In this course, you'll embark on a journey to master data visualization using R, one of the most popular programming languages among data scientists. Starting with the basics, you'll learn how to set up R and RStudio, ensuring your environment is ready for data analysis. You'll then acquire data from the US National Weather Service, focusing on real-world data to make the learning process relevant and engaging. The initial module walks you through inspecting the data to understand its structure and nuances.
Next, you will dive into writing R code to read and manipulate data. You'll explore various data types and values within R, building a solid foundation in handling complex datasets. The course then moves on to practical applications, teaching you how to plot data and create scatter plots. You'll learn to apply linear regression models to identify trends within the data, enhancing your analytical skills. Through hands-on lessons, you'll generate multiple graphs efficiently using loops and display them comprehensively for better comparison.
In the final module, you'll learn to install and use essential R packages like ggplot2, which significantly simplifies the process of creating advanced visualizations. You'll culminate the course by plotting critical temperature data, highlighting significant trends. By the end of this course, you will have a robust understanding of data visualization in R, equipped with the skills to handle and visualize complex datasets effectively.
This course is designed for technical professionals, data enthusiasts, and analysts who are looking to enhance their data visualization skills using R. A basic understanding of programming and data concepts is recommended to fully benefit from this course.
Overview
Syllabus
- Get Set Up
- In this module, we will introduce the course and its objectives, ensuring you understand what to expect. We will guide you through installing R and RStudio, obtaining relevant data from the US National Weather Service, and inspecting the data to comprehend its structure and content.
- Write the Code
- In this module, we will delve into coding practices essential for data analysis in R. You'll start by reading data into R and understanding the different data types. We'll cover creating visual data representations, building and assessing linear regression models, and automating plot generation using loops. Finally, you'll learn to display multiple graphs together for comprehensive data comparison.
- Install and Use an R Package
- In this module, we will explore the installation and use of R packages, specifically focusing on the ggplot2 package for data visualization. You will learn to leverage pre-written functions to simplify your coding process and create sophisticated plots. By the end of this section, you will be able to plot and highlight specific data points, such as minimum and maximum temperatures, customize the aesthetics of your plots, and analyze data trends through enhanced graphical representations.
- Wrap Up
- In this module, we will wrap up the course, summarizing the key concepts and skills you have acquired. We will reflect on how you can apply what you've learned in R and RStudio to real-world data analysis projects. Additionally, we will discuss potential next steps for further learning and skill enhancement in data science and programming with R. Lastly, we will provide resources and guidance for continued practice and exploration to further solidify your understanding and expertise.
Taught by
Packt - Course Instructors
