This weekend while I was browsing through github for inspirational packages written in R to improve my data analysis workflow, I came across ggforce which is now my newest addition to my data science toolbox, and here’s why.

In this Article we explore the trends of debt and major events in Burundi, Kenya, Rwanda, Tanzania, and Uganda.

Within this case study, We are going to dive into wearable-tech health data. We are to derive key insights from our data and perform Customer Segmentation. Hence, grouping the customers with respect to their user data behavior for 🎯 targeted marketing strategies

Our goal will be to define relevant groups or clusters of Bustabit users to identify what patterns and behaviors of gambling persist. Can we describe a particular group as risk-averse? Is there a set of gamblers that have a strategy that seems to be more successful in the long term?

This a Guided Project hosted by DataCamp to analyse and visualize the the trends in spread and significant events during the COVID outbreak