{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Daily Weather Forecast\n",
"\n",
"This notebook gets the weather forecast for the city requested and shows the forecast and the temperature graph."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The input\n",
"\n",
"This cell will be replaced by the place parameter specified when you run the notebook using notebook execution:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"tags": [
"parameters"
]
},
"outputs": [],
"source": [
"place=\"Minneapolis, MN\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Convert the location to longitude and latitude\n",
"\n",
"In this section, we use the [geopy](https://geopy.readthedocs.io/en/stable/) library to get the latitude and longitude of the city from Open Street Map. "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from geopy.geocoders import Nominatim"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"geolocator = Nominatim(user_agent=\"sagemaker test app\")\n",
"location = geolocator.geocode(place)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"if location is None:\n",
" raise ValueError(\"Unknown place name: {}\".format(place))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Minneapolis, MN is at lat/long 44.9772995, -93.2654692\n"
]
}
],
"source": [
"latitude = location.latitude\n",
"longitude = location.longitude\n",
"\n",
"print(\"{} is at lat/long {}, {}\".format(place, latitude, longitude))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Use the NWS API to retrieve the forecast\n",
"\n",
"The National Weather Service has an [API](https://www.weather.gov/documentation/services-web-api) to retrieving forecasts for any lat/long combo in the United States. \n",
"\n",
"Getting the forecast from an arbitrary point is a two-stage process. First, you call the `points` endpoint to find the forecasts for the specified point. The result gives you URLs for hourly and twice-daily forecasts that cover that point. You retrieve those to get the actual forecast.\n",
"\n",
"All the results are in JSON, so they're easy to consume."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'https://api.weather.gov/points/44.9773,-93.2655'"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"info_url = \"https://api.weather.gov/points/{0:.4f},{1:.4f}\".format(latitude,longitude)\n",
"info_url"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We use the `requests` library to retrieve the JSON and then save it to a pandas dataframe."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"import json\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"response = requests.get(info_url)\n",
"# If the response was successful, no Exception will be raised\n",
"response.raise_for_status()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"info = json.loads(response.text)\n",
"forecastHourly_url = info[\"properties\"][\"forecastHourly\"]\n",
"forecast_url = info[\"properties\"][\"forecast\"]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"def get_forecast(url):\n",
" response = requests.get(url)\n",
" response.raise_for_status()\n",
"\n",
" forecast_data = json.loads(response.text)\n",
" forecast = pd.DataFrame(forecast_data[\"properties\"][\"periods\"])\n",
" forecast[\"startTime\"] = pd.to_datetime(forecast[\"startTime\"])\n",
" forecast[\"endTime\"] = pd.to_datetime(forecast[\"endTime\"])\n",
" return forecast\n",
"\n",
"hourly_forecast = get_forecast(forecastHourly_url)\n",
"daily_forecast = get_forecast(forecast_url)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Forecast for the next 24 hours"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" | \n",
