.3,\n",
       "   190.7,\n",
       "   206.9,\n",
       "   182.8,\n",
       "   241.1,\n",
       "   185.2,\n",
       "   221.2,\n",
       "   211.4,\n",
       "   176.2]},\n",
       " 'RESTRICTED': False,\n",
       " 'QC_FLAGGED': False,\n",
       " 'LATITUDE': '38.98541',\n",
       " 'TIMEZONE': 'America/Los_Angeles',\n",
       " 'ID': '91448'}"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response.json()['STATION'][station_count-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame(columns=['obs_datetime','wind_speed','wind_speed_units','wind_direction','fuel_moisture','fuel_moisture_units'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "index = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'wind_speed': 'knots',\n",
       " 'position': 'ft',\n",
       " 'wind_direction': 'Degrees',\n",
       " 'fuel_moisture': 'gm',\n",
       " 'elevation': 'ft'}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response.json()['UNITS']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['wind_speed_units'] = response.json()['UNITS']['wind_speed']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['fuel_moisture_units'] = response.json()['UNITS']['fuel_moisture']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'STATUS': 'ACTIVE',\n",
       " 'MNET_ID': '25',\n",
       " 'PERIOD_OF_RECORD': {'start': '2000-01-20T00:00:00Z',\n",
       "  'end': '2019-06-10T19:00:00Z'},\n",
       " 'ELEVATION': '8012',\n",
       " 'NAME': 'SQUAW VALLEY G.C.',\n",
       " 'STID': 'SQWC1',\n",
       " 'SENSOR_VARIABLES': {'wind_speed': {'wind_speed_set_1': {}},\n",
       "  'date_time': {'date_time': {}},\n",
       "  'wind_direction': {'wind_direction_set_1': {}}},\n",
       " 'ELEV_DEM': '8034.8',\n",
       " 'LONGITUDE': '-120.26576',\n",
       " 'STATE': 'CA',\n",
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       "   '2018-11-17T06:00:00Z',\n",
       "   '2018-11-17T07:00:00Z',\n",
       "   '2018-11-17T08:00:00Z',\n",
       "   '2018-11-17T09:00:00Z',\n",
       "   '2018-11-17T10:00:00Z',\n",
       "   '2018-11-17T11:00:00Z',\n",
       "   '2018-11-17T12:00:00Z',\n",
       "   '2018-11-17T13:00:00Z',\n",
       "   '2018-11-17T14:00:00Z',\n",
       "   '2018-11-17T15:00:00Z',\n",
       "   '2018-11-17T16:00:00Z',\n",
       "   '2018-11-17T17:00:00Z',\n",
       "   '2018-11-17T18:00:00Z',\n",
       "   '2018-11-17T19:00:00Z',\n",
       "   '2018-11-17T20:00:00Z',\n",
       "   '2018-11-17T21:00:00Z',\n",
       "   '2018-11-17T22:00:00Z',\n",
       "   '2018-11-17T23:00:00Z',\n",
       "   '2018-11-18T00:00:00Z',\n",
       "   '2018-11-18T01:00:00Z',\n",
       "   '2018-11-18T02:00:00Z',\n",
       "   '2018-11-18T03:00:00Z',\n",
       "   '2018-11-18T04:00:00Z',\n",
       "   '2018-11-18T05:00:00Z',\n",
       "   '2018-11-18T06:00:00Z',\n",
       "   '2018-11-18T07:00:00Z',\n",
       "   '2018-11-18T08:00:00Z',\n",
       "   '2018-11-18T09:00:00Z',\n",
       "   '2018-11-18T10:00:00Z',\n",
       "   '2018-11-18T11:00:00Z',\n",
       "   '2018-11-18T12:00:00Z',\n",
       "   '2018-11-18T13:00:00Z',\n",
       "   '2018-11-18T14:00:00Z',\n",
       "   '2018-11-18T15:00:00Z',\n",
       "   '2018-11-18T16:00:00Z',\n",
       "   '2018-11-18T17:00:00Z',\n",
       "   '2018-11-18T18:00:00Z',\n",
       "   '2018-11-18T19:00:00Z',\n",
       "   '2018-11-18T20:00:00Z',\n",
       "   '2018-11-18T21:00:00Z',\n",
       "   '2018-11-18T22:00:00Z',\n",
       "   '2018-11-18T23:00:00Z',\n",
       "   '2018-11-19T00:00:00Z',\n",
       "   '2018-11-19T01:00:00Z',\n",
       "   '2018-11-19T02:00:00Z',\n",
       "   '2018-11-19T03:00:00Z',\n",
       "   '2018-11-19T04:00:00Z',\n",
       "   '2018-11-19T05:00:00Z',\n",
       "   '2018-11-19T06:00:00Z',\n",
       "   '2018-11-19T07:00:00Z',\n",
       "   '2018-11-19T08:00:00Z',\n",
       "   '2018-11-19T09:00:00Z',\n",
       "   '2018-11-19T10:00:00Z',\n",
       "   '2018-11-19T11:00:00Z',\n",
       "   '2018-11-19T12:00:00Z',\n",
       "   '2018-11-19T13:00:00Z',\n",
       "   '2018-11-19T14:00:00Z',\n",
       "   '2018-11-19T15:00:00Z',\n",
       "   '2018-11-19T16:00:00Z',\n",
       "   '2018-11-19T17:00:00Z',\n",
       "   '2018-11-19T18:00:00Z',\n",
       "   '2018-11-19T19:00:00Z',\n",
       "   '2018-11-19T20:00:00Z',\n",
       "   '2018-11-19T21:00:00Z',\n",
       "   '2018-11-19T22:00:00Z',\n",
       "   '2018-11-19T23:00:00Z',\n",
       "   '2018-11-20T00:00:00Z',\n",
       "   '2018-11-20T01:00:00Z',\n",
       "   '2018-11-20T02:00:00Z',\n",
       "   '2018-11-20T03:00:00Z',\n",
       "   '2018-11-20T04:00:00Z',\n",
       "   '2018-11-20T05:00:00Z',\n",
       "   '2018-11-20T06:00:00Z',\n",
       "   '2018-11-20T07:00:00Z',\n",
       "   '2018-11-20T08:00:00Z',\n",
       "   '2018-11-20T09:00:00Z',\n",
       "   '2018-11-20T10:00:00Z',\n",
       "   '2018-11-20T11:00:00Z',\n",
       "   '2018-11-20T12:00:00Z',\n",
       "   '2018-11-20T13:00:00Z',\n",
       "   '2018-11-20T14:00:00Z',\n",
       "   '2018-11-20T15:00:00Z',\n",
       "   '2018-11-20T16:00:00Z',\n",
       "   '2018-11-20T17:00:00Z',\n",
       "   '2018-11-20T18:00:00Z',\n",
       "   '2018-11-20T19:00:00Z',\n",
       "   '2018-11-20T20:00:00Z',\n",
       "   '2018-11-20T21:00:00Z',\n",
       "   '2018-11-20T22:00:00Z',\n",
       "   '2018-11-20T23:00:00Z',\n",
       "   '2018-11-21T00:00:00Z',\n",
       "   '2018-11-21T01:00:00Z',\n",
       "   '2018-11-21T02:00:00Z',\n",
       "   '2018-11-21T03:00:00Z',\n",
       "   '2018-11-21T04:00:00Z',\n",
       "   '2018-11-21T05:00:00Z',\n",
       "   '2018-11-21T06:00:00Z',\n",
       "   '2018-11-21T07:00:00Z',\n",
       "   '2018-11-21T08:00:00Z',\n",
       "   '2018-11-21T09:00:00Z',\n",
       "   '2018-11-21T10:00:00Z',\n",
       "   '2018-11-21T11:00:00Z',\n",
       "   '2018-11-21T12:00:00Z',\n",
       "   '2018-11-21T13:00:00Z',\n",
       "   '2018-11-21T14:00:00Z',\n",
       "   '2018-11-21T15:00:00Z',\n",
       "   '2018-11-21T16:00:00Z',\n",
       "   '2018-11-21T17:00:00Z',\n",
       "   '2018-11-21T18:00:00Z',\n",
       "   '2018-11-21T19:00:00Z',\n",
       "   '2018-11-21T20:00:00Z',\n",
       "   '2018-11-21T21:00:00Z',\n",
       "   '2018-11-21T22:00:00Z',\n",
       "   '2018-11-21T23:00:00Z',\n",
       "   '2018-11-22T00:00:00Z',\n",
       "   '2018-11-22T01:00:00Z',\n",
       "   '2018-11-22T02:00:00Z',\n",
       "   '2018-11-22T03:00:00Z',\n",
       "   '2018-11-22T04:00:00Z',\n",
       "   '2018-11-22T05:00:00Z',\n",
       "   '2018-11-22T06:00:00Z',\n",
       "   '2018-11-22T07:00:00Z',\n",
       "   '2018-11-22T08:00:00Z',\n",
       "   '2018-11-22T09:00:00Z',\n",
       "   '2018-11-22T10:00:00Z',\n",
       "   '2018-11-22T11:00:00Z',\n",
       "   '2018-11-22T12:00:00Z',\n",
       "   '2018-11-22T13:00:00Z',\n",
       "   '2018-11-22T14:00:00Z',\n",
       "   '2018-11-22T15:00:00Z',\n",
       "   '2018-11-22T16:00:00Z',\n",
       "   '2018-11-22T17:00:00Z',\n",
       "   '2018-11-22T18:00:00Z',\n",
       "   '2018-11-22T19:00:00Z',\n",
       "   '2018-11-22T20:00:00Z',\n",
       "   '2018-11-22T21:00:00Z',\n",
       "   '2018-11-22T22:00:00Z',\n",
       "   '2018-11-22T23:00:00Z',\n",
       "   '2018-11-23T00:00:00Z',\n",
       "   '2018-11-23T01:00:00Z',\n",
       "   '2018-11-23T02:00:00Z',\n",
       "   '2018-11-23T03:00:00Z',\n",
       "   '2018-11-23T04:00:00Z',\n",
       "   '2018-11-23T05:00:00Z',\n",
       "   '2018-11-23T06:00:00Z',\n",
       "   '2018-11-23T07:00:00Z',\n",
       "   '2018-11-23T08:00:00Z',\n",
       "   '2018-11-23T09:00:00Z',\n",
       "   '2018-11-23T10:00:00Z',\n",
       "   '2018-11-23T11:00:00Z',\n",
       "   '2018-11-23T12:00:00Z',\n",
       "   '2018-11-23T13:00:00Z',\n",
       "   '2018-11-23T14:00:00Z',\n",
       "   '2018-11-23T15:00:00Z',\n",
       "   '2018-11-23T16:00:00Z',\n",
       "   '2018-11-23T17:00:00Z',\n",
       "   '2018-11-23T18:00:00Z',\n",
       "   '2018-11-23T19:00:00Z',\n",
       "   '2018-11-23T20:00:00Z',\n",
       "   '2018-11-23T21:00:00Z',\n",
       "   '2018-11-23T22:00:00Z',\n",
       "   '2018-11-23T23:00:00Z',\n",
       "   '2018-11-24T00:00:00Z',\n",
       "   '2018-11-24T01:00:00Z',\n",
       "   '2018-11-24T02:00:00Z',\n",
       "   '2018-11-24T03:00:00Z',\n",
       "   '2018-11-24T04:00:00Z',\n",
       "   '2018-11-24T05:00:00Z',\n",
       "   '2018-11-24T06:00:00Z',\n",
       "   '2018-11-24T07:00:00Z',\n",
       "   '2018-11-24T08:00:00Z',\n",
       "   '2018-11-24T09:00:00Z',\n",
       "   '2018-11-24T10:00:00Z',\n",
       "   '2018-11-24T11:00:00Z',\n",
       "   '2018-11-24T12:00:00Z',\n",
       "   '2018-11-24T13:00:00Z',\n",
       "   '2018-11-24T14:00:00Z',\n",
       "   '2018-11-24T15:00:00Z',\n",
       "   '2018-11-24T16:00:00Z',\n",
       "   '2018-11-24T17:00:00Z',\n",
       "   '2018-11-24T18:00:00Z',\n",
       "   '2018-11-24T19:00:00Z',\n",
       "   '2018-11-24T20:00:00Z',\n",
       "   '2018-11-24T21:00:00Z',\n",
       "   '2018-11-24T22:00:00Z',\n",
       "   '2018-11-24T23:00:00Z',\n",
       "   '2018-11-25T00:00:00Z',\n",
       "   '2018-11-25T01:00:00Z',\n",
       "   '2018-11-25T02:00:00Z',\n",
       "   '2018-11-25T03:00:00Z',\n",
       "   '2018-11-25T04:00:00Z',\n",
       "   '2018-11-25T05:00:00Z',\n",
       "   '2018-11-25T06:00:00Z',\n",
       "   '2018-11-25T07:00:00Z',\n",
       "   '2018-11-25T08:00:00Z',\n",
       "   '2018-11-25T09:00:00Z',\n",
       "   '2018-11-25T10:00:00Z',\n",
       "   '2018-11-25T11:00:00Z',\n",
       "   '2018-11-25T12:00:00Z',\n",
       "   '2018-11-25T13:00:00Z',\n",
       "   '2018-11-25T14:00:00Z',\n",
       "   '2018-11-25T15:00:00Z',\n",
       "   '2018-11-25T16:00:00Z',\n",
       "   '2018-11-25T17:00:00Z',\n",
       "   '2018-11-25T18:00:00Z',\n",
       "   '2018-11-25T19:00:00Z',\n",
       "   '2018-11-25T20:00:00Z',\n",
       "   '2018-11-25T21:00:00Z',\n",
       "   '2018-11-25T22:00:00Z',\n",
       "   '2018-11-25T23:00:00Z',\n",
       "   '2018-11-26T00:00:00Z',\n",
       "   '2018-11-26T01:00:00Z',\n",
       "   '2018-11-26T02:00:00Z',\n",
       "   '2018-11-26T03:00:00Z',\n",
       "   '2018-11-26T04:00:00Z',\n",
       "   '2018-11-26T05:00:00Z',\n",
       "   '2018-11-26T06:00:00Z',\n",
       "   '2018-11-26T07:00:00Z',\n",
       "   '2018-11-26T08:00:00Z',\n",
       "   '2018-11-26T09:00:00Z',\n",
       "   '2018-11-26T10:00:00Z',\n",
       "   '2018-11-26T11:00:00Z',\n",
       "   '2018-11-26T12:00:00Z',\n",
       "   '2018-11-26T13:00:00Z',\n",
       "   '2018-11-26T14:00:00Z',\n",
       "   '2018-11-26T15:00:00Z',\n",
       "   '2018-11-26T16:00:00Z',\n",
       "   '2018-11-26T17:00:00Z',\n",
       "   '2018-11-26T18:00:00Z',\n",
       "   '2018-11-26T19:00:00Z',\n",
       "   '2018-11-26T20:00:00Z',\n",
       "   '2018-11-26T21:00:00Z',\n",
       "   '2018-11-26T22:00:00Z',\n",
       "   '2018-11-26T23:00:00Z',\n",
       "   '2018-11-27T00:00:00Z',\n",
       "   '2018-11-27T01:00:00Z',\n",
       "   '2018-11-27T02:00:00Z',\n",
       "   '2018-11-27T03:00:00Z',\n",
       "   '2018-11-27T04:00:00Z',\n",
       "   '2018-11-27T05:00:00Z',\n",
       "   '2018-11-27T06:00:00Z',\n",
       "   '2018-11-27T07:00:00Z',\n",
       "   '2018-11-27T08:00:00Z',\n",
       "   '2018-11-27T09:00:00Z',\n",
       "   '2018-11-27T10:00:00Z',\n",
       "   '2018-11-27T11:00:00Z',\n",
       "   '2018-11-27T12:00:00Z',\n",
       "   '2018-11-27T13:00:00Z',\n",
       "   '2018-11-27T14:00:00Z',\n",
       "   '2018-11-27T15:00:00Z',\n",
       "   '2018-11-27T16:00:00Z',\n",
       "   '2018-11-27T17:00:00Z',\n",
       "   '2018-11-27T18:00:00Z',\n",
       "   '2018-11-27T19:00:00Z',\n",
       "   '2018-11-27T20:00:00Z',\n",
       "   '2018-11-27T21:00:00Z',\n",
       "   '2018-11-27T22:00:00Z',\n",
       "   '2018-11-27T23:00:00Z',\n",
       "   '2018-11-28T00:00:00Z',\n",
       "   '2018-11-28T01:00:00Z',\n",
       "   '2018-11-28T02:00:00Z',\n",
       "   '2018-11-28T03:00:00Z',\n",
       "   '2018-11-28T04:00:00Z',\n",
       "   '2018-11-28T05:00:00Z',\n",
       "   '2018-11-28T06:00:00Z',\n",
       "   '2018-11-28T07:00:00Z',\n",
       "   '2018-11-28T08:00:00Z',\n",
       "   '2018-11-28T09:00:00Z',\n",
       "   '2018-11-28T10:00:00Z',\n",
       "   '2018-11-28T11:00:00Z',\n",
       "   '2018-11-28T12:00:00Z',\n",
       "   '2018-11-28T13:00:00Z',\n",
       "   '2018-11-28T14:00:00Z',\n",
       "   '2018-11-28T15:00:00Z',\n",
       "   '2018-11-28T16:00:00Z',\n",
       "   '2018-11-28T17:00:00Z',\n",
       "   '2018-11-28T18:00:00Z',\n",
       "   '2018-11-28T19:00:00Z',\n",
       "   '2018-11-28T20:00:00Z',\n",
       "   '2018-11-28T21:00:00Z',\n",
       "   '2018-11-28T22:00:00Z',\n",
       "   '2018-11-28T23:00:00Z',\n",
       "   '2018-11-29T00:00:00Z',\n",
       "   '2018-11-29T01:00:00Z',\n",
       "   '2018-11-29T02:00:00Z',\n",
       "   '2018-11-29T03:00:00Z',\n",
       "   '2018-11-29T04:00:00Z',\n",
       "   '2018-11-29T05:00:00Z',\n",
       "   '2018-11-29T06:00:00Z',\n",
       "   '2018-11-29T07:00:00Z',\n",
       "   '2018-11-29T08:00:00Z',\n",
       "   '2018-11-29T09:00:00Z',\n",
