Graphics in R: Data Visualization and Data Analysis with R

Graphics in R: Data Visualization and Data Analysis with R

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Advance your data visualization skills using r packages. Master ggplot2, lattice, interactive plots with ggvis package

Updated on Sep, 2026

Programming, Data Science, Data Analysis

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Learn data visualizations by projects that use real-world datasets in professional industries such as finance, marketing, sales etc.

This course will help you master data visualization techniques and create graphics in R using packages such as ggplot2, lattice package and ggvis package from shiny for adding interactivity to your R graphics.

Real-world datasets are used for projects. So, not only will you master the graphics in R, but you will also be able to interpret your graphics and make an impressive plot. All done by yourself.

Data Visualization helps people see, interact with, and better understand the data. Whether simple or complex, the right visualization can bring everyone on the same page, regardless of their level of expertise.

Almost all professional industries benefit from making data more understandable. Every STEM field benefits from data analysts who are able to understand data—and so do fields in government, finance, marketing, history, consumer goods, service industries, education, sports, and so on.

As the “age of Big Data” and "Artificial Intelligence (AI)" kicks into high gear, visualization is an increasingly key tool to make sense of the trillions of rows of data generated every day. Data visualization helps to tell stories by curating data into a form easier to understand, highlighting the trends and outliers. A good visualization tells a story, removing the noise from data and highlighting useful information.

With R tools such as ggplot2, and lattice package, we can create visually appealing graphics and data visualizations by writing a few lines of code . For this purpose, R is widely used and it is easy to use and understand when it comes to data visualizations, good appealing graphics, data analysis (dplyr) etc. Through R, we can easily customize our data visualization by changing axes, fonts, legends, annotations, and labels.

After completing the course you will receive the electronic certificate that you can add to your resume or CV and LinkedIn profile from Tutorialspoint.

The access to this course is also lifetime, hence you will learn at your own pace. The course is also updated regularly to ensure it meets all the student's demands and students enrolled are learning the latest version of r and R Studio.

Graphics in R: Beginner Level

Graphic Devices & Colors

Data Visualization in R: Beginner Level

Barplots & Pie Charts

Box and Whisker Plots

Intermediate Data Visualization & Graphics in R

Data Visualization with Lattice Package

High-Level Functions in lattice package

Lattice Package panel functions

Going further with data visualization

How to Handle and switch between graphics

Controlling layout with layout function

ggplot2 scales and guides:

scale_x_continous, scale_y_continous, scale_color_manual,scale_fill_manual

scale_shape_manual,scale_shape_manual,scale_alpha_continous

guide_legend, gudei_colorbar

ggplot2 faceting: facet_wrap() vs facet_grid()

scatterplot with layers, interactive plots with input_slider(), add_legend(), add_axis etc

I am certain with all the material covered in this course you will be able to advance your Data visualization and Data Analysis skills!

See you in the first lecture!

In this data visualization course you will learn the following:

After Mastering R Programming for beginners and Data Analysis, you will begin creating graphics with r and visualizations.

Check out the detailed breakdown of what’s inside the course

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