" Temperature | \n",
" Wind | \n",
" Forecast | \n",
"
\n",
" \n",
" Date | \n",
" Time | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" May 21 | \n",
" 17:00 | \n",
" 69 | \n",
" 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 18:00 | \n",
" 69 | \n",
" 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 19:00 | \n",
" 69 | \n",
" 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 20:00 | \n",
" 69 | \n",
" 5 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 21:00 | \n",
" 67 | \n",
" 5 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 22:00 | \n",
" 65 | \n",
" 5 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 23:00 | \n",
" 64 | \n",
" 5 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" May 22 | \n",
" 00:00 | \n",
" 63 | \n",
" 5 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 01:00 | \n",
" 62 | \n",
" 5 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 02:00 | \n",
" 61 | \n",
" 5 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 03:00 | \n",
" 61 | \n",
" 5 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 04:00 | \n",
" 60 | \n",
" 5 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 05:00 | \n",
" 59 | \n",
" 5 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 06:00 | \n",
" 59 | \n",
" 5 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 07:00 | \n",
" 60 | \n",
" 5 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 08:00 | \n",
" 62 | \n",
" 5 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 09:00 | \n",
" 65 | \n",
" 10 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 10:00 | \n",
" 67 | \n",
" 10 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 11:00 | \n",
" 69 | \n",
" 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 12:00 | \n",
" 70 | \n",
" 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 13:00 | \n",
" 72 | \n",
" 10 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 14:00 | \n",
" 73 | \n",
" 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 15:00 | \n",
" 74 | \n",
" 10 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" 16:00 | \n",
" 74 | \n",
" 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Temperature Wind Forecast\n",
"Date Time \n",
"May 21 17:00 69 10 mph SSE Mostly Cloudy\n",
" 18:00 69 10 mph SSE Mostly Cloudy\n",
" 19:00 69 10 mph SSE Mostly Cloudy\n",
" 20:00 69 5 mph SSE Mostly Cloudy\n",
" 21:00 67 5 mph SSE Mostly Cloudy\n",
" 22:00 65 5 mph SSE Mostly Cloudy\n",
" 23:00 64 5 mph SSE Mostly Cloudy\n",
"May 22 00:00 63 5 mph SSE Mostly Cloudy\n",
" 01:00 62 5 mph SSE Mostly Cloudy\n",
" 02:00 61 5 mph SE Mostly Cloudy\n",
" 03:00 61 5 mph SE Mostly Cloudy\n",
" 04:00 60 5 mph SSE Mostly Cloudy\n",
" 05:00 59 5 mph SE Mostly Cloudy\n",
" 06:00 59 5 mph SE Mostly Cloudy\n",
" 07:00 60 5 mph SE Mostly Cloudy\n",
" 08:00 62 5 mph SE Mostly Cloudy\n",
" 09:00 65 10 mph SE Mostly Cloudy\n",
" 10:00 67 10 mph SE Mostly Cloudy\n",
" 11:00 69 10 mph SSE Mostly Cloudy\n",
" 12:00 70 10 mph SSE Mostly Cloudy\n",
" 13:00 72 10 mph SE Mostly Cloudy\n",
" 14:00 73 10 mph SSE Mostly Cloudy\n",
" 15:00 74 10 mph SE Mostly Cloudy\n",
" 16:00 74 10 mph SSE Mostly Cloudy"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"today = hourly_forecast[:24][[\"startTime\",\"temperature\",\"windSpeed\", \"windDirection\", \"shortForecast\"]]\n",
"today = today.rename(columns={\"temperature\": \"Temperature\", \"shortForecast\": \"Forecast\"})\n",
"today.insert(0, \"Date\", today[\"startTime\"].dt.strftime(\"%b %d\"))\n",
