Installing ggplot2 R graphics
The ggplot2 package can be easily installed using the R function install.packages().
You need to type the following R code in the console:
install.packages("ggplot2")The above code will automatically download the ggplot2 package, from the CRAN (Comprehensive R Archive Network) repository, and install it.
Using ggplot2
After installing the package, you can load it using the R function library().
# Load ggplot2
library("ggplot2")
# Create a scatter plot
ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
geom_point(aes(color = Species)) +
scale_color_viridis_d() +
theme_minimal()
Recommended for you
This section contains best data science and self-development resources to help you on your path.
Coursera – Online Courses and Specialization
Data science
- Course: Machine Learning: Master the Fundamentals by Stanford
- Specialization: Data Science by Johns Hopkins University
- Specialization: Python for Everybody by University of Michigan
- Courses: Build Skills for a Top Job in any Industry by Coursera
- Specialization: Master Machine Learning Fundamentals by University of Washington
- Specialization: Statistics with RÂ by Duke University
- Specialization: Software Development in RÂ by Johns Hopkins University
- Specialization: Genomic Data Science by Johns Hopkins University
Popular Courses Launched in 2020
- Google IT Automation with Python by Google
- AI for Medicine by deeplearning.ai
- Epidemiology in Public Health Practice by Johns Hopkins University
- AWS Fundamentals by Amazon Web Services
Trending Courses
- The Science of Well-Being by Yale University
- Google IT Support Professional by Google
- Python for Everybody by University of Michigan
- IBM Data Science Professional Certificate by IBM
- Business Foundations by University of Pennsylvania
- Introduction to Psychology by Yale University
- Excel Skills for Business by Macquarie University
- Psychological First Aid by Johns Hopkins University
- Graphic Design by Cal Arts
Amazon FBA
Amazing Selling Machine
Books – Data Science
Our Books
- Practical Guide to Cluster Analysis in RÂ by A. Kassambara (Datanovia)
- Practical Guide To Principal Component Methods in RÂ by A. Kassambara (Datanovia)
- Machine Learning Essentials: Practical Guide in RÂ by A. Kassambara (Datanovia)
- R Graphics Essentials for Great Data Visualization by A. Kassambara (Datanovia)
- GGPlot2 Essentials for Great Data Visualization in RÂ by A. Kassambara (Datanovia)
- Network Analysis and Visualization in RÂ by A. Kassambara (Datanovia)
- Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia)
- Inter-Rater Reliability Essentials: Practical Guide in RÂ by A. Kassambara (Datanovia)
Others
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham & Garrett Grolemund
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien Géron
- Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce & Andrew Bruce
- Hands-On Programming with R: Write Your Own Functions And Simulations by Garrett Grolemund & Hadley Wickham
- An Introduction to Statistical Learning: with Applications in RÂ by Gareth James et al.
- Deep Learning with R by François Chollet & J.J. Allaire
- Deep Learning with Python by François Chollet
Author: Editor
Views: 4
No responses yet