PatTheAtak/East-Africa-Financial-Inclusion

# East-Africa-Financial-Inclusion #### Financial Inclusion in East Africa Dataset Analysis, 3/5/2020 #### By **M A P** ## Description This is a detailed description and analysis of the Financial Inclusion dataset. The analysis is meant to answer a number of questions as well as be used to make recommendations. **Research Question** 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. * Define the question, the metric for success, the context, experimental design taken and the appropriateness of the available data to answer the given question * Find and deal with outliers, anomalies, and missing data within the dataset. * Perform univariate, bivariate and multivariate analysis recording your observations. * Implement the solution by performing the respective analysis i.e. factor analysis, principal component analysis, and discriminant analysis. * Challenge your solution by providing insights on how you can make improvements. ## Setup/Installation Requirements * Install Python * Install NumPy and Pandas libraries for exploration and analysis. * Install Scikit-Learn for Machine Learning. * Install Matplotlib and Seaborn for Data Visualization. * Install Anaconda and use Jupyter Notebook. ## Technologies Used * Python * Pandas * Numpy * Matplotlib * Seaborn * Scikit-Learn ### License **MIT (c) 2020 M A P**