"today.insert(1, \"Time\", today[\"startTime\"].dt.strftime(\"%H:%M\"))\n",
"today.insert(4, \"Wind\", today[[\"windSpeed\", \"windDirection\"]].agg(' '.join, axis=1 ))\n",
"today = today.drop([\"startTime\", \"windSpeed\", \"windDirection\"], axis=\"columns\")\n",
"today.set_index(['Date', 'Time'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Forecast for the next week"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" When | Temperature | Wind | Forecast |
\n",
" \n",
" This Afternoon | \n",
" 71 | \n",
" 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" Tonight | \n",
" 59 | \n",
" 5 to 10 mph SSE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" Friday | \n",
" 74 | \n",
" 5 to 10 mph SE | \n",
" Mostly Cloudy | \n",
"
\n",
" \n",
" Friday Night | \n",
" 63 | \n",
" 5 to 10 mph ESE | \n",
" Chance Showers And Thunderstorms | \n",
"
\n",
" \n",
" Saturday | \n",
" 76 | \n",
" 5 to 10 mph SE | \n",
" Chance Showers And Thunderstorms then Showers And Thunderstorms Likely | \n",
"
\n",
" \n",
" Saturday Night | \n",
" 64 | \n",
" 0 to 5 mph SE | \n",
" Chance Showers And Thunderstorms then Mostly Cloudy | \n",
"
\n",
" \n",
" Sunday | \n",
" 82 | \n",
" 5 to 10 mph SSE | \n",
" Chance Showers And Thunderstorms | \n",
"
\n",
" \n",
" Sunday Night | \n",
" 62 | \n",
" 5 mph SW | \n",
" Showers And Thunderstorms Likely then Chance Showers And Thunderstorms | \n",
"
\n",
" \n",
" Memorial Day | \n",
" 76 | \n",
" 5 mph WNW | \n",
" Chance Showers And Thunderstorms | \n",
"
\n",
" \n",
" Monday Night | \n",
" 59 | \n",
" 0 to 5 mph WNW | \n",
" Chance Showers And Thunderstorms then Mostly Cloudy | \n",
"
\n",
" \n",
" Tuesday | \n",
" 79 | \n",
" 0 to 5 mph WNW | \n",
" Mostly Sunny | \n",
"
\n",
" \n",
" Tuesday Night | \n",
" 61 | \n",
" 0 to 5 mph SW | \n",
" Partly Cloudy | \n",
"
\n",
" \n",
" Wednesday | \n",
" 81 | \n",
" 0 to 5 mph SSW | \n",
" Mostly Sunny then Chance Showers And Thunderstorms | \n",
"
\n",
" \n",
" Wednesday Night | \n",
" 63 | \n",
" 5 mph SSW | \n",
" Chance Showers And Thunderstorms | \n",
"
\n",
"
"
],
"text/plain": [
""
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"week = daily_forecast[[\"name\",\"temperature\",\"windSpeed\", \"windDirection\", \"shortForecast\"]]\n",
"week = week.rename(columns={\"name\": \"When\", \"temperature\": \"Temperature\", \"shortForecast\": \"Forecast\"})\n",
"week.insert(4, \"Wind\", week[[\"windSpeed\", \"windDirection\"]].agg(' '.join, axis=1 ))\n",
"week = week.drop([\"windSpeed\", \"windDirection\"], axis=\"columns\")\n",
"week = week.style.hide_index()\n",
"week"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A chart of temperatures for the next 7 days\n",
"\n",
"We use the [Altair](https://altair-viz.github.io/index.html) charting library to render the hourly predicted temperatures for the next week."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"import altair as alt"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"nights_df=hourly_forecast.assign(new=hourly_forecast.isDaytime.diff().ne(0).cumsum()).groupby([\"isDaytime\", \"new\"]).agg({\"startTime\": min, \"endTime\": max}).reset_index()\n",
"nights_df=nights_df[nights_df[\"isDaytime\"]==False]\n",
"nights=alt.Chart(nights_df).mark_rect(color=\"#9E9CC9\").encode(x=\"startTime:T\", x2=\"endTime:T\")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"scaleMin = np.min(hourly_forecast[\"temperature\"])\n",
"scaleMin = int(scaleMin * 0.9)\n",
"scaleMin = scaleMin - (scaleMin % 5)\n",
"\n",
"scaleMax = np.max(hourly_forecast[\"temperature\"])\n",
