Composing Via Numbers

I have been thinking about personal projects to undertake to learn more about Jupyter Notebooks, Numpy, Pandas, etc.  I have decided to start looking at Bike data from Ford GoBike.  I got interested in this project based on a Berkeley online class on Python.  It used Bike sharing data from the San Francisco area.  I eventually found data on Ford GoBike by doing a similar search. Here is the Ford GoBike website:  I am still working on the analysis.  I will not show all code to this project for three reasons.   The first is that this is a learning project so not all the code and visual styles are mine.  When needed I search the internet for code, best practices and references. So I can not claim that all of this is my work. For me, the first goal is to learn to use Juypter Notebooks better by working on a project. In order to learn, I need to learn from other. That being said,  I have encountered many problems during the way...

My colleagues and I run a Tableau training session for executives. During our introduction to Tableau part, we generally like to work with world data. One of the exercises we do tests the participant's knowledge of global  facts.  This is related to Hans Rosling's book "Factfulness". One question, we ask the participants is whether the world should be classified as 1st world, 2nd world, and 3rd world.  We explore this Tableau visual using data from Gapminder during this activity. The video below shows life expectancy and fertility rates for each country from 1950-2018. Most executives have never used Tableau before so the visual really surprises them. It is best to view the video using "full screen".