doowilliams/TB-Analysis-and-Visualization-in-Nigeria

# TB-Analysis-and-Visualization-in-Nigeria *Description:* Led a comprehensive analysis and visualization project focused on Tuberculosis (TB) indicators in Nigeria from 2015 to 2022. The initiative aimed to provide insights into TB trends, identify patterns, and contribute to informed decision-making in public health. *Role:* Took charge of data preprocessing, analysis, and visualization. Conducted in-depth exploration of TB indicators, created visually compelling representations, and applied advanced statistical methods for predictive modeling. *Tools/Technologies Used:* Python, pandas, matplotlib, seaborn, scikit-learn *Key Achievements:* - Executed meticulous data cleaning and conversion, ensuring accuracy and reliability in subsequent analyses. - Developed a suite of informative visualizations, including dynamic line plots showcasing trends in TB indicators over the years. - Applied linear regression analysis to forecast future values, providing actionable insights for strategic planning. - Contributed valuable perspectives on TB case detection rates, childhood TB notifications, drug-resistant TB notifications, and other pivotal metrics. - Effectively communicated findings through visually appealing graphics and precise numerical results, enhancing the comprehension of TB dynamics in Nigeria. *Impact:* Empowered stakeholders with actionable insights, aiding in evidence-based decision-making for TB control and prevention efforts in Nigeria. ---