"scaleMax = int(scaleMax * 1.1)\n",
"scaleMax = scaleMax + (5 - (scaleMax % 5))\n",
"domain = (scaleMin, scaleMax)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"temps = (alt.Chart(hourly_forecast, title=\"7-day Temperature Forecast for {}\".format(place)).\n",
" mark_line().\n",
" encode(x=alt.X(\"startTime\", title=\"Date\"),\n",
" y=alt.Y(\"temperature\", title=\"Temperature (°F)\",scale=alt.Scale(domain=domain))).\n",
" properties(width=700, height=300))"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.vegalite.v3+json": {
"$schema": "https://vega.github.io/schema/vega-lite/v3.4.0.json",
"config": {
"mark": {
"tooltip": null
},
"view": {
"height": 300,
"width": 400
}
},
"datasets": {
"data-ca9334b1b570a8e5b8c3c494abd88bd9": [
{
"detailedForecast": "",
"endTime": "2020-05-21T18:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/day/bkn?size=small",
"isDaytime": true,
"name": "",
"number": 1,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-21T17:00:00-05:00",
"temperature": 69,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "10 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-21T19:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 2,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-21T18:00:00-05:00",
"temperature": 69,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "10 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-21T20:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 3,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-21T19:00:00-05:00",
"temperature": 69,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "10 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-21T21:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 4,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-21T20:00:00-05:00",
"temperature": 69,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-21T22:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 5,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-21T21:00:00-05:00",
"temperature": 67,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-21T23:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 6,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-21T22:00:00-05:00",
"temperature": 65,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-22T00:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 7,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-21T23:00:00-05:00",
"temperature": 64,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-22T01:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 8,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-22T00:00:00-05:00",
"temperature": 63,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-22T02:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 9,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-22T01:00:00-05:00",
"temperature": 62,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-22T03:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 10,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-22T02:00:00-05:00",
"temperature": 61,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-22T04:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 11,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-22T03:00:00-05:00",
"temperature": 61,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-22T05:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 12,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-22T04:00:00-05:00",
"temperature": 60,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SSE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
