Analysis of the causes of death in ten countries using Python and Tableau as part of CareerFoundry Data Analytics course.
The goal of the project is to help pharmaceutical manufacturers to monitor the most frequent causes of death so they can better serve the needs of healthcare. The clients want to know what illnesses are at the top of the causes of deaths and what markets in terms of countries need more attention in connection with it.
The original data sets are the following:
Programming language: Python
Python libraries: Pandas, seaborn, NumPy, os, matplotlib, seaborn, statsmodels, warnings,sklearn, Kmeans, pylab, StandardScaller, PCA, plotly.express, train_test_split, LinearRegression, mean_squared_error, r2_score, folium, json
Software distribution: Anaconda
Environment: Jupyter Notebook