       "   '2018-11-29T10:00:00Z',\n",
       "   '2018-11-29T11:00:00Z',\n",
       "   '2018-11-29T12:00:00Z',\n",
       "   '2018-11-29T13:00:00Z',\n",
       "   '2018-11-29T14:00:00Z',\n",
       "   '2018-11-29T15:00:00Z',\n",
       "   '2018-11-29T16:00:00Z',\n",
       "   '2018-11-29T17:00:00Z',\n",
       "   '2018-11-29T18:00:00Z',\n",
       "   '2018-11-29T19:00:00Z',\n",
       "   '2018-11-29T20:00:00Z',\n",
       "   '2018-11-29T21:00:00Z',\n",
       "   '2018-11-29T22:00:00Z',\n",
       "   '2018-11-29T23:00:00Z',\n",
       "   '2018-11-30T00:00:00Z',\n",
       "   '2018-11-30T01:00:00Z',\n",
       "   '2018-11-30T02:00:00Z',\n",
       "   '2018-11-30T03:00:00Z',\n",
       "   '2018-11-30T04:00:00Z',\n",
       "   '2018-11-30T05:00:00Z',\n",
       "   '2018-11-30T06:00:00Z',\n",
       "   '2018-11-30T07:00:00Z',\n",
       "   '2018-11-30T08:00:00Z',\n",
       "   '2018-11-30T09:00:00Z',\n",
       "   '2018-11-30T10:00:00Z',\n",
       "   '2018-11-30T11:00:00Z',\n",
       "   '2018-11-30T12:00:00Z'],\n",
       "  'wind_speed_set_1': [2.35,\n",
       "   1.4,\n",
       "   4.08,\n",
       "   4.0,\n",
       "   4.53,\n",
       "   3.83,\n",
       "   2.25,\n",
       "   1.75,\n",
       "   1.9,\n",
       "   1.9,\n",
       "   1.75,\n",
       "   1.4,\n",
       "   1.22,\n",
       "   1.56,\n",
       "   1.4,\n",
       "   2.18,\n",
       "   2.53,\n",
       "   2.43,\n",
       "   1.65,\n",
       "   5.03,\n",
       "   6.78,\n",
       "   6.01,\n",
       "   4.33,\n",
       "   5.03,\n",
       "   7.11,\n",
       "   5.46,\n",
       "   6.43,\n",
       "   6.78,\n",
       "   6.43,\n",
       "   5.81,\n",
       "   4.68,\n",
       "   4.88,\n",
       "   8.59,\n",
       "   5.31,\n",
       "   4.96,\n",
       "   5.38,\n",
       "   5.46,\n",
       "   5.03,\n",
       "   2.0,\n",
       "   2.18,\n",
       "   1.83,\n",
       "   1.22,\n",
       "   1.75,\n",
       "   3.03,\n",
       "   3.91,\n",
       "   2.68,\n",
       "   3.3,\n",
       "   2.35,\n",
       "   1.4,\n",
       "   2.0,\n",
       "   1.83,\n",
       "   2.1,\n",
       "   1.56,\n",
       "   1.75,\n",
       "   1.83,\n",
       "   2.43,\n",
       "   4.78,\n",
       "   4.08,\n",
       "   4.33,\n",
       "   3.56,\n",
       "   2.78,\n",
       "   0.95,\n",
       "   0.78,\n",
       "   0.95,\n",
       "   0.87,\n",
       "   0.52,\n",
       "   None,\n",
       "   1.75,\n",
       "   1.3,\n",
       "   2.0,\n",
       "   2.53,\n",
       "   2.95,\n",
       "   6.96,\n",
       "   6.01,\n",
       "   8.16,\n",
       "   6.51,\n",
       "   9.04,\n",
       "   8.59,\n",
       "   10.34,\n",
       "   10.87,\n",
       "   12.34,\n",
       "   15.12,\n",
       "   16.78,\n",
       "   14.95,\n",
       "   11.9,\n",
       "   9.39,\n",
       "   7.99,\n",
       "   8.16,\n",
       "   12.07,\n",
       "   13.02,\n",
       "   11.22,\n",
       "   10.59,\n",
       "   11.29,\n",
       "   13.22,\n",
       "   13.12,\n",
       "   11.04,\n",
       "   11.72,\n",
       "   9.64,\n",
       "   10.94,\n",
       "   9.39,\n",
       "   9.12,\n",
       "   7.31,\n",
       "   6.34,\n",
       "   4.88,\n",
       "   3.83,\n",
       "   4.78,\n",
       "   3.21,\n",
       "   2.68,\n",
       "   1.48,\n",
       "   1.9,\n",
       "   1.75,\n",
       "   2.35,\n",
       "   1.65,\n",
       "   2.35,\n",
       "   2.6,\n",
       "   2.0,\n",
       "   2.25,\n",
       "   1.75,\n",
       "   5.31,\n",
       "   4.08,\n",
       "   3.03,\n",
       "   2.6,\n",
       "   2.6,\n",
       "   2.68,\n",
       "   2.43,\n",
       "   1.65,\n",
       "   2.1,\n",
       "   2.0,\n",
       "   2.1,\n",
       "   1.9,\n",
       "   1.56,\n",
       "   1.65,\n",
       "   1.48,\n",
       "   1.65,\n",
       "   2.43,\n",
       "   2.18,\n",
       "   3.48,\n",
       "   5.56,\n",
       "   7.56,\n",
       "   8.59,\n",
       "   10.24,\n",
       "   10.94,\n",
       "   9.82,\n",
       "   10.34,\n",
       "   10.34,\n",
       "   10.59,\n",
       "   10.24,\n",
       "   9.64,\n",
       "   9.56,\n",
       "   9.99,\n",
       "   9.12,\n",
       "   10.44,\n",
       "   11.9,\n",
       "   8.79,\n",
       "   7.46,\n",
       "   6.51,\n",
       "   5.31,\n",
       "   5.56,\n",
       "   1.56,\n",
       "   0.78,\n",
       "   0.87,\n",
       "   0.35,\n",
       "   1.13,\n",
       "   1.65,\n",
       "   2.35,\n",
       "   3.48,\n",
       "   4.08,\n",
       "   6.01,\n",
       "   5.46,\n",
       "   7.21,\n",
       "   7.04,\n",
       "   7.21,\n",
       "   5.56,\n",
       "   4.53,\n",
       "   4.61,\n",
       "   4.78,\n",
       "   4.43,\n",
       "   6.08,\n",
       "   5.38,\n",
       "   5.56,\n",
       "   6.34,\n",
       "   6.43,\n",
       "   3.48,\n",
       "   2.6,\n",
       "   1.83,\n",
       "   2.1,\n",
       "   1.3,\n",
       "   0.78,\n",
       "   0.7,\n",
       "   1.4,\n",
       "   1.75,\n",
       "   2.0,\n",
       "   1.48,\n",
       "   1.75,\n",
       "   1.9,\n",
       "   1.3,\n",
       "   1.4,\n",
       "   1.56,\n",
       "   1.56,\n",
       "   1.56,\n",
       "   1.48,\n",
       "   1.56,\n",
       "   1.56,\n",
       "   4.61,\n",
       "   6.26,\n",
       "   5.38,\n",
       "   6.43,\n",
       "   8.51,\n",
       "   7.74,\n",
       "   8.16,\n",
       "   7.81,\n",
       "   7.46,\n",
       "   7.99,\n",
       "   6.61,\n",
       "   5.66,\n",
       "   4.88,\n",
       "   3.03,\n",
       "   6.16,\n",
       "   7.99,\n",
       "   6.86,\n",
       "   6.08,\n",
       "   4.26,\n",
       "   3.73,\n",
       "   5.46,\n",
       "   5.56,\n",
       "   5.38,\n",
       "   4.0,\n",
       "   3.48,\n",
       "   0.95,\n",
       "   0.52,\n",
       "   2.25,\n",
       "   1.05,\n",
       "   1.56,\n",
       "   1.65,\n",
       "   2.78,\n",
       "   4.08,\n",
       "   2.43,\n",
       "   5.13,\n",
       "   4.26,\n",
       "   4.78,\n",
       "   5.03,\n",
       "   6.61,\n",
       "   6.51,\n",
       "   6.43,\n",
       "   6.51,\n",
       "   5.38,\n",
       "   4.78,\n",
       "   3.65,\n",
       "   3.48,\n",
       "   4.33,\n",
       "   3.73,\n",
       "   2.18,\n",
       "   2.43,\n",
       "   3.65,\n",
       "   1.9,\n",
       "   0.95,\n",
       "   0.78,\n",
       "   1.05,\n",
       "   0.7,\n",
       "   0.87,\n",
       "   1.13,\n",
       "   0.95,\n",
       "   1.13,\n",
       "   1.22,\n",
       "   0.95,\n",
       "   1.05,\n",
       "   1.13,\n",
       "   1.3,\n",
       "   2.35,\n",
       "   1.65,\n",
       "   2.6,\n",
       "   2.95,\n",
       "   2.6,\n",
       "   3.03,\n",
       "   1.9,\n",
       "   0.87,\n",
       "   0.52,\n",
       "   0.43,\n",
       "   0.78,\n",
       "   0.95,\n",
       "   0.95,\n",
       "   0.78,\n",
       "   1.22,\n",
       "   1.05,\n",
       "   1.65,\n",
       "   1.56,\n",
       "   2.18,\n",
       "   1.13,\n",
       "   0.87,\n",
       "   1.4,\n",
       "   2.0,\n",
       "   1.3,\n",
       "   0.6,\n",
       "   0.52,\n",
       "   0.95,\n",
       "   0.87,\n",
       "   0.7,\n",
       "   0.52,\n",
       "   0.52,\n",
       "   0.35,\n",
       "   0.7,\n",
       "   1.48,\n",
       "   1.65,\n",
       "   1.48,\n",
       "   2.1,\n",
       "   2.43,\n",
       "   2.43,\n",
       "   2.25,\n",
       "   2.88,\n",
       "   2.6,\n",
       "   3.56,\n",
       "   5.38,\n",
       "   2.6,\n",
       "   2.43,\n",
       "   1.48,\n",
       "   0.95,\n",
       "   0.95,\n",
       "   0.95,\n",
       "   1.4,\n",
       "   1.48,\n",
       "   1.75,\n",
       "   1.56,\n",
       "   1.3,\n",
       "   1.75,\n",
       "   1.75,\n",
       "   1.65,\n",
       "   2.0,\n",
       "   1.56,\n",
       "   1.22,\n",
       "   1.56,\n",
       "   1.3,\n",
       "   1.75,\n",
       "   2.18,\n",
       "   1.4,\n",
       "   1.65,\n",
       "   1.83,\n",
       "   1.83,\n",
       "   2.25,\n",
       "   1.83,\n",
       "   0.78,\n",
       "   1.13,\n",
       "   1.13,\n",
       "   1.56,\n",
       "   1.48,\n",
       "   1.65,\n",
       "   1.65,\n",
       "   4.0,\n",
       "   5.21,\n",
       "   4.61,\n",
       "   1.65,\n",
       "   2.25,\n",
       "   2.25,\n",
       "   2.53,\n",
       "   2.43,\n",
       "   2.78,\n",
       "   2.95,\n",
       "   3.21,\n",
       "   3.48,\n",
       "   4.33,\n",
       "   5.13,\n",
       "   5.21,\n",
       "   4.68,\n",
       "   2.68,\n",
       "   0.95,\n",
       "   0.87,\n",
       "   1.22,\n",
       "   1.65,\n",
       "   1.75,\n",
       "   2.35,\n",
       "   5.38,\n",
       "   6.43,\n",
       "   6.01,\n",
       "   7.21,\n",
       "   3.3,\n",
       "   3.21,\n",
       "   2.78,\n",
       "   2.0,\n",
       "   2.35,\n",
       "   2.6,\n",
       "   4.08,\n",
       "   2.78,\n",
       "   4.96,\n",
       "   6.43,\n",
       "   6.61,\n",
       "   4.26,\n",
       "   3.65,\n",
       "   4.78,\n",
       "   4.0,\n",
       "   2.6,\n",
       "   2.88,\n",
       "   3.73,\n",
       "   4.33,\n",
       "   4.96,\n",
       "   5.91,\n",
       "   4.96,\n",
       "   4.78,\n",
       "   3.56,\n",
       "   1.75,\n",
       "   1.75,\n",
       "   0.7,\n",
       "   0.87,\n",
       "   0.78,\n",
       "   1.4,\n",
       "   1.22,\n",
       "   0.95,\n",
       "   1.13,\n",
       "   2.25,\n",
       "   2.53,\n",
       "   2.53,\n",
       "   2.18,\n",
       "   2.95,\n",
       "   1.3,\n",
       "   0.95,\n",
       "   1.05,\n",
       "   1.22,\n",
       "   1.56,\n",
       "   1.65,\n",
       "   1.65,\n",
       "   2.25,\n",
       "   2.25,\n",
       "   2.18,\n",
       "   2.35,\n",
       "   2.18,\n",
       "   2.43,\n",
       "   2.35,\n",
       "   2.25,\n",
       "   2.18,\n",
       "   4.33,\n",
       "   1.65,\n",
       "   2.0,\n",
       "   0.7,\n",
       "   1.65,\n",
       "   2.68,\n",
       "   2.53,\n",
       "   3.48,\n",
       "   1.65,\n",
       "   0.7,\n",
       "   1.4,\n",
       "   1.3,\n",
       "   1.13,\n",
       "   1.4,\n",
       "   1.48,\n",
       "   1.48,\n",
       "   1.83,\n",
       "   1.9,\n",
       "   2.1,\n",
       "   2.25,\n",
       "   2.18,\n",
       "   2.43,\n",
       "   2.1,\n",
       "   1.56,\n",
       "   2.35,\n",
       "   3.21,\n",
       "   1.56,\n",
       "   1.65,\n",
       "   3.21,\n",
       "   5.38,\n",
       "   4.26,\n",
       "   6.34,\n",
       "   9.12,\n",
       "   8.86,\n",
       "   6.96,\n",
       "   6.78,\n",
       "   5.38,\n",
       "   4.26,\n",
       "   5.13,\n",
       "   5.91,\n",
       "   6.34,\n",
       "   6.69,\n",
       "   5.81,\n",
       "   5.91,\n",
       "   4.78,\n",
       "   5.38,\n",
       "   4.43,\n",
       "   6.86,\n",
       "   8.09,\n",
       "   9.39,\n",
       "   10.87,\n",
       "   12.42,\n",
       "   11.99,\n",
       "   10.34,\n",
       "   10.44,\n",
       "   12.07,\n",
       "   11.64,\n",
       "   11.9,\n",
       "   12.42,\n",
       "   8.51,\n",
       "   9.39,\n",
       "   13.9,\n",
       "   12.52,\n",
       "   9.56,\n",
       "   14.15,\n",
       "   14.25,\n",
       "   13.55,\n",
       "   10.69,\n",
       "   11.99,\n",
       "   8.51,\n",
       "   5.38,\n",
       "   8.51,\n",
       "   11.29,\n",
       "   5.38,\n",
       "   5.46,\n",
       "   6.43,\n",
       "   9.12,\n",
       "   6.78,\n",
       "   12.34,\n",
       "   6.86,\n",
       "   10.09,\n",
       "   11.72,\n",
       "   14.15,\n",
       "   15.3,\n",
       "   16.43,\n",
       "   17.46,\n",
       "   9.64,\n",
       "   11.72,\n",
       "   11.04,\n",
       "   9.39,\n",
       "   8.79,\n",
       "   10.09,\n",
       "   11.04,\n",
       "   12.69,\n",
       "   9.12,\n",
       "   10.87,\n",
       "   17.73,\n",
       "   18.86,\n",
       "   17.13,\n",
       "   16.0,\n",
       "   14.85,\n",
       "   12.6,\n",
       "   9.56,\n",
       "   10.94,\n",
       "   8.86,\n",
       "   9.64,\n",
       "   14.68,\n",
       "   18.51,\n",
       "   17.38,\n",
       "   19.21,\n",
       "   13.37,\n",
       "   14.25,\n",
       "   20.68,\n",
       "   18.93,\n",
       "   18.78,\n",
       "   19.71,\n",
       "   19.56,\n",
       "   21.36,\n",
       "   21.63,\n",
       "   20.25,\n",
       "   19.71,\n",
       "   19.9,\n",
       "   19.28,\n",
       "   19.56,\n",
       "   19.71,\n",
       "   19.71,\n",
       "   16.43,\n",
       "   16.43,\n",
       "   12.95,\n",
       "   14.85,\n",
       "   13.3,\n",
       "   10.69,\n",
       "   9.82,\n",
       "   7.91,\n",
       "   5.38,\n",
       "   3.21,\n",
       "   2.43,\n",
       "   1.13,\n",
       "   1.4,\n",
       "   1.3,\n",
       "   1.83,\n",
       "   1.4,\n",
       "   1.4,\n",
       "   1.83,\n",
       "   1.13,\n",
       "   2.35,\n",
       "   8.86,\n",
       "   2.88,\n",
       "   1.3,\n",
       "   1.65,\n",
       "   1.05,\n",
       "   0.87,\n",
       "   0.6,\n",
