Investigating COVID-19 Virus Trends
- Guided Project
- 1 hours
- Beginner
- R
Practice data manipulation and aggregation in R to analyze real COVID-19 data and find countries with highest positive test rates.
Overview
In this project, you'll take on the role of a data analyst exploring the global COVID-19 pandemic. You'll work with a real-world dataset, applying your R programming skills and leveraging powerful libraries like dplyr to manipulate, filter and aggregate the data.
Through techniques like grouping and summarizing, you'll identify which countries have the highest rates of positive COVID-19 tests relative to their testing. In the process, you'll strengthen your R coding and analytical thinking skills, building capabilities that are highly valued in data science roles.
Objective: Analyze a real COVID-19 dataset using R data wrangling techniques to uncover insights about testing and positive rates across countries, developing in-demand data analysis skills for your career.
What You'll Learn
- ✓ Expand your portfolio with a data structures project
- ✓ Overcome common challenges in data analysis
Before You Start
- ✓ Creating and working with vectors, matrices, and lists in R
- ✓ Indexing data structures to extract elements for analysis
- ✓ Applying functions to data structures to perform calculations
- ✓ Manipulating and analyzing data using dataframes
Project Steps
9 steps
- 1 Guided Project Introduction
- 2 Understanding the Data
- 3 Isolating the Rows We Need
- 4 Isolating the Columns We Need
- 5 Extracting the Top Ten Countries with Most Covid-19 Cases
- 6 Identifying the Highest Positive Against Tested Cases
- 7 Keeping relevant information
- 8 Putting all together
- 9 Next steps
Join 1M+ data learners on Dataquest.
- 1
Create a free account
- 2
Choose a learning path
- 3
Complete exercises and projects
- 4
Advance your career