"endTime": "2020-05-22T06:00:00-05:00",
"icon": "https://api.weather.gov/icons/land/night/bkn?size=small",
"isDaytime": false,
"name": "",
"number": 13,
"shortForecast": "Mostly Cloudy",
"startTime": "2020-05-22T05:00:00-05:00",
"temperature": 59,
"temperatureTrend": null,
"temperatureUnit": "F",
"windDirection": "SE",
"windSpeed": "5 mph"
},
{
"detailedForecast": "",
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"text/plain": [
"\n",
"\n",
"If you see this message, it means the renderer has not been properly enabled\n",
"for the frontend that you are using. For more information, see\n",
"https://altair-viz.github.io/user_guide/troubleshooting.html\n"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nights + temps"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Save the results with scrapbook\n",
"\n",
"We use [scrapbook](https://github.com/nteract/scrapbook) to save particular results of this run so that they can be retrieved later by reading the notebook.\n",
"\n",
"This will let us take the data from multiple runs of the notebook and compare it."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"application/scrapbook.scrap.text+json": {
"data": "Minneapolis, MN",
"encoder": "text",
"name": "place",
"version": 1
}
},
"metadata": {
"scrapbook": {
"data": true,
"display": false,
"name": "place"
}
},
"output_type": "display_data"
},
{
"data": {
"application/scrapbook.scrap.text+json": {
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Thunderstorms\"},\"detailedForecast\":{\"0\":\"\",\"1\":\"\",\"2\":\"\",\"3\":\"\",\"4\":\"\",\"5\":\"\",\"6\":\"\",\"7\":\"\",\"8\":\"\",\"9\":\"\",\"10\":\"\",\"11\":\"\",\"12\":\"\",\"13\":\"\",\"14\":\"\",\"15\":\"\",\"16\":\"\",\"17\":\"\",\"18\":\"\",\"19\":\"\",\"20\":\"\",\"21\":\"\",\"22\":\"\",\"23\":\"\",\"24\":\"\",\"25\":\"\",\"26\":\"\",\"27\":\"\",\"28\":\"\",\"29\":\"\",\"30\":\"\",\"31\":\"\",\"32\":\"\",\"33\":\"\",\"34\":\"\",\"35\":\"\",\"36\":\"\",\"37\":\"\",\"38\":\"\",\"39\":\"\",\"40\":\"\",\"41\":\"\",\"42\":\"\",\"43\":\"\",\"44\":\"\",\"45\":\"\",\"46\":\"\",\"47\":\"\",\"48\":\"\",\"49\":\"\",\"50\":\"\",\"51\":\"\",\"52\":\"\",\"53\":\"\",\"54\":\"\",\"55\":\"\",\"56\":\"\",\"57\":\"\",\"58\":\"\",\"59\":\"\",\"60\":\"\",\"61\":\"\",\"62\":\"\",\"63\":\"\",\"64\":\"\",\"65\":\"\",\"66\":\"\",\"67\":\"\",\"68\":\"\",\"69\":\"\",\"70\":\"\",\"71\":\"\",\"72\":\"\",\"73\":\"\",\"74\":\"\",\"75\":\"\",\"76\":\"\",\"77\":\"\",\"78\":\"\",\"79\":\"\",\"80\":\"\",\"81\":\"\",\"82\":\"\",\"83\":\"\",\"84\":\"\",\"85\":\"\",\"86\":\"\",\"87\":\"\",\"88\":\"\",\"89\":\"\",\"90\":\"\",\"91\":\"\",\"92\":\"\",\"93\":\"\",\"94\":\"\",\"95\":\"\",\"96\":\"\",\"97\":\"\",\"98\":\"\",\"99\":\"\",\"100\":\"\",\"101\":\"\",\"102\":\"\",\"103\":\"\",\"104\":\"\",\"105\":\"\",\"106\":\"\",\"107\":\"\",\"108\":\"\",\"109\":\"\",\"110\":\"\",\"111\":\"\",\"112\":\"\",\"113\":\"\",\"114\":\"\",\"115\":\"\",\"116\":\"\",\"117\":\"\",\"118\":\"\",\"119\":\"\",\"120\":\"\",\"121\":\"\",\"122\":\"\",\"123\":\"\",\"124\":\"\",\"125\":\"\",\"126\":\"\",\"127\":\"\",\"128\":\"\",\"129\":\"\",\"130\":\"\",\"131\":\"\",\"132\":\"\",\"133\":\"\",\"134\":\"\",\"135\":\"\",\"136\":\"\",\"137\":\"\",\"138\":\"\",\"139\":\"\",\"140\":\"\",\"141\":\"\",\"142\":\"\",\"143\":\"\",\"144\":\"\",\"145\":\"\",\"146\":\"\",\"147\":\"\",\"148\":\"\",\"149\":\"\",\"150\":\"\",\"151\":\"\",\"152\":\"\",\"153\":\"\",\"154\":\"\",\"155\":\"\"}}",
"encoder": "text",
"name": "hourly_forecast",
"version": 1
}
},
"metadata": {
"scrapbook": {
"data": true,
"display": false,
"name": "hourly_forecast"
}
},
"output_type": "display_data"
},
{
"data": {
"application/scrapbook.scrap.text+json": {
"data": "{\"number\":{\"0\":1,\"1\":2,\"2\":3,\"3\":4,\"4\":5,\"5\":6,\"6\":7,\"7\":8,\"8\":9,\"9\":10,\"10\":11,\"11\":12,\"12\":13,\"13\":14},\"name\":{\"0\":\"This Afternoon\",\"1\":\"Tonight\",\"2\":\"Friday\",\"3\":\"Friday Night\",\"4\":\"Saturday\",\"5\":\"Saturday Night\",\"6\":\"Sunday\",\"7\":\"Sunday Night\",\"8\":\"Memorial Day\",\"9\":\"Monday Night\",\"10\":\"Tuesday\",\"11\":\"Tuesday Night\",\"12\":\"Wednesday\",\"13\":\"Wednesday Night\"},\"startTime\":{\"0\":1590098400000,\"1\":1590102000000,\"2\":1590145200000,\"3\":1590188400000,\"4\":1590231600000,\"5\":1590274800000,\"6\":1590318000000,\"7\":1590361200000,\"8\":1590404400000,\"9\":1590447600000,\"10\":1590490800000,\"11\":1590534000000,\"12\":1590577200000,\"13\":1590620400000},\"endTime\":{\"0\":1590102000000,\"1\":1590145200000,\"2\":1590188400000,\"3\":1590231600000,\"4\":1590274800000,\"5\":1590318000000,\"6\":1590361200000,\"7\":1590404400000,\"8\":1590447600000,\"9\":1590490800000,\"10\":1590534000000,\"11\":1590577200000,\"12\":1590620400000,\"13\":1590663600000},\"isDaytime\":{\"0\":true,\"1\":false,\"2\":true,\"3\":false,\"4\":true,\"5\":false,\"6\":true,\"7\":false,\"8\":true,\"9\":false,\"10\":true,\"11\":false,\"12\":true,\"13\":false},\"temperature\":{\"0\":71,\"1\":59,\"2\":74,\"3\":63,\"4\":76,\"5\":64,\"6\":82,\"7\":62,\"8\":76,\"9\":59,\"10\":79,\"11\":61,\"12\":81,\"13\":63},\"temperatureUnit\":{\"0\":\"F\",\"1\":\"F\",\"2\":\"F\",\"3\":\"F\",\"4\":\"F\",\"5\":\"F\",\"6\":\"F\",\"7\":\"F\",\"8\":\"F\",\"9\":\"F\",\"10\":\"F\",\"11\":\"F\",\"12\":\"F\",\"13\":\"F\"},\"temperatureTrend\":{\"0\":null,\"1\":null,\"2\":null,\"3\":null,\"4\":null,\"5\":null,\"6\":null,\"7\":null,\"8\":null,\"9\":null,\"10\":null,\"11\":null,\"12\":null,\"13\":null},\"windSpeed\":{\"0\":\"10 mph\",\"1\":\"5 to 10 mph\",\"2\":\"5 to 10 mph\",\"3\":\"5 to 10 mph\",\"4\":\"5 to 10 mph\",\"5\":\"0 to 5 mph\",\"6\":\"5 to 10 mph\",\"7\":\"5 mph\",\"8\":\"5 mph\",\"9\":\"0 to 5 mph\",\"10\":\"0 to 5 mph\",\"11\":\"0 to 5 mph\",\"12\":\"0 to 5 mph\",\"13\":\"5 mph\"},\"windDirection\":{\"0\":\"SSE\",\"1\":\"SSE\",\"2\":\"SE\",\"3\":\"ESE\",\"4\":\"SE\",\"5\":\"SE\",\"6\":\"SSE\",\"7\":\"SW\",\"8\":\"WNW\",\"9\":\"WNW\",\"10\":\"WNW\",\"11\":\"SW\",\"12\":\"SSW\",\"13\":\"SSW\"},\"icon\":{\"0\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/day\\/bkn?size=medium\",\"1\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/night\\/bkn?size=medium\",\"2\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/day\\/bkn?size=medium\",\"3\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/night\\/tsra,30\\/tsra,50?size=medium\",\"4\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/day\\/tsra,60?size=medium\",\"5\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/night\\/tsra_hi,50\\/bkn?size=medium\",\"6\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/day\\/tsra_sct,50\\/tsra_sct,70?size=medium\",\"7\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/night\\/tsra,70\\/tsra,50?size=medium\",\"8\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/day\\/tsra_sct,30\\/tsra_sct,40?size=medium\",\"9\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/night\\/tsra_sct,40\\/bkn?size=medium\",\"10\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/day\\/sct?size=medium\",\"11\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/night\\/sct?size=medium\",\"12\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/day\\/sct\\/tsra_hi,30?size=medium\",\"13\":\"https:\\/\\/api.weather.gov\\/icons\\/land\\/night\\/tsra_hi,30\\/tsra_hi,40?size=medium\"},\"shortForecast\":{\"0\":\"Mostly