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# Hints and Considerations * You may want to start this assignment by refreshing yourself on the (). * See (WeatherPy_Example.pdf) for a reference on expected format. * You must use proper labeling of your plots, including aspects like: Plot Titles (with date of analysis) and Axes Labels. * You must include a written description of three observable trends based on the data. * You must use the Matplotlib or Pandas plotting libraries. As final considerations: * You must complete your analysis using a Jupyter notebook. * Save both a CSV of all data retrieved and png images for each scatter plot. * Include a print log of each city as it's being processed with the city number and city name.
Cost distance toolset arcgis 10.3 series#
* Perform a weather check on each of the cities using a series of successive API calls. Latitude Your final notebook must: * Randomly select **at least** 500 unique (non-repeat) cities based on latitude and longitude. Your objective is to build a series of scatter plots to showcase the following relationships: * Temperature (F) vs. To accomplish this, you'll be utilizing a (), the (), and a little common sense to create a representative model of weather across world cities. GitHub - DDiaz07/WeatherPy_homework: # WeatherPy In this example, you'll be creating a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator.