Here we’ll be looking at a python library matplotlib which is used for plotting data in various ways. We’ll be detailing things such as iterating subplots, different grid specs, and complex labeling. We will not be covering all of the different types of plots that can be done, those can be found in the documentation here.
Here we’ll be talking about how to use the super method, function decorators, and combining the two. We’ll start off with the super method, and some use cases.
Here we showcase different ways of creating a map with folium, and different attributes of markers and circles. There are many ways to build a map, so don't be afraid to dig into documentation or message me on Linkedin if you need something specific.
Here I will go over multiple methods of using css and html to style and prettify your jupyter notebook like my photo below. For use in any html/css scenario I will be going over:
The teacher supplies a project, and the students complete the project. What if that data involves web scraping? Well I had the grand idea of getting the entire class in on scraping the budgets and grosses of 700,000 movies to match the 1-2 million movie datasets i downloaded from IMDB. So I went on my merry way and split the IMDB indexes I had into 10 parts, each with the name of a person.