Analyzing the Impact of COVID-19 on the Global Economy

Project Overview

This project explores the multifaceted impact of the COVID-19 pandemic on global economic and social aspects using data analysis and visualization. The focus is on uncovering trends, identifying critical patterns, and drawing insights from key datasets.

Datasets Used

Website -: www.Kaggle.com

Impact of COVID-19 on the Global Economy- : https://www.kaggle.com/datasets/shashwatwork/impact-of-covid19-pandemic-on-the-global-economy

Key Analyses and Insights

1. Global Trends in COVID-19 Cases and Deaths

• Charts Created:
  • Line charts showing cumulative cases and deaths globally.
  • Heatmaps illustrating the distribution of cases and deaths by region.
• Insights:
  • The pandemic exhibited distinct waves, with varying intensity across regions.
  • Certain countries with robust healthcare systems experienced relatively lower mortality rates.

2. Economic Impact

• Charts Created:
  • Bar charts comparing GDP contraction and recovery trends across continents.
  • Scatter plots examining the relationship between unemployment rates and lockdown stringency.
• Insights:
  • Developing economies faced sharper GDP declines but displayed quicker recoveries compared to advanced economies.
  • Countries with strong social safety nets saw less pronounced spikes in unemployment.

3. Vaccination and Recovery

• Charts Created:
  • Bubble plots showing vaccination rates vs. GDP recovery.
  • Choropleth maps highlighting global vaccination progress.
• Insights:
  • Higher vaccination rates correlated with faster economic recovery.
  • Regions with delayed vaccine rollouts experienced prolonged economic stagnation.

4. Social and Mobility Changes

• Charts Created:
  • Line graphs displaying changes in workplace and residential mobility trends.
  • Area charts visualizing retail and recreation activities over time.
• Insights:
  • Lockdowns led to an increase in residential mobility, reflecting remote work adoption.
  • Retail and recreation activities showed slow recovery, signaling lingering caution among consumers.

Tools and Techniques

The analysis employed the following tools and libraries:

• Data Cleaning: Pandas for data preprocessing and handling missing values.
• Visualization: Matplotlib, Seaborn, and Plotly for dynamic and static visualizations.
• Geospatial Analysis: Folium for mapping regional data trends.
• Statistical Insights: Correlation and regression analysis to quantify relationships between variables.

Key Findings

• Vaccination rates and economic recovery exhibit a strong positive correlation.
• Stringent lockdowns, while effective in controlling virus spread, imposed significant economic costs.
• Mobility trends reflected the shifts in societal behavior, with lasting impacts on workplace and retail environments.

Future Work

Further analysis could focus on:

1. Exploring the long-term effects of the pandemic on global trade and supply chains.
2. Examining disparities in recovery across socioeconomic groups within countries.
3. Predicting the trajectory of future pandemics using machine learning models.