       "   0.35,\n",
       "   0.7,\n",
       "   0.95,\n",
       "   0.95,\n",
       "   0.87,\n",
       "   1.65,\n",
       "   2.43,\n",
       "   2.1,\n",
       "   1.56,\n",
       "   1.3,\n",
       "   1.48,\n",
       "   1.56,\n",
       "   1.05,\n",
       "   1.48,\n",
       "   1.4,\n",
       "   1.75,\n",
       "   0.87,\n",
       "   1.05,\n",
       "   1.48,\n",
       "   3.73,\n",
       "   3.3,\n",
       "   2.25,\n",
       "   3.65,\n",
       "   1.75,\n",
       "   0.6,\n",
       "   0.95,\n",
       "   1.56,\n",
       "   3.56,\n",
       "   3.65,\n",
       "   5.56,\n",
       "   7.91,\n",
       "   9.64,\n",
       "   10.09,\n",
       "   11.12,\n",
       "   10.69,\n",
       "   9.12,\n",
       "   11.82,\n",
       "   10.87,\n",
       "   5.13,\n",
       "   5.46,\n",
       "   6.16,\n",
       "   4.61,\n",
       "   6.51,\n",
       "   6.26,\n",
       "   6.43,\n",
       "   6.43,\n",
       "   9.04,\n",
       "   10.59,\n",
       "   8.94,\n",
       "   11.64,\n",
       "   9.39,\n",
       "   12.07,\n",
       "   9.12,\n",
       "   5.81,\n",
       "   6.96,\n",
       "   5.81,\n",
       "   5.66,\n",
       "   7.46,\n",
       "   11.12,\n",
       "   10.87,\n",
       "   8.59,\n",
       "   10.17,\n",
       "   9.47,\n",
       "   11.82,\n",
       "   9.21,\n",
       "   11.29,\n",
       "   8.59,\n",
       "   9.99,\n",
       "   9.56,\n",
       "   5.81,\n",
       "   4.88,\n",
       "   9.29,\n",
       "   10.17,\n",
       "   10.24,\n",
       "   11.04,\n",
       "   9.56,\n",
       "   9.29,\n",
       "   9.47,\n",
       "   6.78,\n",
       "   4.96,\n",
       "   4.78,\n",
       "   4.0,\n",
       "   7.91,\n",
       "   8.59,\n",
       "   6.26,\n",
       "   9.74,\n",
       "   10.59,\n",
       "   2.43,\n",
       "   2.43,\n",
       "   9.29,\n",
       "   15.2,\n",
       "   13.55,\n",
       "   11.72,\n",
       "   10.94,\n",
       "   8.16,\n",
       "   8.44,\n",
       "   5.38,\n",
       "   7.74,\n",
       "   13.22,\n",
       "   15.3,\n",
       "   14.25,\n",
       "   14.6,\n",
       "   9.47,\n",
       "   7.56,\n",
       "   5.91,\n",
       "   4.53,\n",
       "   2.88,\n",
       "   5.03,\n",
       "   6.78,\n",
       "   8.59,\n",
       "   9.47,\n",
       "   11.64,\n",
       "   9.12,\n",
       "   6.61,\n",
       "   4.96,\n",
       "   7.31],\n",
       "  'wind_direction_set_1': [93.0,\n",
       "   111.0,\n",
       "   82.0,\n",
       "   75.0,\n",
       "   85.0,\n",
       "   105.0,\n",
       "   116.0,\n",
       "   124.0,\n",
       "   128.0,\n",
       "   159.0,\n",
       "   146.0,\n",
       "   129.0,\n",
       "   147.0,\n",
       "   303.0,\n",
       "   322.0,\n",
       "   289.0,\n",
       "   297.0,\n",
       "   300.0,\n",
       "   315.0,\n",
       "   301.0,\n",
       "   301.0,\n",
       "   298.0,\n",
       "   299.0,\n",
       "   292.0,\n",
       "   285.0,\n",
       "   297.0,\n",
       "   291.0,\n",
       "   293.0,\n",
       "   306.0,\n",
       "   315.0,\n",
       "   300.0,\n",
       "   324.0,\n",
       "   323.0,\n",
       "   288.0,\n",
       "   308.0,\n",
       "   274.0,\n",
       "   296.0,\n",
       "   286.0,\n",
       "   325.0,\n",
       "   300.0,\n",
       "   303.0,\n",
       "   86.0,\n",
       "   287.0,\n",
       "   327.0,\n",
       "   352.0,\n",
       "   336.0,\n",
       "   13.0,\n",
       "   309.0,\n",
       "   19.0,\n",
       "   320.0,\n",
       "   317.0,\n",
       "   291.0,\n",
       "   208.0,\n",
       "   135.0,\n",
       "   130.0,\n",
       "   126.0,\n",
       "   103.0,\n",
       "   106.0,\n",
       "   101.0,\n",
       "   99.0,\n",
       "   103.0,\n",
       "   116.0,\n",
       "   124.0,\n",
       "   271.0,\n",
       "   118.0,\n",
       "   285.0,\n",
       "   None,\n",
       "   322.0,\n",
       "   19.0,\n",
       "   311.0,\n",
       "   315.0,\n",
       "   313.0,\n",
       "   290.0,\n",
       "   295.0,\n",
       "   324.0,\n",
       "   296.0,\n",
       "   264.0,\n",
       "   264.0,\n",
       "   267.0,\n",
       "   270.0,\n",
       "   261.0,\n",
       "   262.0,\n",
       "   262.0,\n",
       "   265.0,\n",
       "   267.0,\n",
       "   291.0,\n",
       "   303.0,\n",
       "   289.0,\n",
       "   284.0,\n",
       "   287.0,\n",
       "   286.0,\n",
       "   284.0,\n",
       "   275.0,\n",
       "   273.0,\n",
       "   274.0,\n",
       "   282.0,\n",
       "   281.0,\n",
       "   283.0,\n",
       "   281.0,\n",
       "   284.0,\n",
       "   290.0,\n",
       "   269.0,\n",
       "   281.0,\n",
       "   268.0,\n",
       "   270.0,\n",
       "   287.0,\n",
       "   294.0,\n",
       "   323.0,\n",
       "   331.0,\n",
       "   347.0,\n",
       "   325.0,\n",
       "   316.0,\n",
       "   354.0,\n",
       "   312.0,\n",
       "   316.0,\n",
       "   316.0,\n",
       "   316.0,\n",
       "   347.0,\n",
       "   15.0,\n",
       "   31.0,\n",
       "   7.0,\n",
       "   None,\n",
       "   319.0,\n",
       "   320.0,\n",
       "   95.0,\n",
       "   135.0,\n",
       "   135.0,\n",
       "   139.0,\n",
       "   137.0,\n",
       "   148.0,\n",
       "   152.0,\n",
       "   238.0,\n",
       "   299.0,\n",
       "   315.0,\n",
       "   296.0,\n",
       "   308.0,\n",
       "   296.0,\n",
       "   292.0,\n",
       "   290.0,\n",
       "   289.0,\n",
       "   291.0,\n",
       "   281.0,\n",
       "   279.0,\n",
       "   284.0,\n",
       "   279.0,\n",
       "   283.0,\n",
       "   278.0,\n",
       "   271.0,\n",
       "   272.0,\n",
       "   280.0,\n",
       "   270.0,\n",
       "   271.0,\n",
       "   279.0,\n",
       "   288.0,\n",
       "   272.0,\n",
       "   280.0,\n",
       "   290.0,\n",
       "   291.0,\n",
       "   302.0,\n",
       "   259.0,\n",
       "   20.0,\n",
       "   87.0,\n",
       "   119.0,\n",
       "   116.0,\n",
       "   112.0,\n",
       "   107.0,\n",
       "   108.0,\n",
       "   102.0,\n",
       "   105.0,\n",
       "   98.0,\n",
       "   100.0,\n",
       "   102.0,\n",
       "   113.0,\n",
       "   114.0,\n",
       "   116.0,\n",
       "   116.0,\n",
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       "   304.0,\n",
       "   274.0]},\n",
       " 'RESTRICTED': False,\n",
       " 'QC_FLAGGED': True,\n",
       " 'LATITUDE': '39.18986',\n",
       " 'TIMEZONE': 'America/Los_Angeles',\n",
       " 'ID': '1054'}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_data = response.json()['STATION'][index]\n",
    "station_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['wind_speed', 'date_time', 'wind_direction']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avail_sensors = list(station_data['SENSOR_VARIABLES'].keys())\n",
    "avail_sensors\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "  '2018-11-21T18:00:00Z',\n",
       "  '2018-11-21T19:00:00Z',\n",
       "  '2018-11-21T20:00:00Z',\n",
       "  '2018-11-21T21:00:00Z',\n",
       "  '2018-11-21T22:00:00Z',\n",
       "  '2018-11-21T23:00:00Z',\n",
       "  '2018-11-22T00:00:00Z',\n",
       "  '2018-11-22T01:00:00Z',\n",
       "  '2018-11-22T02:00:00Z',\n",
       "  '2018-11-22T03:00:00Z',\n",
       "  '2018-11-22T04:00:00Z',\n",
       "  '2018-11-22T05:00:00Z',\n",
       "  '2018-11-22T06:00:00Z',\n",
       "  '2018-11-22T07:00:00Z',\n",
       "  '2018-11-22T08:00:00Z',\n",
       "  '2018-11-22T09:00:00Z',\n",
       "  '2018-11-22T10:00:00Z',\n",
       "  '2018-11-22T11:00:00Z',\n",
       "  '2018-11-22T12:00:00Z',\n",
       "  '2018-11-22T13:00:00Z',\n",
       "  '2018-11-22T14:00:00Z',\n",
       "  '2018-11-22T15:00:00Z',\n",
       "  '2018-11-22T16:00:00Z',\n",
       "  '2018-11-22T17:00:00Z',\n",
       "  '2018-11-22T18:00:00Z',\n",
       "  '2018-11-22T19:00:00Z',\n",
       "  '2018-11-22T20:00:00Z',\n",
       "  '2018-11-22T21:00:00Z',\n",
       "  '2018-11-22T22:00:00Z',\n",
       "  '2018-11-22T23:00:00Z',\n",
       "  '2018-11-23T00:00:00Z',\n",
       "  '2018-11-23T01:00:00Z',\n",
       "  '2018-11-23T02:00:00Z',\n",
       "  '2018-11-23T03:00:00Z',\n",
       "  '2018-11-23T04:00:00Z',\n",
       "  '2018-11-23T05:00:00Z',\n",
       "  '2018-11-23T06:00:00Z',\n",
       "  '2018-11-23T07:00:00Z',\n",
       "  '2018-11-23T08:00:00Z',\n",
       "  '2018-11-23T09:00:00Z',\n",
       "  '2018-11-23T10:00:00Z',\n",
       "  '2018-11-23T11:00:00Z',\n",
       "  '2018-11-23T12:00:00Z',\n",
       "  '2018-11-23T13:00:00Z',\n",
       "  '2018-11-23T14:00:00Z',\n",
       "  '2018-11-23T15:00:00Z',\n",
       "  '2018-11-23T16:00:00Z',\n",
       "  '2018-11-23T17:00:00Z',\n",
       "  '2018-11-23T18:00:00Z',\n",
       "  '2018-11-23T19:00:00Z',\n",
       "  '2018-11-23T20:00:00Z',\n",
       "  '2018-11-23T21:00:00Z',\n",
       "  '2018-11-23T22:00:00Z',\n",
       "  '2018-11-23T23:00:00Z',\n",
       "  '2018-11-24T00:00:00Z',\n",
       "  '2018-11-24T01:00:00Z',\n",
       "  '2018-11-24T02:00:00Z',\n",
       "  '2018-11-24T03:00:00Z',\n",
       "  '2018-11-24T04:00:00Z',\n",
       "  '2018-11-24T05:00:00Z',\n",
       "  '2018-11-24T06:00:00Z',\n",
       "  '2018-11-24T07:00:00Z',\n",
       "  '2018-11-24T08:00:00Z',\n",
       "  '2018-11-24T09:00:00Z',\n",
       "  '2018-11-24T10:00:00Z',\n",
       "  '2018-11-24T11:00:00Z',\n",
       "  '2018-11-24T12:00:00Z',\n",
       "  '2018-11-24T13:00:00Z',\n",
       "  '2018-11-24T14:00:00Z',\n",
       "  '2018-11-24T15:00:00Z',\n",
       "  '2018-11-24T16:00:00Z',\n",
       "  '2018-11-24T17:00:00Z',\n",
       "  '2018-11-24T18:00:00Z',\n",
       "  '2018-11-24T19:00:00Z',\n",
       "  '2018-11-24T20:00:00Z',\n",
       "  '2018-11-24T21:00:00Z',\n",
       "  '2018-11-24T22:00:00Z',\n",
       "  '2018-11-24T23:00:00Z',\n",
       "  '2018-11-25T00:00:00Z',\n",
       "  '2018-11-25T01:00:00Z',\n",
       "  '2018-11-25T02:00:00Z',\n",
       "  '2018-11-25T03:00:00Z',\n",
       "  '2018-11-25T04:00:00Z',\n",
       "  '2018-11-25T05:00:00Z',\n",
       "  '2018-11-25T06:00:00Z',\n",
       "  '2018-11-25T07:00:00Z',\n",
       "  '2018-11-25T08:00:00Z',\n",
       "  '2018-11-25T09:00:00Z',\n",
       "  '2018-11-25T10:00:00Z',\n",
       "  '2018-11-25T11:00:00Z',\n",
       "  '2018-11-25T12:00:00Z',\n",
       "  '2018-11-25T13:00:00Z',\n",
       "  '2018-11-25T14:00:00Z',\n",
       "  '2018-11-25T15:00:00Z',\n",
       "  '2018-11-25T16:00:00Z',\n",
       "  '2018-11-25T17:00:00Z',\n",
       "  '2018-11-25T18:00:00Z',\n",
       "  '2018-11-25T19:00:00Z',\n",
       "  '2018-11-25T20:00:00Z',\n",
       "  '2018-11-25T21:00:00Z',\n",
       "  '2018-11-25T22:00:00Z',\n",
       "  '2018-11-25T23:00:00Z',\n",
       "  '2018-11-26T00:00:00Z',\n",
       "  '2018-11-26T01:00:00Z',\n",
       "  '2018-11-26T02:00:00Z',\n",
       "  '2018-11-26T03:00:00Z',\n",
       "  '2018-11-26T04:00:00Z',\n",
       "  '2018-11-26T05:00:00Z',\n",
       "  '2018-11-26T06:00:00Z',\n",
       "  '2018-11-26T07:00:00Z',\n",
       "  '2018-11-26T08:00:00Z',\n",
       "  '2018-11-26T09:00:00Z',\n",
       "  '2018-11-26T10:00:00Z',\n",
       "  '2018-11-26T11:00:00Z',\n",
       "  '2018-11-26T12:00:00Z',\n",
       "  '2018-11-26T13:00:00Z',\n",
       "  '2018-11-26T14:00:00Z',\n",
       "  '2018-11-26T15:00:00Z',\n",
       "  '2018-11-26T16:00:00Z',\n",
       "  '2018-11-26T17:00:00Z',\n",
       "  '2018-11-26T18:00:00Z',\n",
       "  '2018-11-26T19:00:00Z',\n",
       "  '2018-11-26T20:00:00Z',\n",
       "  '2018-11-26T21:00:00Z',\n",
       "  '2018-11-26T22:00:00Z',\n",
       "  '2018-11-26T23:00:00Z',\n",
       "  '2018-11-27T00:00:00Z',\n",
       "  '2018-11-27T01:00:00Z',\n",
       "  '2018-11-27T02:00:00Z',\n",
       "  '2018-11-27T03:00:00Z',\n",
       "  '2018-11-27T04:00:00Z',\n",
       "  '2018-11-27T05:00:00Z',\n",
       "  '2018-11-27T06:00:00Z',\n",
       "  '2018-11-27T07:00:00Z',\n",
       "  '2018-11-27T08:00:00Z',\n",
       "  '2018-11-27T09:00:00Z',\n",
       "  '2018-11-27T10:00:00Z',\n",
       "  '2018-11-27T11:00:00Z',\n",
       "  '2018-11-27T12:00:00Z',\n",
       "  '2018-11-27T13:00:00Z',\n",
       "  '2018-11-27T14:00:00Z',\n",
       "  '2018-11-27T15:00:00Z',\n",
       "  '2018-11-27T16:00:00Z',\n",
       "  '2018-11-27T17:00:00Z',\n",
       "  '2018-11-27T18:00:00Z',\n",
       "  '2018-11-27T19:00:00Z',\n",
       "  '2018-11-27T20:00:00Z',\n",
       "  '2018-11-27T21:00:00Z',\n",
       "  '2018-11-27T22:00:00Z',\n",
       "  '2018-11-27T23:00:00Z',\n",
       "  '2018-11-28T00:00:00Z',\n",
       "  '2018-11-28T01:00:00Z',\n",
       "  '2018-11-28T02:00:00Z',\n",
       "  '2018-11-28T03:00:00Z',\n",
       "  '2018-11-28T04:00:00Z',\n",
       "  '2018-11-28T05:00:00Z',\n",
       "  '2018-11-28T06:00:00Z',\n",
       "  '2018-11-28T07:00:00Z',\n",
       "  '2018-11-28T08:00:00Z',\n",
       "  '2018-11-28T09:00:00Z',\n",
       "  '2018-11-28T10:00:00Z',\n",
       "  '2018-11-28T11:00:00Z',\n",
       "  '2018-11-28T12:00:00Z',\n",
       "  '2018-11-28T13:00:00Z',\n",
       "  '2018-11-28T14:00:00Z',\n",
