Robertfnicholson/World_Weather_Analysis

I used Python, Jupyter Notebook and the city PI module to get the cities for more than 700 random latitudes and longitudes then I requested on the open weather map API and retrieve the JSON weather data from these cities. I then added the weather data to the Panda’s dataframe. From there I used Matplotlib to create a series of scatter plots to show the relationship between the latitude and a variety of weather parameters . Completed a series of statistical calculations on the data using linear regression on the weather parameters. This data helped my team predict the best time of the year for people to plan their vacation. Finally, I exported the data, cleaned it and used the weather data to choose the best cities for a vacation based on certain weather criteria and then mapped these cities using Jupyter G Maps and the Google Places API.

Jupyter Notebook