catherinesloan/python-api-challenge

python-api-challenge

PART I - WeatherPy

Task:

To utilise a Python library and the OpenWeatherMap API to create a representative model of weather across world cities.

Output:

A Python script that visualises the weather of 500+ cities across the world of varying distance from the equator.

1. A random selection of 500+ unique cities based on latitude and longitude
2. A weather check on each of the cities using a series of successive API calls
3. A print log of each city as it's being processed with the city number and city name
4. A CSV export of all retrieved data
5. A series of scatter plots that showcases the following relationships:
   • Temperature (F) vs. Latitude
   • Humidity (%) vs. Latitude
   • Cloudiness (%) vs. Latitude
   • Wind Speed (mph) vs. Latitude
6. Linear regression on each relationship, seperated into Northern Hemisphere and Southern Hemisphere:
   • Temperature (F) vs. Latitude
   • Humidity (%) vs. Latitude
   • Cloudiness (%) vs. Latitude
   • Wind Speed (mph) vs. Latitude
7. PNG image export for each plot

.

PART II - VacationPy

Task:

Use jupyter-gmaps and the Google Places API to create a heat map that displays the humidity for every city from part I.

Output:

A Python script which narrows down the DataFrame from part I to find my ideal weather conditions of

• Temperature 23 to 28 degrees celcius
• Wind speed < 10 mph
• Cloudiness < 1%

1. Google Places API to find the first hotel for each city located within 5000 meters of locations with my ideal weather conditions.
2. A humidity heatmap with plots of each of the hotels, including a pin containing;
   • Hotel Name
   • City
   • Country