Jasminewakini/WK2-IP-FINANCIAL_INCLUSIONS

This is my Python Notebook where I analysis the state of financial inclusion in East African (Kenya, Rwanda, Tanzania, and Uganda) while providing insights into some of the key demographic factors that might drive individuals’ financial outcomes. # WK2CORE-IP-FINANCIAL_INCLUSIONS The research problem is to figure out how we can predict which individuals are most likely to have or use a bank account. # Moringa_Data_Science_Core_W2_Jasmine_Wakini_2021_12_Python_Notebook.ipynb #### {Python Programmming Data Science Project}, {December, 2021} #### By **{Jasmine Wakini}** ## Description 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. The research problem is to figure out how we can predict which individuals are most likely to have or use a bank account. Your solution will help provide an indication of the state of financial inclusion in Kenya, Rwanda, Tanzania, and Uganda, while providing insights into some of the key demographic factors that might drive individuals’ financial outcomes. ## Setup/Installation Requirements * Google Colab/Jupyter Notebook. * Pandas and Numpy Python libraries for data exploration and manipulation * Data cleaning tools * Exploratory data analysis techniques. ## Known Bugs {There are no known bugs. Improvements are encouraged.} ## Technologies Used {Python Programming, Libraries: Numpy, Pandas, matplotlib, seaborn} ## Support and contact details { To make a contribution to the code or any part of the project, …