london_weather.ipynb

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   "source": [
    "A replacement to Darksky is [Openweather](https://openweathermap.org/darksky-openweather), the API is quite similar, once you create your account, just fetch your API_KEY [here](https://home.openweathermap.org/api_keys)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import dateutil.parser\n",
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "API_KEY = \"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "lat, lon = 51.4859062, -0.0976355\n",
    "resp = requests.get(f\"https://api.openweathermap.org/data/2.5/onecall?lat={lat}&lon={lon}&appid={API_KEY}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp.text"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = resp.json()\n",
    "d"
   ]
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   "cell_type": "code",
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   "source": [
    "time_ = int(dateutil.parser.parse('08-06-2021', dayfirst=True).timestamp())\n",
    "url = f'https://api.openweathermap.org/data/2.5/onecall/timemachine?lat={lat}&lon={lon}&dt={time_}&exclude=current,minutely,alerts&units=metric&appid={API_KEY}'\n",
    "\n",
    "resp = requests.get(url)\n",
    "weather_small_df = pd.DataFrame(resp.json()['hourly'])\n",
    "weather_small_df['dt'] = pd.to_datetime(weather_small_df['dt'], unit='s')\n",
    "# weather_small_df.index = weather_small_df.set_index(['dt'], append=True)\n",
    "weather_small_df"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_small_df_idx = weather_small_df.set_index(['dt'], append=False)\n",
    "# weather_small_df_idx.index\n",
    "weather_small_df_idx.feels_like.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# time = int(dateutil.parser.parse('2021-06-08T00:00:00', dayfirst=False).timestamp())\n",
    "def get_daily_weather(time):\n",
    "#     print(time)\n",
    "    url = f'https://api.openweathermap.org/data/2.5/onecall/timemachine?lat={lat}&lon={lon}&dt={time}&exclude=current,minutely,alerts&units=metric&appid={API_KEY}'\n",
    "    resp = requests.get(url)\n",
    "    hourly_weather = resp.json()\n",
    "    hourly_weather = pd.DataFrame(resp.json()['hourly'])\n",
    "    hourly_weather['dt'] = pd.to_datetime(hourly_weather['dt'], unit='s')\n",
    "    hourly_weather_result = hourly_weather.set_index(['dt'], append=False)\n",
    "    return hourly_weather_result\n",
    "\n",
    "# hourly_weather = get_daily_weather(time)\n",
    "# hourly_weather.feels_like.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Openweather only provides with the last 5 days of historical data so, set your dates here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "range = pd.date_range(start='2021-06-08', end='2021-06-13', freq='d')\n",
    "range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_list = []\n",
    "for t in range:\n",
    "#     print(int(t.timestamp()))\n",
    "    daily_weather = get_daily_weather(int(t.timestamp()))\n",
    "    weather_list.append(daily_weather)\n",
    "# weather_list\n",
    "weather = pd.concat(weather_list)\n",
    "# weather.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "weather.feels_like.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = 'data/chicago_weather/weather.csv'\n",
    "weather.to_csv(file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_weather = pd.read_csv(file_path, index_col=0, parse_dates=True)\n",
    "new_weather.feels_like.plot()"
   ]
  }
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