       "  '2018-11-28T15:00:00Z',\n",
       "  '2018-11-28T16:00:00Z',\n",
       "  '2018-11-28T17:00:00Z',\n",
       "  '2018-11-28T18:00:00Z',\n",
       "  '2018-11-28T19:00:00Z',\n",
       "  '2018-11-28T20:00:00Z',\n",
       "  '2018-11-28T21:00:00Z',\n",
       "  '2018-11-28T22:00:00Z',\n",
       "  '2018-11-28T23:00:00Z',\n",
       "  '2018-11-29T00:00:00Z',\n",
       "  '2018-11-29T01:00:00Z',\n",
       "  '2018-11-29T02:00:00Z',\n",
       "  '2018-11-29T03:00:00Z',\n",
       "  '2018-11-29T04:00:00Z',\n",
       "  '2018-11-29T05:00:00Z',\n",
       "  '2018-11-29T06:00:00Z',\n",
       "  '2018-11-29T07:00:00Z',\n",
       "  '2018-11-29T08:00:00Z',\n",
       "  '2018-11-29T09:00:00Z',\n",
       "  '2018-11-29T10:00:00Z',\n",
       "  '2018-11-29T11:00:00Z',\n",
       "  '2018-11-29T12:00:00Z',\n",
       "  '2018-11-29T13:00:00Z',\n",
       "  '2018-11-29T14:00:00Z',\n",
       "  '2018-11-29T15:00:00Z',\n",
       "  '2018-11-29T16:00:00Z',\n",
       "  '2018-11-29T17:00:00Z',\n",
       "  '2018-11-29T18:00:00Z',\n",
       "  '2018-11-29T19:00:00Z',\n",
       "  '2018-11-29T20:00:00Z',\n",
       "  '2018-11-29T21:00:00Z',\n",
       "  '2018-11-29T22:00:00Z',\n",
       "  '2018-11-29T23:00:00Z',\n",
       "  '2018-11-30T00:00:00Z',\n",
       "  '2018-11-30T01:00:00Z',\n",
       "  '2018-11-30T02:00:00Z',\n",
       "  '2018-11-30T03:00:00Z',\n",
       "  '2018-11-30T04:00:00Z',\n",
       "  '2018-11-30T05:00:00Z',\n",
       "  '2018-11-30T06:00:00Z',\n",
       "  '2018-11-30T07:00:00Z',\n",
       "  '2018-11-30T08:00:00Z',\n",
       "  '2018-11-30T09:00:00Z',\n",
       "  '2018-11-30T10:00:00Z',\n",
       "  '2018-11-30T11:00:00Z',\n",
       "  '2018-11-30T12:00:00Z'],\n",
       " 'wind_speed_set_1': [2.35,\n",
       "  1.4,\n",
       "  4.08,\n",
       "  4.0,\n",
       "  4.53,\n",
       "  3.83,\n",
       "  2.25,\n",
       "  1.75,\n",
       "  1.9,\n",
       "  1.9,\n",
       "  1.75,\n",
       "  1.4,\n",
       "  1.22,\n",
       "  1.56,\n",
       "  1.4,\n",
       "  2.18,\n",
       "  2.53,\n",
       "  2.43,\n",
       "  1.65,\n",
       "  5.03,\n",
       "  6.78,\n",
       "  6.01,\n",
       "  4.33,\n",
       "  5.03,\n",
       "  7.11,\n",
       "  5.46,\n",
       "  6.43,\n",
       "  6.78,\n",
       "  6.43,\n",
       "  5.81,\n",
       "  4.68,\n",
       "  4.88,\n",
       "  8.59,\n",
       "  5.31,\n",
       "  4.96,\n",
       "  5.38,\n",
       "  5.46,\n",
       "  5.03,\n",
       "  2.0,\n",
       "  2.18,\n",
       "  1.83,\n",
       "  1.22,\n",
       "  1.75,\n",
       "  3.03,\n",
       "  3.91,\n",
       "  2.68,\n",
       "  3.3,\n",
       "  2.35,\n",
       "  1.4,\n",
       "  2.0,\n",
       "  1.83,\n",
       "  2.1,\n",
       "  1.56,\n",
       "  1.75,\n",
       "  1.83,\n",
       "  2.43,\n",
       "  4.78,\n",
       "  4.08,\n",
       "  4.33,\n",
       "  3.56,\n",
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       "  0.95,\n",
       "  0.78,\n",
       "  0.95,\n",
       "  0.87,\n",
       "  0.52,\n",
       "  None,\n",
       "  1.75,\n",
       "  1.3,\n",
       "  2.0,\n",
       "  2.53,\n",
       "  2.95,\n",
       "  6.96,\n",
       "  6.01,\n",
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       "  9.04,\n",
       "  8.59,\n",
       "  10.34,\n",
       "  10.87,\n",
       "  12.34,\n",
       "  15.12,\n",
       "  16.78,\n",
       "  14.95,\n",
       "  11.9,\n",
       "  9.39,\n",
       "  7.99,\n",
       "  8.16,\n",
       "  12.07,\n",
       "  13.02,\n",
       "  11.22,\n",
       "  10.59,\n",
       "  11.29,\n",
       "  13.22,\n",
       "  13.12,\n",
       "  11.04,\n",
       "  11.72,\n",
       "  9.64,\n",
       "  10.94,\n",
       "  9.39,\n",
       "  9.12,\n",
       "  7.31,\n",
       "  6.34,\n",
       "  4.88,\n",
       "  3.83,\n",
       "  4.78,\n",
       "  3.21,\n",
       "  2.68,\n",
       "  1.48,\n",
       "  1.9,\n",
       "  1.75,\n",
       "  2.35,\n",
       "  1.65,\n",
       "  2.35,\n",
       "  2.6,\n",
       "  2.0,\n",
       "  2.25,\n",
       "  1.75,\n",
       "  5.31,\n",
       "  4.08,\n",
       "  3.03,\n",
       "  2.6,\n",
       "  2.6,\n",
       "  2.68,\n",
       "  2.43,\n",
       "  1.65,\n",
       "  2.1,\n",
       "  2.0,\n",
       "  2.1,\n",
       "  1.9,\n",
       "  1.56,\n",
       "  1.65,\n",
       "  1.48,\n",
       "  1.65,\n",
       "  2.43,\n",
       "  2.18,\n",
       "  3.48,\n",
       "  5.56,\n",
       "  7.56,\n",
       "  8.59,\n",
       "  10.24,\n",
       "  10.94,\n",
       "  9.82,\n",
       "  10.34,\n",
       "  10.34,\n",
       "  10.59,\n",
       "  10.24,\n",
       "  9.64,\n",
       "  9.56,\n",
       "  9.99,\n",
       "  9.12,\n",
       "  10.44,\n",
       "  11.9,\n",
       "  8.79,\n",
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       "  5.56,\n",
       "  1.56,\n",
       "  0.78,\n",
       "  0.87,\n",
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       "  2.35,\n",
       "  3.48,\n",
       "  4.08,\n",
       "  6.01,\n",
       "  5.46,\n",
       "  7.21,\n",
       "  7.04,\n",
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       "  4.53,\n",
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       "  4.78,\n",
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       "  6.08,\n",
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       "  5.56,\n",
       "  6.34,\n",
       "  6.43,\n",
       "  3.48,\n",
       "  2.6,\n",
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       "  1.48,\n",
       "  1.75,\n",
       "  1.9,\n",
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       "  1.4,\n",
       "  1.56,\n",
       "  1.56,\n",
       "  1.56,\n",
       "  1.48,\n",
       "  1.56,\n",
       "  1.56,\n",
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       "  5.38,\n",
       "  6.43,\n",
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       "  7.74,\n",
       "  8.16,\n",
       "  7.81,\n",
       "  7.46,\n",
       "  7.99,\n",
       "  6.61,\n",
       "  5.66,\n",
       "  4.88,\n",
       "  3.03,\n",
       "  6.16,\n",
       "  7.99,\n",
       "  6.86,\n",
       "  6.08,\n",
       "  4.26,\n",
       "  3.73,\n",
       "  5.46,\n",
       "  5.56,\n",
       "  5.38,\n",
       "  4.0,\n",
       "  3.48,\n",
       "  0.95,\n",
       "  0.52,\n",
       "  2.25,\n",
       "  1.05,\n",
       "  1.56,\n",
       "  1.65,\n",
       "  2.78,\n",
       "  4.08,\n",
       "  2.43,\n",
       "  5.13,\n",
       "  4.26,\n",
       "  4.78,\n",
       "  5.03,\n",
       "  6.61,\n",
       "  6.51,\n",
       "  6.43,\n",
       "  6.51,\n",
       "  5.38,\n",
       "  4.78,\n",
       "  3.65,\n",
       "  3.48,\n",
       "  4.33,\n",
       "  3.73,\n",
       "  2.18,\n",
       "  2.43,\n",
       "  3.65,\n",
       "  1.9,\n",
       "  0.95,\n",
       "  0.78,\n",
       "  1.05,\n",
       "  0.7,\n",
       "  0.87,\n",
       "  1.13,\n",
       "  0.95,\n",
       "  1.13,\n",
       "  1.22,\n",
       "  0.95,\n",
       "  1.05,\n",
       "  1.13,\n",
       "  1.3,\n",
       "  2.35,\n",
       "  1.65,\n",
       "  2.6,\n",
       "  2.95,\n",
       "  2.6,\n",
       "  3.03,\n",
       "  1.9,\n",
       "  0.87,\n",
       "  0.52,\n",
       "  0.43,\n",
       "  0.78,\n",
       "  0.95,\n",
       "  0.95,\n",
       "  0.78,\n",
       "  1.22,\n",
       "  1.05,\n",
       "  1.65,\n",
       "  1.56,\n",
       "  2.18,\n",
       "  1.13,\n",
       "  0.87,\n",
       "  1.4,\n",
       "  2.0,\n",
       "  1.3,\n",
       "  0.6,\n",
       "  0.52,\n",
       "  0.95,\n",
       "  0.87,\n",
       "  0.7,\n",
       "  0.52,\n",
       "  0.52,\n",
       "  0.35,\n",
       "  0.7,\n",
       "  1.48,\n",
       "  1.65,\n",
       "  1.48,\n",
       "  2.1,\n",
       "  2.43,\n",
       "  2.43,\n",
       "  2.25,\n",
       "  2.88,\n",
       "  2.6,\n",
       "  3.56,\n",
       "  5.38,\n",
       "  2.6,\n",
       "  2.43,\n",
       "  1.48,\n",
       "  0.95,\n",
       "  0.95,\n",
       "  0.95,\n",
       "  1.4,\n",
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       "  1.56,\n",
       "  1.3,\n",
       "  1.75,\n",
       "  1.75,\n",
       "  1.65,\n",
       "  2.0,\n",
       "  1.56,\n",
       "  1.22,\n",
       "  1.56,\n",
       "  1.3,\n",
       "  1.75,\n",
       "  2.18,\n",
       "  1.4,\n",
       "  1.65,\n",
       "  1.83,\n",
       "  1.83,\n",
       "  2.25,\n",
       "  1.83,\n",
       "  0.78,\n",
       "  1.13,\n",
       "  1.13,\n",
       "  1.56,\n",
       "  1.48,\n",
       "  1.65,\n",
       "  1.65,\n",
       "  4.0,\n",
       "  5.21,\n",
       "  4.61,\n",
       "  1.65,\n",
       "  2.25,\n",
       "  2.25,\n",
       "  2.53,\n",
       "  2.43,\n",
       "  2.78,\n",
       "  2.95,\n",
       "  3.21,\n",
       "  3.48,\n",
       "  4.33,\n",
       "  5.13,\n",
       "  5.21,\n",
       "  4.68,\n",
       "  2.68,\n",
       "  0.95,\n",
       "  0.87,\n",
       "  1.22,\n",
       "  1.65,\n",
       "  1.75,\n",
       "  2.35,\n",
       "  5.38,\n",
       "  6.43,\n",
       "  6.01,\n",
       "  7.21,\n",
       "  3.3,\n",
       "  3.21,\n",
       "  2.78,\n",
       "  2.0,\n",
       "  2.35,\n",
       "  2.6,\n",
       "  4.08,\n",
       "  2.78,\n",
       "  4.96,\n",
       "  6.43,\n",
       "  6.61,\n",
       "  4.26,\n",
       "  3.65,\n",
       "  4.78,\n",
       "  4.0,\n",
       "  2.6,\n",
       "  2.88,\n",
       "  3.73,\n",
       "  4.33,\n",
       "  4.96,\n",
       "  5.91,\n",
       "  4.96,\n",
       "  4.78,\n",
       "  3.56,\n",
       "  1.75,\n",
       "  1.75,\n",
       "  0.7,\n",
       "  0.87,\n",
       "  0.78,\n",
       "  1.4,\n",
       "  1.22,\n",
       "  0.95,\n",
       "  1.13,\n",
       "  2.25,\n",
       "  2.53,\n",
       "  2.53,\n",
       "  2.18,\n",
       "  2.95,\n",
       "  1.3,\n",
       "  0.95,\n",
       "  1.05,\n",
       "  1.22,\n",
       "  1.56,\n",
       "  1.65,\n",
       "  1.65,\n",
       "  2.25,\n",
       "  2.25,\n",
       "  2.18,\n",
       "  2.35,\n",
       "  2.18,\n",
       "  2.43,\n",
       "  2.35,\n",
       "  2.25,\n",
       "  2.18,\n",
       "  4.33,\n",
       "  1.65,\n",
       "  2.0,\n",
       "  0.7,\n",
       "  1.65,\n",
       "  2.68,\n",
       "  2.53,\n",
       "  3.48,\n",
       "  1.65,\n",
       "  0.7,\n",
       "  1.4,\n",
       "  1.3,\n",
       "  1.13,\n",
       "  1.4,\n",
       "  1.48,\n",
       "  1.48,\n",
       "  1.83,\n",
       "  1.9,\n",
       "  2.1,\n",
       "  2.25,\n",
       "  2.18,\n",
       "  2.43,\n",
       "  2.1,\n",
       "  1.56,\n",
       "  2.35,\n",
       "  3.21,\n",
       "  1.56,\n",
       "  1.65,\n",
       "  3.21,\n",
       "  5.38,\n",
       "  4.26,\n",
       "  6.34,\n",
       "  9.12,\n",
       "  8.86,\n",
       "  6.96,\n",
       "  6.78,\n",
       "  5.38,\n",
       "  4.26,\n",
       "  5.13,\n",
       "  5.91,\n",
       "  6.34,\n",
       "  6.69,\n",
       "  5.81,\n",
       "  5.91,\n",
       "  4.78,\n",
       "  5.38,\n",
       "  4.43,\n",
       "  6.86,\n",
       "  8.09,\n",
       "  9.39,\n",
       "  10.87,\n",
       "  12.42,\n",
       "  11.99,\n",
       "  10.34,\n",
       "  10.44,\n",
       "  12.07,\n",
       "  11.64,\n",
       "  11.9,\n",
       "  12.42,\n",
       "  8.51,\n",
       "  9.39,\n",
       "  13.9,\n",
       "  12.52,\n",
       "  9.56,\n",
       "  14.15,\n",
       "  14.25,\n",
       "  13.55,\n",
       "  10.69,\n",
       "  11.99,\n",
       "  8.51,\n",
       "  5.38,\n",
       "  8.51,\n",
       "  11.29,\n",
       "  5.38,\n",
       "  5.46,\n",
       "  6.43,\n",
       "  9.12,\n",
       "  6.78,\n",
       "  12.34,\n",
       "  6.86,\n",
       "  10.09,\n",
       "  11.72,\n",
       "  14.15,\n",
       "  15.3,\n",
       "  16.43,\n",
       "  17.46,\n",
       "  9.64,\n",
       "  11.72,\n",
       "  11.04,\n",
       "  9.39,\n",
       "  8.79,\n",
       "  10.09,\n",
       "  11.04,\n",
       "  12.69,\n",
       "  9.12,\n",
       "  10.87,\n",
       "  17.73,\n",
       "  18.86,\n",
       "  17.13,\n",
       "  16.0,\n",
       "  14.85,\n",
       "  12.6,\n",
       "  9.56,\n",
       "  10.94,\n",
       "  8.86,\n",
       "  9.64,\n",
       "  14.68,\n",
       "  18.51,\n",
       "  17.38,\n",
       "  19.21,\n",
       "  13.37,\n",
       "  14.25,\n",
       "  20.68,\n",
       "  18.93,\n",
       "  18.78,\n",
       "  19.71,\n",
       "  19.56,\n",
       "  21.36,\n",
       "  21.63,\n",
       "  20.25,\n",
       "  19.71,\n",
       "  19.9,\n",
       "  19.28,\n",
       "  19.56,\n",
       "  19.71,\n",
       "  19.71,\n",
       "  16.43,\n",
       "  16.43,\n",
       "  12.95,\n",
       "  14.85,\n",
       "  13.3,\n",
       "  10.69,\n",
       "  9.82,\n",
       "  7.91,\n",
       "  5.38,\n",
       "  3.21,\n",
       "  2.43,\n",
       "  1.13,\n",
       "  1.4,\n",
       "  1.3,\n",
       "  1.83,\n",
