The-Vheed/African-Tuberculosis-Data-Analysis

his repository contains an Exploratory Data Analysis (EDA) of African Tuberculosis (TB) data, focusing on key insights related to disease prevalence, mortality, and incidence rates across various African countries. The analysis is built around a series of investigative questions, leveraging the tb-burden-country.csv dataset. # African Tuberculosis Data Analysis: Exploratory Data Analysis (EDA) This repository contains an Exploratory Data Analysis (EDA) of African Tuberculosis (TB) data, focusing on key insights related to disease prevalence, mortality, and incidence rates across various African countries. The analysis is built around a series of investigative questions, leveraging the `tb-burden-country.csv` dataset. ### Exercise Objectives: The EDA addresses the following core questions: * **Prevalence Analysis:** Identification of African countries with the highest and lowest TB prevalence based on the most recent available data. * **Mortality Trends in South Africa:** Quantification of the total number of TB-related deaths annually in South Africa. * **Incidence Rate Comparison:** Determination of the country with the highest TB incidence rate for each year, specifically among countries where the method for deriving incidence estimates is provided. * **HIV-Positive TB Cases in Kenya:** Visualization of the incidence rate of HIV-positive TB cases over time in Kenya, presented as a bar plot with error bars. The analysis utilizes a pandas DataFrame for data loading and manipulation, and a data visualization library (Matplotlib) for graphical representation of findings.