README.md

Python-API

"What is the weather like as we approach the equator?"

Background

Taking what has been learned about Python requests, APIs and JSON traversals to answer the fundamental question of "What is the weather like as we approach the equator?"

Part 1: WeatherPy

Create a Python script to visualize the weather of over 500 cities of varying distances from the equator.

• Requirement 1: Create plots to showcase the relationship between weather variables and latitude

  • A series of scatter plots were created to showcase the following:
    • Latitude vs. Temperature
    • Latitude vs. Humidity
    • Latitude vs. Cloudiness
    • Latitude vs. Wind Speed

• Requirement 2: Compute linear regression for each relationship and separate into Northern Hemisphere and Southern Hemisphere

  • A series of scatter plots were created for both the Northern and Southern Hemispheres to showcase the following for each:

    • Latitude vs. Temperature
    • Latitude vs. Humidity
    • Latitude vs. Cloudiness
    • Latitude vs. Wind Speed

  • A description of relationships that were unconvered for each plot is provided.

Part 2: VacationPy

Use weather data skills to plan future vacations and create map visualizations. The following will be incorporated in the code: * Create a map that displays a point for every city in the DataFrame, where the size of the point should be the humidity in each city. * Narrow the DataFrame to find the ideal weather condition. * Create a new DataFrame called hotel_df to store the city, country, coordinates and humidty. * For each city, use the Geoapify API to find the first hotel located within 10,000 meters of your coordinates. * Add the hotel name and the country as additional information in the hover message for each city.

References

• Dataset provided by edX UofT Data Analytics, which had been generated by Trilogy Education Services, LLC.

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