       "  1.4,\n",
       "  1.4,\n",
       "  1.83,\n",
       "  1.13,\n",
       "  2.35,\n",
       "  8.86,\n",
       "  2.88,\n",
       "  1.3,\n",
       "  1.65,\n",
       "  1.05,\n",
       "  0.87,\n",
       "  0.6,\n",
       "  0.35,\n",
       "  0.7,\n",
       "  0.95,\n",
       "  0.95,\n",
       "  0.87,\n",
       "  1.65,\n",
       "  2.43,\n",
       "  2.1,\n",
       "  1.56,\n",
       "  1.3,\n",
       "  1.48,\n",
       "  1.56,\n",
       "  1.05,\n",
       "  1.48,\n",
       "  1.4,\n",
       "  1.75,\n",
       "  0.87,\n",
       "  1.05,\n",
       "  1.48,\n",
       "  3.73,\n",
       "  3.3,\n",
       "  2.25,\n",
       "  3.65,\n",
       "  1.75,\n",
       "  0.6,\n",
       "  0.95,\n",
       "  1.56,\n",
       "  3.56,\n",
       "  3.65,\n",
       "  5.56,\n",
       "  7.91,\n",
       "  9.64,\n",
       "  10.09,\n",
       "  11.12,\n",
       "  10.69,\n",
       "  9.12,\n",
       "  11.82,\n",
       "  10.87,\n",
       "  5.13,\n",
       "  5.46,\n",
       "  6.16,\n",
       "  4.61,\n",
       "  6.51,\n",
       "  6.26,\n",
       "  6.43,\n",
       "  6.43,\n",
       "  9.04,\n",
       "  10.59,\n",
       "  8.94,\n",
       "  11.64,\n",
       "  9.39,\n",
       "  12.07,\n",
       "  9.12,\n",
       "  5.81,\n",
       "  6.96,\n",
       "  5.81,\n",
       "  5.66,\n",
       "  7.46,\n",
       "  11.12,\n",
       "  10.87,\n",
       "  8.59,\n",
       "  10.17,\n",
       "  9.47,\n",
       "  11.82,\n",
       "  9.21,\n",
       "  11.29,\n",
       "  8.59,\n",
       "  9.99,\n",
       "  9.56,\n",
       "  5.81,\n",
       "  4.88,\n",
       "  9.29,\n",
       "  10.17,\n",
       "  10.24,\n",
       "  11.04,\n",
       "  9.56,\n",
       "  9.29,\n",
       "  9.47,\n",
       "  6.78,\n",
       "  4.96,\n",
       "  4.78,\n",
       "  4.0,\n",
       "  7.91,\n",
       "  8.59,\n",
       "  6.26,\n",
       "  9.74,\n",
       "  10.59,\n",
       "  2.43,\n",
       "  2.43,\n",
       "  9.29,\n",
       "  15.2,\n",
       "  13.55,\n",
       "  11.72,\n",
       "  10.94,\n",
       "  8.16,\n",
       "  8.44,\n",
       "  5.38,\n",
       "  7.74,\n",
       "  13.22,\n",
       "  15.3,\n",
       "  14.25,\n",
       "  14.6,\n",
       "  9.47,\n",
       "  7.56,\n",
       "  5.91,\n",
       "  4.53,\n",
       "  2.88,\n",
       "  5.03,\n",
       "  6.78,\n",
       "  8.59,\n",
       "  9.47,\n",
       "  11.64,\n",
       "  9.12,\n",
       "  6.61,\n",
       "  4.96,\n",
       "  7.31],\n",
       " 'wind_direction_set_1': [93.0,\n",
       "  111.0,\n",
       "  82.0,\n",
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       "  85.0,\n",
       "  105.0,\n",
       "  116.0,\n",
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       "  285.0,\n",
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       "  311.0,\n",
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       "  313.0,\n",
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       "  347.0,\n",
       "  15.0,\n",
       "  31.0,\n",
       "  7.0,\n",
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       "  95.0,\n",
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       "  169.0,\n",
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       "  288.0,\n",
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       "  106.0,\n",
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       "  99.0,\n",
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       "  122.0,\n",
       "  79.0,\n",
       "  15.0,\n",
       "  357.0,\n",
       "  340.0,\n",
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       "  38.0,\n",
       "  108.0,\n",
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       "  125.0,\n",
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       "  190.0,\n",
       "  239.0,\n",
       "  223.0,\n",
       "  288.0,\n",
       "  302.0,\n",
       "  302.0,\n",
       "  358.0,\n",
       "  301.0,\n",
       "  275.0,\n",
       "  310.0,\n",
       "  319.0,\n",
       "  318.0,\n",
       "  360.0,\n",
       "  319.0,\n",
       "  306.0,\n",
       "  302.0,\n",
       "  298.0,\n",
       "  177.0,\n",
       "  168.0,\n",
       "  135.0,\n",
       "  139.0,\n",
       "  133.0,\n",
       "  137.0,\n",
       "  138.0,\n",
       "  147.0,\n",
       "  302.0,\n",
       "  311.0,\n",
       "  305.0,\n",
       "  302.0,\n",
       "  293.0,\n",
       "  301.0,\n",
       "  301.0,\n",
       "  304.0,\n",
       "  299.0,\n",
       "  292.0,\n",
       "  300.0,\n",
       "  320.0,\n",
       "  314.0,\n",
       "  318.0,\n",
       "  351.0,\n",
       "  275.0,\n",
       "  233.0,\n",
       "  167.0,\n",
       "  147.0,\n",
       "  144.0,\n",
       "  141.0,\n",
       "  130.0,\n",
       "  165.0,\n",
       "  257.0,\n",
       "  298.0,\n",
       "  299.0,\n",
       "  301.0,\n",
       "  299.0,\n",
       "  298.0,\n",
       "  287.0,\n",
       "  294.0,\n",
       "  299.0,\n",
       "  298.0,\n",
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       "  301.0,\n",
       "  299.0,\n",
       "  303.0,\n",
       "  304.0,\n",
       "  303.0,\n",
       "  265.0,\n",
       "  186.0,\n",
       "  149.0,\n",
       "  127.0,\n",
       "  140.0,\n",
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       "  175.0,\n",
       "  294.0,\n",
       "  305.0,\n",
       "  291.0,\n",
       "  306.0,\n",
       "  303.0,\n",
       "  297.0,\n",
       "  297.0,\n",
       "  297.0,\n",
       "  299.0,\n",
       "  304.0,\n",
       "  297.0,\n",
       "  300.0,\n",
       "  298.0,\n",
       "  302.0,\n",
       "  299.0,\n",
       "  298.0,\n",
       "  323.0,\n",
       "  280.0,\n",
       "  203.0,\n",
       "  146.0,\n",
       "  142.0,\n",
       "  147.0,\n",
       "  199.0,\n",
       "  286.0,\n",
       "  300.0,\n",
       "  296.0,\n",
       "  288.0,\n",
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       "  311.0,\n",
       "  312.0,\n",
       "  301.0,\n",
       "  302.0,\n",
       "  290.0,\n",
       "  299.0,\n",
       "  306.0,\n",
       "  275.0,\n",
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       "  315.0,\n",
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       "  293.0,\n",
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       "  9.0,\n",
       "  11.0,\n",
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       "  None,\n",
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       "  290.0,\n",
       "  321.0,\n",
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       "  266.0,\n",
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       "  250.0,\n",
       "  200.0,\n",
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       "  114.0,\n",
       "  145.0,\n",
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       "  80.0,\n",
       "  338.0,\n",
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       "  21.0,\n",
       "  327.0,\n",
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       "  314.0,\n",
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       "  286.0,\n",
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       "  187.0,\n",
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       "  147.0,\n",
       "  137.0,\n",
       "  83.0,\n",
       "  296.0,\n",
       "  291.0,\n",
       "  279.0,\n",
       "  279.0,\n",
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       "  278.0,\n",
       "  276.0,\n",
       "  304.0,\n",
       "  274.0]}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station_obs = station_data['OBSERVATIONS']\n",
    "station_obs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "696"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(station_obs['date_time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "obs_df = pd.DataFrame(station_obs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date_time</th>\n",
       "      <th>wind_speed_set_1</th>\n",
       "      <th>wind_direction_set_1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-11-01T12:00:00Z</td>\n",
       "      <td>2.35</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-11-01T13:00:00Z</td>\n",
       "      <td>1.40</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-11-01T14:00:00Z</td>\n",
       "      <td>4.08</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-11-01T15:00:00Z</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-11-01T16:00:00Z</td>\n",
       "      <td>4.53</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              date_time  wind_speed_set_1  wind_direction_set_1\n",
       "0  2018-11-01T12:00:00Z              2.35                  93.0\n",
       "1  2018-11-01T13:00:00Z              1.40                 111.0\n",
       "2  2018-11-01T14:00:00Z              4.08                  82.0\n",
       "3  2018-11-01T15:00:00Z              4.00                  75.0\n",
       "4  2018-11-01T16:00:00Z              4.53                  85.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obs_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 696 observations\n"
     ]
    }
   ],
   "source": [
    "obs_count = obs_df.shape [0]\n",
    "print(f'Found {obs_count} observations')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['obs_datetime'] = obs_df['date_time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['wind_speed'] = obs_df['wind_speed_set_1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['wind_direction'] = obs_df['wind_direction_set_1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>obs_datetime</th>\n",
       "      <th>wind_speed</th>\n",
       "      <th>wind_speed_units</th>\n",
       "      <th>wind_direction</th>\n",
       "      <th>fuel_moisture</th>\n",
       "      <th>fuel_moisture_units</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-11-01T12:00:00Z</td>\n",
       "      <td>2.35</td>\n",
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       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2018-11-01T13:00:00Z</td>\n",
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       "      <td>111.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-11-01T14:00:00Z</td>\n",
       "      <td>4.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>82.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-11-01T15:00:00Z</td>\n",
       "      <td>4.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-11-01T16:00:00Z</td>\n",
       "      <td>4.53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           obs_datetime  wind_speed wind_speed_units  wind_direction  \\\n",
       "0  2018-11-01T12:00:00Z        2.35              NaN            93.0   \n",
       "1  2018-11-01T13:00:00Z        1.40              NaN           111.0   \n",
       "2  2018-11-01T14:00:00Z        4.08              NaN            82.0   \n",
       "3  2018-11-01T15:00:00Z        4.00              NaN            75.0   \n",
       "4  2018-11-01T16:00:00Z        4.53              NaN            85.0   \n",
       "\n",
       "  fuel_moisture fuel_moisture_units  \n",
       "0           NaN                 NaN  \n",
       "1           NaN                 NaN  \n",
       "2           NaN                 NaN  \n",
       "3           NaN                 NaN  \n",
       "4           NaN                 NaN  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_station_data(response, i):\n",
    "    sdf = pd.DataFrame(columns=['station_id','station_name','obs_datetime','wind_speed','wind_speed_units','wind_direction','wkt'])\n",
    "    print(f'Extracting data for station {i}')\n",
    "    station_data = response.json()['STATION'][i]\n",
    "    \n",
    "    station_id = station_data['STID']\n",
    "    sdf['station_id'] = station_id\n",
    "    station_name = station_data['NAME']\n",
    "    sdf['station_name'] = station_name\n",
    "    lon = station_data['LONGITUDE']\n",
    "    lat = station_data['LATITUDE']\n",
    "    station_loc =  f\"POINT({lon} {lat})\"\n",
    "    sdf['wkt'] = station_loc\n",
    "    avail_sensors = list(station_data['SENSOR_VARIABLES'].keys())\n",
    "    print(f'Working on station {i}: {station_name}')\n",
    "    wsu = response.json()['UNITS']['wind_speed']\n",
    "    sdf['wind_speed_units'] = wsu\n",
    "    \n",
    "    sdf.head()\n",
    "    \n",
    "    # this gets a dictionary with date_time keys\n",
    "    station_obs = station_data['OBSERVATIONS']\n",
    "    obs_df = pd.DataFrame(station_obs)\n",
    "    obs_count = obs_df.size\n",
    "    print(f'Found {obs_count} observations')\n",
    "\n",
    "    if obs_count > 0:\n",
    "        try:\n",
    "            sdf['obs_datetime'] = obs_df['date_time']\n",
    "        except:\n",
    "            sdf['obs_datetime'] = None\n",
    "            print(f'Unexpected error: could not find data/times for observations for station {i}')\n",
    "        try:\n",
    "            sdf['wind_speed'] = obs_df['wind_speed_set_1']\n",
    "        except:\n",
    "            sdf['wind_speed'] = None\n",
    "            print(f'Wind speed data not available for station {i}, these sensors found: {avail_sensors}')\n",
