This repository contains analysis of two datasets namely : Financial Dataset-1 and auto_lib_daily_events_postal_code. This datasets are included in the IP week 7 datasets folder together with their column explanation documents.
Financial Inclusion remains one of the main obstacles to economic and human development in Africa. For example, across Kenya, Rwanda, Tanzania, and Uganda only 9.1 million adults (or 13.9% of the adult population) have access to or use a commercial bank account.
Traditionally, access to bank accounts has been regarded as an indicator of financial inclusion. Despite the proliferation of mobile money in Africa and the growth of innovative fintech solutions, banks still play a pivotal role in facilitating access to financial services. Access to bank accounts enables households to save and facilitate payments while also helping businesses build up their credit-worthiness and improve their access to other financial services. Therefore, access to bank accounts is an essential contributor to long-term economic growth.
We have been tasked to understand electric car usag. We will work as a Data Scientist for the Autolib electric car-sharing service company to investigate a claim about the blue cars from the provided Autolib dataset.
In an effort to do this, we need to identify some areas and periods of interest via sampling stating the reason to the choice of method, then perform hypothesis testing with regards to the claim that we will have made. An example of claim to test would be "Is the number of Bluecars taken in area X different than in area Y? Is it greater in area X than in area Z? Etc”. The selected periods of interest be either weekdays or weekends but not a mix of both. You can also consider postal codes 75015 vs 75017 to some of the areas of interest.