In data science, it's not enough to be able to analyze data. You must also be able to create compelling visualizations to showcase your insights and help people understand your results.
In this introductory course on data visualization in R, you will learn about the different resources you can use to explore and showcase your data visually. Most importantly, you'll learn how to use ggplot2, a powerful and immensely popular data visualization library for R.
By the end of this course, you will be able to create visualizations such as line charts, bar plots, scatter plots, histograms, and box plots to understand your data, and help others understand your data as well.
You will also learn how to add and work with multiple plots in your code to show different visualizations in a single dashboard.
At the end of the course, we’ll wrap up with a guided data science project. You will be able to combine all your new R data viz skills to create data visualizations that dig into real-world data about forest fires in Portugal to answer some interesting questions.
By the end of this course, you'll be able to:
Learn Data Visualization in R
Creating Line Graphs
Learn the basics of ggplot2 as you visualize change in life expectancy over time.
Creating Multiple Line Graphs
Learn techniques for visualizing variables using ggplot2.
Bar Charts, Histograms, and Box Plots
Learn to visualize data distributions as you analyze movie reviews.
Scatter Plots for Exploratory Analysis
Learn to create and interpret scatter plots to explore relationships between variables.
Analyzing Forest Fire Data
Use data visualization techniques to explore data on forest fire occurrences.