    "        try:\n",
    "            sdf['wind_direction'] = obs_df['wind_direction_set_1']\n",
    "        except:\n",
    "            sdf['wind_direction'] = None\n",
    "        sdf['station_id'] = station_id\n",
    "        sdf['station_name'] = station_name\n",
    "        sdf['wkt'] = station_loc\n",
    "        sdf['wind_speed_units'] = wsu\n",
    "\n",
    "    else:\n",
    "        print(f'Unexpected result - found no observations for station')\n",
    "    sdf.set_index='obs_datetime'\n",
    "    return(sdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using s2 library\n",
      "Operating without GDAL library - functionality will be reduced\n",
      "Using pymapd version 0.9.0\n",
      "OmniSci connection established on python global variable \"con\"\n",
      "Using CPU memory (/dev/shm) for temp geo files\n",
      "Filesystem     1K-blocks  Used Available Use% Mounted on\n",
      "tmpfs          115549360 82192 115467168   1% /dev/shm\n"
     ]
    }
   ],
   "source": [
    "%run ../omnigeo.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>date_time</th>\n",
       "      <th>wind_speed_set_1</th>\n",
       "      <th>wind_direction_set_1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-11-01T12:00:00Z</td>\n",
       "      <td>2.35</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-11-01T13:00:00Z</td>\n",
       "      <td>1.40</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-11-01T14:00:00Z</td>\n",
       "      <td>4.08</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-11-01T15:00:00Z</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-11-01T16:00:00Z</td>\n",
       "      <td>4.53</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2018-11-01T17:00:00Z</td>\n",
       "      <td>3.83</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2018-11-01T18:00:00Z</td>\n",
       "      <td>2.25</td>\n",
       "      <td>116.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2018-11-01T19:00:00Z</td>\n",
       "      <td>1.75</td>\n",
       "      <td>124.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018-11-01T20:00:00Z</td>\n",
       "      <td>1.90</td>\n",
       "      <td>128.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2018-11-01T21:00:00Z</td>\n",
       "      <td>1.90</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018-11-01T22:00:00Z</td>\n",
       "      <td>1.75</td>\n",
       "      <td>146.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2018-11-01T23:00:00Z</td>\n",
       "      <td>1.40</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2018-11-02T00:00:00Z</td>\n",
       "      <td>1.22</td>\n",
       "      <td>147.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2018-11-02T01:00:00Z</td>\n",
       "      <td>1.56</td>\n",
       "      <td>303.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2018-11-02T02:00:00Z</td>\n",
       "      <td>1.40</td>\n",
       "      <td>322.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2018-11-02T03:00:00Z</td>\n",
       "      <td>2.18</td>\n",
       "      <td>289.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2018-11-02T04:00:00Z</td>\n",
       "      <td>2.53</td>\n",
       "      <td>297.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2018-11-02T05:00:00Z</td>\n",
       "      <td>2.43</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2018-11-02T06:00:00Z</td>\n",
       "      <td>1.65</td>\n",
       "      <td>315.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2018-11-02T07:00:00Z</td>\n",
       "      <td>5.03</td>\n",
       "      <td>301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2018-11-02T08:00:00Z</td>\n",
       "      <td>6.78</td>\n",
       "      <td>301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2018-11-02T09:00:00Z</td>\n",
       "      <td>6.01</td>\n",
       "      <td>298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2018-11-02T10:00:00Z</td>\n",
       "      <td>4.33</td>\n",
       "      <td>299.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2018-11-02T11:00:00Z</td>\n",
       "      <td>5.03</td>\n",
       "      <td>292.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2018-11-02T12:00:00Z</td>\n",
       "      <td>7.11</td>\n",
       "      <td>285.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2018-11-02T13:00:00Z</td>\n",
       "      <td>5.46</td>\n",
       "      <td>297.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2018-11-02T14:00:00Z</td>\n",
       "      <td>6.43</td>\n",
       "      <td>291.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2018-11-02T15:00:00Z</td>\n",
       "      <td>6.78</td>\n",
       "      <td>293.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2018-11-02T16:00:00Z</td>\n",
       "      <td>6.43</td>\n",
       "      <td>306.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2018-11-02T17:00:00Z</td>\n",
       "      <td>5.81</td>\n",
       "      <td>315.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>666</th>\n",
       "      <td>2018-11-29T07:00:00Z</td>\n",
       "      <td>10.59</td>\n",
       "      <td>243.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>667</th>\n",
       "      <td>2018-11-29T08:00:00Z</td>\n",
       "      <td>2.43</td>\n",
       "      <td>136.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>668</th>\n",
       "      <td>2018-11-29T09:00:00Z</td>\n",
       "      <td>2.43</td>\n",
       "      <td>167.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>669</th>\n",
       "      <td>2018-11-29T10:00:00Z</td>\n",
       "      <td>9.29</td>\n",
       "      <td>213.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>670</th>\n",
       "      <td>2018-11-29T11:00:00Z</td>\n",
       "      <td>15.20</td>\n",
       "      <td>233.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>671</th>\n",
       "      <td>2018-11-29T12:00:00Z</td>\n",
       "      <td>13.55</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>672</th>\n",
       "      <td>2018-11-29T13:00:00Z</td>\n",
       "      <td>11.72</td>\n",
       "      <td>279.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>673</th>\n",
       "      <td>2018-11-29T14:00:00Z</td>\n",
       "      <td>10.94</td>\n",
       "      <td>303.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>674</th>\n",
       "      <td>2018-11-29T15:00:00Z</td>\n",
       "      <td>8.16</td>\n",
       "      <td>341.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>675</th>\n",
       "      <td>2018-11-29T16:00:00Z</td>\n",
       "      <td>8.44</td>\n",
       "      <td>351.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>676</th>\n",
       "      <td>2018-11-29T17:00:00Z</td>\n",
       "      <td>5.38</td>\n",
       "      <td>149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>677</th>\n",
       "      <td>2018-11-29T18:00:00Z</td>\n",
       "      <td>7.74</td>\n",
       "      <td>167.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>678</th>\n",
       "      <td>2018-11-29T19:00:00Z</td>\n",
       "      <td>13.22</td>\n",
       "      <td>203.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>679</th>\n",
       "      <td>2018-11-29T20:00:00Z</td>\n",
       "      <td>15.30</td>\n",
       "      <td>227.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>680</th>\n",
       "      <td>2018-11-29T21:00:00Z</td>\n",
       "      <td>14.25</td>\n",
       "      <td>220.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681</th>\n",
       "      <td>2018-11-29T22:00:00Z</td>\n",
       "      <td>14.60</td>\n",
       "      <td>224.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682</th>\n",
       "      <td>2018-11-29T23:00:00Z</td>\n",
       "      <td>9.47</td>\n",
       "      <td>187.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>683</th>\n",
       "      <td>2018-11-30T00:00:00Z</td>\n",
       "      <td>7.56</td>\n",
       "      <td>187.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>684</th>\n",
       "      <td>2018-11-30T01:00:00Z</td>\n",
       "      <td>5.91</td>\n",
       "      <td>147.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>685</th>\n",
       "      <td>2018-11-30T02:00:00Z</td>\n",
       "      <td>4.53</td>\n",
       "      <td>137.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>686</th>\n",
       "      <td>2018-11-30T03:00:00Z</td>\n",
       "      <td>2.88</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>687</th>\n",
       "      <td>2018-11-30T04:00:00Z</td>\n",
       "      <td>5.03</td>\n",
       "      <td>296.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>688</th>\n",
       "      <td>2018-11-30T05:00:00Z</td>\n",
       "      <td>6.78</td>\n",
       "      <td>291.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>689</th>\n",
       "      <td>2018-11-30T06:00:00Z</td>\n",
       "      <td>8.59</td>\n",
       "      <td>279.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>690</th>\n",
       "      <td>2018-11-30T07:00:00Z</td>\n",
       "      <td>9.47</td>\n",
       "      <td>279.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>691</th>\n",
       "      <td>2018-11-30T08:00:00Z</td>\n",
       "      <td>11.64</td>\n",
       "      <td>282.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>692</th>\n",
       "      <td>2018-11-30T09:00:00Z</td>\n",
       "      <td>9.12</td>\n",
       "      <td>278.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>693</th>\n",
       "      <td>2018-11-30T10:00:00Z</td>\n",
       "      <td>6.61</td>\n",
       "      <td>276.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>694</th>\n",
       "      <td>2018-11-30T11:00:00Z</td>\n",
       "      <td>4.96</td>\n",
       "      <td>304.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>695</th>\n",
       "      <td>2018-11-30T12:00:00Z</td>\n",
       "      <td>7.31</td>\n",
       "      <td>274.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>696 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                date_time  wind_speed_set_1  wind_direction_set_1\n",
       "0    2018-11-01T12:00:00Z              2.35                  93.0\n",
       "1    2018-11-01T13:00:00Z              1.40                 111.0\n",
       "2    2018-11-01T14:00:00Z              4.08                  82.0\n",
       "3    2018-11-01T15:00:00Z              4.00                  75.0\n",
       "4    2018-11-01T16:00:00Z              4.53                  85.0\n",
       "5    2018-11-01T17:00:00Z              3.83                 105.0\n",
       "6    2018-11-01T18:00:00Z              2.25                 116.0\n",
       "7    2018-11-01T19:00:00Z              1.75                 124.0\n",
       "8    2018-11-01T20:00:00Z              1.90                 128.0\n",
       "9    2018-11-01T21:00:00Z              1.90                 159.0\n",
       "10   2018-11-01T22:00:00Z              1.75                 146.0\n",
       "11   2018-11-01T23:00:00Z              1.40                 129.0\n",
       "12   2018-11-02T00:00:00Z              1.22                 147.0\n",
       "13   2018-11-02T01:00:00Z              1.56                 303.0\n",
       "14   2018-11-02T02:00:00Z              1.40                 322.0\n",
       "15   2018-11-02T03:00:00Z              2.18                 289.0\n",
       "16   2018-11-02T04:00:00Z              2.53                 297.0\n",
       "17   2018-11-02T05:00:00Z              2.43                 300.0\n",
       "18   2018-11-02T06:00:00Z              1.65                 315.0\n",
       "19   2018-11-02T07:00:00Z              5.03                 301.0\n",
       "20   2018-11-02T08:00:00Z              6.78                 301.0\n",
       "21   2018-11-02T09:00:00Z              6.01                 298.0\n",
       "22   2018-11-02T10:00:00Z              4.33                 299.0\n",
       "23   2018-11-02T11:00:00Z              5.03                 292.0\n",
       "24   2018-11-02T12:00:00Z              7.11                 285.0\n",
       "25   2018-11-02T13:00:00Z              5.46                 297.0\n",
       "26   2018-11-02T14:00:00Z              6.43                 291.0\n",
       "27   2018-11-02T15:00:00Z              6.78                 293.0\n",
       "28   2018-11-02T16:00:00Z              6.43                 306.0\n",
       "29   2018-11-02T17:00:00Z              5.81                 315.0\n",
       "..                    ...               ...                   ...\n",
       "666  2018-11-29T07:00:00Z             10.59                 243.0\n",
       "667  2018-11-29T08:00:00Z              2.43                 136.0\n",
       "668  2018-11-29T09:00:00Z              2.43                 167.0\n",
       "669  2018-11-29T10:00:00Z              9.29                 213.0\n",
       "670  2018-11-29T11:00:00Z             15.20                 233.0\n",
       "671  2018-11-29T12:00:00Z             13.55                 198.0\n",
       "672  2018-11-29T13:00:00Z             11.72                 279.0\n",
       "673  2018-11-29T14:00:00Z             10.94                 303.0\n",
