Project Summary
COVID-19 is the disease caused by a coronavirus called SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2). It was first discovered on 31st December 2019, following a report of a cluster of cases of so-called viral pneumonia in Wuhan, People’s Republic of China. Since its identification, this virus has impacted the world in all sectors, it’s one of the hardest periods humanbeings have encountered. The most common symptoms of COVID-19 are fever, chills,sore throat etc.It is difficult to know how many people have COVID-19, so we’re going to analyze this dataset in other to gain deeper insight into COVID-19.
Project Overview: Utilized Python to analyze COVID-19 in other to gain in-depth insights into pandemic trends, providing a clear picture of infection rates, mortality, and recovery patterns. By employing various analytical techniques and visualizations, this project contributes to understanding the pandemic’s dynamics and aids in assessing the effectiveness of public health measures.
- DELIVERABLES
- Developed a Python-based dashboard that visualizes COVID-19 case trends across various regions using interactive plots.
- Implemented data cleaning techniques to preprocess raw COVID-19 datasets, ensuring accuracy and consistency in the analysis.
- Conducted exploratory data analysis (EDA) to uncover patterns and anomalies in COVID-19 data using Python’s Pandas and Matplotlib libraries.
- Created time series analyses to examine the impact of various interventions on COVID-19 case dynamics.
- Developed custom Python functions to handle missing or inconsistent data in COVID-19 datasets, improving data reliability for analysis.
- ANALYSIS IMPACT
- The project successfully delivered a suite of tools and insights that will empower stakeholders to make informed decisions regarding public health responses to the COVID-19 pandemic. The interactive dashboard and predictive models facilitated a deeper understanding of pandemic dynamics, while the impact assessments provided critical feedback on the effectiveness of implemented strategies.