Cloudy\",\"1\":\"Mostly Cloudy\",\"2\":\"Mostly Cloudy\",\"3\":\"Chance Showers And Thunderstorms\",\"4\":\"Chance Showers And Thunderstorms then Showers And Thunderstorms Likely\",\"5\":\"Chance Showers And Thunderstorms then Mostly Cloudy\",\"6\":\"Chance Showers And Thunderstorms\",\"7\":\"Showers And Thunderstorms Likely then Chance Showers And Thunderstorms\",\"8\":\"Chance Showers And Thunderstorms\",\"9\":\"Chance Showers And Thunderstorms then Mostly Cloudy\",\"10\":\"Mostly Sunny\",\"11\":\"Partly Cloudy\",\"12\":\"Mostly Sunny then Chance Showers And Thunderstorms\",\"13\":\"Chance Showers And Thunderstorms\"},\"detailedForecast\":{\"0\":\"Mostly cloudy, with a high near 71. South southeast wind around 10 mph.\",\"1\":\"Mostly cloudy, with a low around 59. South southeast wind 5 to 10 mph.\",\"2\":\"Mostly cloudy, with a high near 74. Southeast wind 5 to 10 mph.\",\"3\":\"A chance of showers and thunderstorms after 7pm. Mostly cloudy, with a low around 63. East southeast wind 5 to 10 mph. Chance of precipitation is 50%.\",\"4\":\"A chance of showers and thunderstorms before 7am, then showers and thunderstorms likely between 7am and 1pm, then a chance of showers and thunderstorms. Mostly cloudy, with a high near 76. Southeast wind 5 to 10 mph. Chance of precipitation is 60%. New rainfall amounts less than a tenth of an inch possible.\",\"5\":\"A chance of showers and thunderstorms before 7pm. Mostly cloudy, with a low around 64. Southeast wind 0 to 5 mph. Chance of precipitation is 50%.\",\"6\":\"A chance of showers and thunderstorms between 7am and 1pm, then showers and thunderstorms likely. Mostly cloudy, with a high near 82. South southeast wind 5 to 10 mph. Chance of precipitation is 70%. New rainfall amounts between a tenth and quarter of an inch possible.\",\"7\":\"Showers and thunderstorms likely before 7pm, then a chance of showers and thunderstorms. Mostly cloudy, with a low around 62. Southwest wind around 5 mph. Chance of precipitation is 70%.\",\"8\":\"A chance of showers and thunderstorms. Mostly cloudy, with a high near 76. West northwest wind around 5 mph. Chance of precipitation is 40%.\",\"9\":\"A chance of showers and thunderstorms before 7pm. Mostly cloudy, with a low around 59. West northwest wind 0 to 5 mph. Chance of precipitation is 40%.\",\"10\":\"Mostly sunny, with a high near 79. West northwest wind 0 to 5 mph.\",\"11\":\"Partly cloudy, with a low around 61. Southwest wind 0 to 5 mph.\",\"12\":\"A chance of showers and thunderstorms after 1pm. Mostly sunny, with a high near 81. South southwest wind 0 to 5 mph. Chance of precipitation is 30%.\",\"13\":\"A chance of showers and thunderstorms. Partly cloudy, with a low around 63. South southwest wind around 5 mph. Chance of precipitation is 40%.\"}}",
"encoder": "text",
"name": "daily_forecast",
"version": 1
}
},
"metadata": {
"scrapbook": {
"data": true,
"display": false,
"name": "daily_forecast"
}
},
"output_type": "display_data"
}
],
"source": [
"import scrapbook as sb\n",
"\n",
"sb.glue(\"place\", place)\n",
"sb.glue(\"hourly_forecast\", hourly_forecast.to_json())\n",
"sb.glue(\"daily_forecast\", daily_forecast.to_json())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.1"
},
"sagemaker_run_notebook": {
"saved_parameters": [
{
"name": "place",
"value": "New York, NY"
}
]
}
},
"nbformat": 4,
"nbformat_minor": 4
}