       "674  2018-11-29T15:00:00Z              8.16                 341.0\n",
       "675  2018-11-29T16:00:00Z              8.44                 351.0\n",
       "676  2018-11-29T17:00:00Z              5.38                 149.0\n",
       "677  2018-11-29T18:00:00Z              7.74                 167.0\n",
       "678  2018-11-29T19:00:00Z             13.22                 203.0\n",
       "679  2018-11-29T20:00:00Z             15.30                 227.0\n",
       "680  2018-11-29T21:00:00Z             14.25                 220.0\n",
       "681  2018-11-29T22:00:00Z             14.60                 224.0\n",
       "682  2018-11-29T23:00:00Z              9.47                 187.0\n",
       "683  2018-11-30T00:00:00Z              7.56                 187.0\n",
       "684  2018-11-30T01:00:00Z              5.91                 147.0\n",
       "685  2018-11-30T02:00:00Z              4.53                 137.0\n",
       "686  2018-11-30T03:00:00Z              2.88                  83.0\n",
       "687  2018-11-30T04:00:00Z              5.03                 296.0\n",
       "688  2018-11-30T05:00:00Z              6.78                 291.0\n",
       "689  2018-11-30T06:00:00Z              8.59                 279.0\n",
       "690  2018-11-30T07:00:00Z              9.47                 279.0\n",
       "691  2018-11-30T08:00:00Z             11.64                 282.0\n",
       "692  2018-11-30T09:00:00Z              9.12                 278.0\n",
       "693  2018-11-30T10:00:00Z              6.61                 276.0\n",
       "694  2018-11-30T11:00:00Z              4.96                 304.0\n",
       "695  2018-11-30T12:00:00Z              7.31                 274.0\n",
       "\n",
       "[696 rows x 3 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obs_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting data for station 1\n",
      "Working on station 1: SQUAW VALLEY G.C.\n",
      "Found 2088 observations\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>station_id</th>\n",
       "      <th>station_name</th>\n",
       "      <th>obs_datetime</th>\n",
       "      <th>wind_speed</th>\n",
       "      <th>wind_speed_units</th>\n",
       "      <th>wind_direction</th>\n",
       "      <th>wkt</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SQWC1</td>\n",
       "      <td>SQUAW VALLEY G.C.</td>\n",
       "      <td>2018-11-01T12:00:00Z</td>\n",
       "      <td>2.35</td>\n",
       "      <td>knots</td>\n",
       "      <td>93.0</td>\n",
       "      <td>POINT(-120.26576 39.18986)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SQWC1</td>\n",
       "      <td>SQUAW VALLEY G.C.</td>\n",
       "      <td>2018-11-01T13:00:00Z</td>\n",
       "      <td>1.40</td>\n",
       "      <td>knots</td>\n",
       "      <td>111.0</td>\n",
       "      <td>POINT(-120.26576 39.18986)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SQWC1</td>\n",
       "      <td>SQUAW VALLEY G.C.</td>\n",
       "      <td>2018-11-01T14:00:00Z</td>\n",
       "      <td>4.08</td>\n",
       "      <td>knots</td>\n",
       "      <td>82.0</td>\n",
       "      <td>POINT(-120.26576 39.18986)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SQWC1</td>\n",
       "      <td>SQUAW VALLEY G.C.</td>\n",
       "      <td>2018-11-01T15:00:00Z</td>\n",
       "      <td>4.00</td>\n",
       "      <td>knots</td>\n",
       "      <td>75.0</td>\n",
       "      <td>POINT(-120.26576 39.18986)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SQWC1</td>\n",
       "      <td>SQUAW VALLEY G.C.</td>\n",
       "      <td>2018-11-01T16:00:00Z</td>\n",
       "      <td>4.53</td>\n",
       "      <td>knots</td>\n",
       "      <td>85.0</td>\n",
       "      <td>POINT(-120.26576 39.18986)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  station_id       station_name          obs_datetime  wind_speed  \\\n",
       "0      SQWC1  SQUAW VALLEY G.C.  2018-11-01T12:00:00Z        2.35   \n",
       "1      SQWC1  SQUAW VALLEY G.C.  2018-11-01T13:00:00Z        1.40   \n",
       "2      SQWC1  SQUAW VALLEY G.C.  2018-11-01T14:00:00Z        4.08   \n",
       "3      SQWC1  SQUAW VALLEY G.C.  2018-11-01T15:00:00Z        4.00   \n",
       "4      SQWC1  SQUAW VALLEY G.C.  2018-11-01T16:00:00Z        4.53   \n",
       "\n",
       "  wind_speed_units  wind_direction                         wkt  \n",
       "0            knots            93.0  POINT(-120.26576 39.18986)  \n",
       "1            knots           111.0  POINT(-120.26576 39.18986)  \n",
       "2            knots            82.0  POINT(-120.26576 39.18986)  \n",
       "3            knots            75.0  POINT(-120.26576 39.18986)  \n",
       "4            knots            85.0  POINT(-120.26576 39.18986)  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf = add_station_data(response, 1)\n",
    "sdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting data for station 0\n",
      "Working on station 0: Emigrant Gap, Blue Canyon Nyack Airport\n",
      "Found 27072 observations\n",
      "(9024, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 1\n",
      "Working on station 1: SQUAW VALLEY G.C.\n",
      "Found 2088 observations\n",
      "(696, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 2\n",
      "Working on station 2: HELL HOLE\n",
      "Found 2716 observations\n",
      "(679, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 3\n",
      "Working on station 3: LINCOLN\n",
      "Found 2784 observations\n",
      "(696, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 4\n",
      "Working on station 4: ROSEVILLE WATER TRMT PLT\n",
      "Found 7846 observations\n",
      "(3923, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 5\n",
      "Working on station 5: SEEDORCHARD\n",
      "Found 2784 observations\n",
      "(696, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 6\n",
      "Working on station 6: DUNCAN\n",
      "Found 2540 observations\n",
      "(635, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 7\n",
      "Working on station 7: Roseville-N Sunrise Blvd\n",
      "Found 1941 observations\n",
      "(647, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 8\n",
      "Working on station 8: Auburn Municipal Airport\n",
      "Found 6240 observations\n",
      "(2080, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 9\n",
      "Working on station 9: K6ALF Rocklin\n",
      "Found 8208 observations\n",
      "(2736, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 10\n",
      "Working on station 10: ONION CREEK NEAR SERENE LAKES 3SE\n",
      "Found 12324 observations\n",
      "(4108, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 11\n",
      "Working on station 11: CW6842 Alta\n",
      "Found 6069 observations\n",
      "(2023, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 12\n",
      "Working on station 12: N6ZQK Foresthill\n",
      "Found 11748 observations\n",
      "(3916, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 13\n",
      "Working on station 13: DW2336 Loomis\n",
      "Found 7419 observations\n",
      "(2473, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 14\n",
      "Working on station 14: Lincoln Regional Karl Harder Field\n",
      "Found 6240 observations\n",
      "(2080, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 15\n",
      "Working on station 15: HOMEWOOD\n",
      "Found 2784 observations\n",
      "(696, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 16\n",
      "Working on station 16: WB6EEQ Colfax\n",
      "Found 11601 observations\n",
      "(3867, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 17\n",
      "Working on station 17: DW7393 Auburn\n",
      "Found 5622 observations\n",
      "(1874, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 18\n",
      "Working on station 18: KE6OBI Foresthill\n",
      "Found 7485 observations\n",
      "(2495, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 19\n",
      "Working on station 19: DW8862 Auburn\n",
      "Found 8196 observations\n",
      "(2732, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 20\n",
      "Working on station 20: DW9019 Olympic Valley\n",
      "Found 8232 observations\n",
      "(2744, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 21\n",
      "Working on station 21: DW9413 Homewood\n",
      "Found 8184 observations\n",
      "(2728, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 22\n",
      "Working on station 22: DW9434 Colfax\n",
      "Found 7212 observations\n",
      "(2404, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 23\n",
      "Working on station 23: RCKLN1\n",
      "Found 1398 observations\n",
      "(466, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 24\n",
      "Working on station 24: EW3273 Tahoe City\n",
      "Found 5739 observations\n",
      "(1913, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 25\n",
      "Working on station 25: BEAR TRAP NEAR EMIGRANT GAP 17SSE  (BTP)\n",
      "Found 1962 observations\n",
      "(654, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 26\n",
      "Working on station 26: TB2 Lake Tahoe\n",
      "Found 1863 observations\n",
      "(621, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 27\n",
      "Working on station 27: TB3 Lake Tahoe\n",
      "Found 1863 observations\n",
      "(621, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 28\n",
      "Working on station 28: TB4 Lake Tahoe\n",
      "Found 1863 observations\n",
      "(621, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 29\n",
      "Working on station 29: Chickering American River Reserve (UCNRS)\n",
      "Found 12063 observations\n",
      "(4021, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 30\n",
      "Working on station 30: COLFAX CA\n",
      "Found 17994 observations\n",
      "(5998, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 31\n",
      "Working on station 31: BLUE CANYON CA\n",
      "Found 18819 observations\n",
      "(6273, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 32\n",
      "Working on station 32: EW4877 Lincoln\n",
      "Found 12384 observations\n",
      "(4128, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 33\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Working on station 33: EW6168 Lincoln\n",
      "Found 156 observations\n",
      "(52, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 34\n",
      "Working on station 34: CALFIRE 511\n",
      "Found 2784 observations\n",
      "(696, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 35\n",
      "Working on station 35: EW9372 Rocklin\n",
      "Found 11865 observations\n",
      "(3955, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 36\n",
      "Working on station 36: Roundhouse Bottom (Ward Mt)-Alpine\n",
      "Found 8106 observations\n",
      "(2702, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 37\n",
      "Working on station 37: Roundhouse Top (mid-slope Ward Mt)-Alpine\n",
      "Found 8106 observations\n",
      "(2702, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 38\n",
      "Working on station 38: Summit (Ward Mt)-Alpine\n",
      "Found 8106 observations\n",
      "(2702, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 39\n",
      "Working on station 39: Red Dog-Squaw\n",
      "Found 8007 observations\n",
      "(2669, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 40\n",
      "Working on station 40: Belmont-Squaw\n",
      "Found 7638 observations\n",
      "(2546, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 41\n",
      "Working on station 41: Siberia (Sierra Crest)-Squaw\n",
      "Found 8103 observations\n",
      "(2701, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 42\n",
      "Working on station 42: Alta-Bonnynook Road\n",
      "Found 12531 observations\n",
      "(4177, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 43\n",
      "Working on station 43: Foresthill Road West\n",
      "Found 12531 observations\n",
      "(4177, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 44\n",
      "Working on station 44: Foresthill Road East\n",
      "Found 12291 observations\n",
      "(4097, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 45\n",
      "Working on station 45: Scott Top-Alpine\n",
      "Found 6612 observations\n",
      "(2204, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 46\n",
      "Working on station 46: Sherwood Btm-Alpine\n",
      "Found 4414 observations\n",
      "(2207, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n",
      "Extracting data for station 47\n",
      "Working on station 47: Wallace Peak\n",
      "Found 12531 observations\n",
      "(4177, 7)\n",
      "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
      "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "#df = pd.DataFrame(columns=['station_id','station_name','obs_datetime','wind_speed','wind_speed_units','wind_direction','wkt'])\n",
    "\n",
    "list_of_dicts = []\n",
    "for i in range(0,station_count):\n",
    "    sdf = add_station_data(response, i)\n",
    "    print(sdf.shape)\n",
    "    print(sdf.columns)\n",
    "    list_of_dicts.append(sdf.to_dict())\n",
    "\n",
