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Weather data trend analysis and visualization of weather across 500 unique world cities using Python library - CitiPy, MatplotLib, and OpenWeatherMap API to build a series of scatter plots to illustrate the relationships between Temperature vs. Latitude, Humidity vs. Latitude, Cloudiness vs. Latitude, and Wind Speed vs. Latitude.

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Python_API_Challenge

OpenWeatherMap API Data Analysis

Objective - Provide visualization and analysis for the weather of 500+ cities across the world of varying distance from the equator by utilizing the OpenWeatherMap API.

  • Perform a weather check on each of the cities using a series of successive API calls
  • Include a print log of each city as it processes with city number and name printed.
  • Save both a csv file and png images for each scatter plot.

Objectives for Scatter Plots Visualizations:

  1. Temperature (F) vs. Latitude
  2. Humidity (%) vs. Latitude
  3. Cloudiness (%) vs. Latitude
  4. Wind Speed (mph) vs. Latitude

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Weather data trend analysis and visualization of weather across 500 unique world cities using Python library - CitiPy, MatplotLib, and OpenWeatherMap API to build a series of scatter plots to illustrate the relationships between Temperature vs. Latitude, Humidity vs. Latitude, Cloudiness vs. Latitude, and Wind Speed vs. Latitude.

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