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PythonAPI

This project has two parts: In the first portion, I created a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator, utilizing a simple Python library, the OpenWeatherMap API, and a little common sense to create a representative model of weather across world cities. The first requirement was to create a series of scatter plots to showcase the following relationships:

  • Temperature (F) vs. Latitude
  • Humidity (%) vs. Latitude
  • Cloudiness (%) vs. Latitude
  • Wind Speed (mph) vs. Latitude image

The second requirement is to run linear regression on each relationship. This time, separate the plots into Northern Hemisphere (greater than or equal to 0 degrees latitude) and - - Southern Hemisphere (less than 0 degrees latitude):

  • Northern Hemisphere - Temperature (F) vs. Latitude
  • Southern Hemisphere - Temperature (F) vs. Latitude
  • Northern Hemisphere - Humidity (%) vs. Latitude
  • Southern Hemisphere - Humidity (%) vs. Latitude
  • Northern Hemisphere - Cloudiness (%) vs. Latitude
  • Southern Hemisphere - Cloudiness (%) vs. Latitude
  • Northern Hemisphere - Wind Speed (mph) vs. Latitude
  • Southern Hemisphere - Wind Speed (mph) vs. Latitude In the final notebook, I:
  • Randomly selected at least 500 unique (non-repeat) cities based on latitude and longitude.
  • Performed a weather check on each of the cities using a series of successive API calls.
  • Included a print log of each city as it's being processed with the city number and city name.
  • Saved a CSV of all retrieved data and a PNG image for each scatter plot. image

In the second part of the assignment, I

  • Create a heat map that displays the humidity for every city from Part I.
  • Narrow down the DataFrame to find your ideal weather condition. For example:
  • A max temperature lower than 80 degrees but higher than 70.
  • Wind speed less than 10 mph.
  • Zero cloudiness.
  • Drop any rows that don't contain all three conditions. You want to be sure the weather is ideal.
  • Using Google Places API to find the first hotel for each city located within 5000 meters of your coordinates.
  • Plot the hotels on top of the humidity heatmap with each pin containing the Hotel Name, City, and Country.