COVID-19 Data Analysis with Python

# Introduction

In this project, you will learn how to analyze COVID-19 data using Python. The COVID-19 pandemic has had a significant impact on the world, and understanding the data is crucial for tracking the spread of the virus and making informed decisions.

## 👀 Preview

{
  "Confirmed": {
    "Africa": 1203094,
    "America": 6396173,
    "Asia": 6480321,
    "Europe": 3450299,
    "Oceania": 27346,
    "Others": 721,
    "Total": 17557954
  },
  "Deaths": {
    "Africa": 28289,
    "America": 254610,
    "Asia": 133186,
    "Europe": 206438,
    "Oceania": 576,
    "Others": 15,
    "Total": 623114
  },
  "Recovered": {
    "Africa": 930536,
    "America": 5087347,
    "Asia": 5163062,
    "Europe": 1927545,
    "Oceania": 21892,
    "Others": 651,
    "Total": 13131033
  },
  "Active": {
    "Africa": 244269,
    "America": 1054216,
    "Asia": 1184073,
    "Europe": 1316316,
    "Oceania": 4878,
    "Others": 55,
    "Total": 3803807
  }
}

## 🎯 Tasks

In this project, you will learn:

- How to set up the development environment and install the required Python libraries
- How to understand the structure and content of the COVID-19 data
- How to implement a function to convert country names to continent names
- How to process the COVID-19 data and calculate the summary statistics for each continent
- How to test the code and verify the output

## 🏆 Achievements

After completing this project, you will be able to:

- Understand how to work with CSV data in Python
- Implement functions to process and analyze data
- Convert data between different formats (e.g., CSV to JSON)
- Gain experience in data analysis and visualization
- Contribute to the understanding of the COVID-19 pandemic through data-driven insights