    "df = pd.DataFrame(list_of_dicts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(48, 7)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>obs_datetime</th>\n",
       "      <th>station_id</th>\n",
       "      <th>station_name</th>\n",
       "      <th>wind_direction</th>\n",
       "      <th>wind_speed</th>\n",
       "      <th>wind_speed_units</th>\n",
       "      <th>wkt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>{0: '2018-11-01T12:00:00Z', 1: '2018-11-01T12:...</td>\n",
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       "      <td>{0: 40.0, 1: 30.0, 2: 40.0, 3: 40.0, 4: 40.0, ...</td>\n",
       "      <td>{0: 8.01, 1: 9.0, 2: 9.0, 3: 6.01, 4: 7.0, 5: ...</td>\n",
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       "      <th>1</th>\n",
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       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: 93.0, 1: 111.0, 2: 82.0, 3: 75.0, 4: 85.0,...</td>\n",
       "      <td>{0: 2.35, 1: 1.4, 2: 4.08, 3: 4.0, 4: 4.53, 5:...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>{0: '2018-11-01T12:09:00Z', 1: '2018-11-01T13:...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: 172.0, 1: 157.0, 2: 171.0, 3: 172.0, 4: 18...</td>\n",
       "      <td>{0: 13.02, 1: 9.56, 2: 12.17, 3: 19.13, 4: 13....</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>{0: '2018-11-01T12:13:00Z', 1: '2018-11-01T13:...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: 87.0, 1: 64.0, 2: 98.0, 3: 86.0, 4: 104.0,...</td>\n",
       "      <td>{0: 1.75, 1: 2.6, 2: 2.6, 3: 2.6, 4: 0.87, 5: ...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>{0: '2018-11-01T12:10:00Z', 1: '2018-11-01T12:...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: None, 1: None, 2: None, 3: None, 4: None, ...</td>\n",
       "      <td>{0: 6.47, 1: 5.4, 2: 6.47, 3: 6.47, 4: 7.56, 5...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "      <td>{0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        obs_datetime  \\\n",
       "0  {0: '2018-11-01T12:00:00Z', 1: '2018-11-01T12:...   \n",
       "1  {0: '2018-11-01T12:00:00Z', 1: '2018-11-01T13:...   \n",
       "2  {0: '2018-11-01T12:09:00Z', 1: '2018-11-01T13:...   \n",
       "3  {0: '2018-11-01T12:13:00Z', 1: '2018-11-01T13:...   \n",
       "4  {0: '2018-11-01T12:10:00Z', 1: '2018-11-01T12:...   \n",
       "\n",
       "                                          station_id  \\\n",
       "0  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "1  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "2  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "3  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "4  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "\n",
       "                                        station_name  \\\n",
       "0  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "1  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "2  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "3  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "4  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "\n",
       "                                      wind_direction  \\\n",
       "0  {0: 40.0, 1: 30.0, 2: 40.0, 3: 40.0, 4: 40.0, ...   \n",
       "1  {0: 93.0, 1: 111.0, 2: 82.0, 3: 75.0, 4: 85.0,...   \n",
       "2  {0: 172.0, 1: 157.0, 2: 171.0, 3: 172.0, 4: 18...   \n",
       "3  {0: 87.0, 1: 64.0, 2: 98.0, 3: 86.0, 4: 104.0,...   \n",
       "4  {0: None, 1: None, 2: None, 3: None, 4: None, ...   \n",
       "\n",
       "                                          wind_speed  \\\n",
       "0  {0: 8.01, 1: 9.0, 2: 9.0, 3: 6.01, 4: 7.0, 5: ...   \n",
       "1  {0: 2.35, 1: 1.4, 2: 4.08, 3: 4.0, 4: 4.53, 5:...   \n",
       "2  {0: 13.02, 1: 9.56, 2: 12.17, 3: 19.13, 4: 13....   \n",
       "3  {0: 1.75, 1: 2.6, 2: 2.6, 3: 2.6, 4: 0.87, 5: ...   \n",
       "4  {0: 6.47, 1: 5.4, 2: 6.47, 3: 6.47, 4: 7.56, 5...   \n",
       "\n",
       "                                    wind_speed_units  \\\n",
       "0  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "1  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "2  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "3  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "4  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...   \n",
       "\n",
       "                                                 wkt  \n",
       "0  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...  \n",
       "1  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...  \n",
       "2  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...  \n",
       "3  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...  \n",
       "4  {0: nan, 1: nan, 2: nan, 3: nan, 4: nan, 5: na...  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9024, 7)"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "table_name = 'placer_co_winds'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Executing query: DROP TABLE placer_co_winds\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<pymapd.cursor.Cursor at 0x7eff13cf6c88>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapdql(f\"DROP TABLE {table_name}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['station_id', 'station_name', 'obs_datetime', 'wind_speed',\n",
       "       'wind_speed_units', 'wind_direction', 'wkt'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "ddl = \"station_id TEXT ENCODING DICT, station_name TEXT ENCODING DICT, \"\n",
    "ddl += \"obs_datetime timestamp, wind_speed float, wind_speed_units TEXT ENCODING DICT, \"\n",
    "ddl += \"wind_direction float, omnisci_geo GEOMETRY(point,4326)\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Executing query: CREATE TABLE placer_co_winds (station_id TEXT ENCODING DICT, station_name TEXT ENCODING DICT, obs_datetime timestamp, wind_speed float, wind_speed_units TEXT ENCODING DICT, wind_direction float, omnisci_geo GEOMETRY(point,4326))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<pymapd.cursor.Cursor at 0x7eff1b13f940>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapdql(f\"CREATE TABLE {table_name} ({ddl})\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/mapd4TB_2/demo/weather/placer_co_winds.csv'"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwdl = !pwd\n",
    "cwd = pwdl[0]\n",
    "full_path = cwd + '/' + 'placer_co_winds.csv'\n",
    "full_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting data for station 0\n",
      "Working on station 0: Emigrant Gap, Blue Canyon Nyack Airport\n",
      "Found 27072 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 1\n",
      "Working on station 1: SQUAW VALLEY G.C.\n",
      "Found 2088 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 2\n",
      "Working on station 2: HELL HOLE\n",
      "Found 2716 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 3\n",
      "Working on station 3: LINCOLN\n",
      "Found 2784 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 4\n",
      "Working on station 4: ROSEVILLE WATER TRMT PLT\n",
      "Found 7846 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 5\n",
      "Working on station 5: SEEDORCHARD\n",
      "Found 2784 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 6\n",
      "Working on station 6: DUNCAN\n",
      "Found 2540 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 7\n",
      "Working on station 7: Roseville-N Sunrise Blvd\n",
      "Found 1941 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 8\n",
      "Working on station 8: Auburn Municipal Airport\n",
      "Found 6240 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 9\n",
      "Working on station 9: K6ALF Rocklin\n",
      "Found 8208 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 10\n",
      "Working on station 10: ONION CREEK NEAR SERENE LAKES 3SE\n",
      "Found 12324 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 11\n",
      "Working on station 11: CW6842 Alta\n",
      "Found 6069 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 12\n",
      "Working on station 12: N6ZQK Foresthill\n",
      "Found 11748 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 13\n",
      "Working on station 13: DW2336 Loomis\n",
      "Found 7419 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 14\n",
      "Working on station 14: Lincoln Regional Karl Harder Field\n",
      "Found 6240 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 15\n",
      "Working on station 15: HOMEWOOD\n",
      "Found 2784 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 16\n",
      "Working on station 16: WB6EEQ Colfax\n",
      "Found 11601 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 17\n",
      "Working on station 17: DW7393 Auburn\n",
      "Found 5622 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 18\n",
      "Working on station 18: KE6OBI Foresthill\n",
      "Found 7485 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 19\n",
      "Working on station 19: DW8862 Auburn\n",
      "Found 8196 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 20\n",
      "Working on station 20: DW9019 Olympic Valley\n",
      "Found 8232 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 21\n",
      "Working on station 21: DW9413 Homewood\n",
      "Found 8184 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 22\n",
      "Working on station 22: DW9434 Colfax\n",
      "Found 7212 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 23\n",
      "Working on station 23: RCKLN1\n",
      "Found 1398 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 24\n",
      "Working on station 24: EW3273 Tahoe City\n",
      "Found 5739 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 25\n",
      "Working on station 25: BEAR TRAP NEAR EMIGRANT GAP 17SSE  (BTP)\n",
      "Found 1962 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 26\n",
      "Working on station 26: TB2 Lake Tahoe\n",
      "Found 1863 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 27\n",
      "Working on station 27: TB3 Lake Tahoe\n",
      "Found 1863 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 28\n",
      "Working on station 28: TB4 Lake Tahoe\n",
      "Found 1863 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 29\n",
      "Working on station 29: Chickering American River Reserve (UCNRS)\n",
      "Found 12063 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 30\n",
      "Working on station 30: COLFAX CA\n",
      "Found 17994 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 31\n",
      "Working on station 31: BLUE CANYON CA\n",
      "Found 18819 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 32\n",
      "Working on station 32: EW4877 Lincoln\n",
      "Found 12384 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 33\n",
      "Working on station 33: EW6168 Lincoln\n",
      "Found 156 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 34\n",
      "Working on station 34: CALFIRE 511\n",
      "Found 2784 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 35\n",
      "Working on station 35: EW9372 Rocklin\n",
      "Found 11865 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 36\n",
      "Working on station 36: Roundhouse Bottom (Ward Mt)-Alpine\n",
      "Found 8106 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 37\n",
      "Working on station 37: Roundhouse Top (mid-slope Ward Mt)-Alpine\n",
      "Found 8106 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 38\n",
      "Working on station 38: Summit (Ward Mt)-Alpine\n",
      "Found 8106 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 39\n",
      "Working on station 39: Red Dog-Squaw\n",
      "Found 8007 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 40\n",
      "Working on station 40: Belmont-Squaw\n",
      "Found 7638 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 41\n",
      "Working on station 41: Siberia (Sierra Crest)-Squaw\n",
      "Found 8103 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 42\n",
      "Working on station 42: Alta-Bonnynook Road\n",
      "Found 12531 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 43\n",
      "Working on station 43: Foresthill Road West\n",
      "Found 12531 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 44\n",
      "Working on station 44: Foresthill Road East\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 12291 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 45\n",
      "Working on station 45: Scott Top-Alpine\n",
      "Found 6612 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 46\n",
      "Working on station 46: Sherwood Btm-Alpine\n",
      "Found 4414 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n",
      "Extracting data for station 47\n",
      "Working on station 47: Wallace Peak\n",
      "Found 12531 observations\n",
      "Executing query: COPY placer_co_winds FROM '/mapd4TB_2/demo/weather/placer_co_winds.csv'\n"
     ]
    }
   ],
   "source": [
    "for i in range(0,station_count):\n",
    "    sdf = add_station_data(response, i)\n",
    "    sdf.to_csv(full_path,index=False)\n",
    "    mapdql(f\"COPY {table_name} FROM '{full_path}'\")"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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