python-api-challenge

Scenario: Prove that places closer to the equator are hotter, and locate a few places with the perfect weather for a vacation. Use OpenWeatherMap API, jupyter-gmaps and the Google Places API.

Part I - WeatherPy Create a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator and plot the relationship of various weather measurements across latitudes.

Part II - VacationPy Create a heatmap of humidities for the cities from part 1. Then, narrow down the list of cities to the places with ideal weather for a vacation. Find a hotel in each city and plot it with a marker on top of the heatmap.

In this repo

• output_data folder

  • cities.csv: city weather generated in Part I.
  • Cloudiness.png: Cloudiness vs. Latitude graph from Part I
  • heatmap.png from Part II
  • heatmap_with_hotels.png from Part II
  • humidity.png: Humidity vs. Latitude graph from Part I
  • max_temp.png: Maximum Temperature vs. Latitude graph from Part I
  • north_cloudiness.png: Cloudiness vs. Latitude, Northern Hemisphere graph from Part I
  • north_humidity.png: Humidity vs. Latitude, Northern Hemisphere graph from Part I
  • north_max_temp.png: Maximum Temperature, Northern Hemisphere vs. Latitude graph from Part I
  • north_wind_speed.png: Wind Speed vs. Latitude, Northern Hemisphere graph from Part I
  • south_cloudiness.png: Cloudiness vs. Latitude, Southern Hemisphere graph from Part I
  • south_humidity.png: Humidity vs. Latitude, Southern Hemisphere graph from Part I
  • south_max_temp.png: Maximum Temperature, Southern Hemisphere vs. Latitude graph from Part I
  • south_wind_speed.png: Wind Speed vs. Latitude, Southern Hemisphere graph from Part I
  • wind_speed.png: Wind Speed vs. Latitude graph from Part I

• VacationPy folder

  • VacationPy.ipynb: code for Part II

• WeatherPy folder

  • WeatherPy.ipynb: code and observations for Part I