https://github.com/trainingbypackt/applied-data-visualization-with-r-and-ggplot2-elearning

Develop informative and aesthetic visualizations that enable effective data analysis in less time
https://github.com/trainingbypackt/applied-data-visualization-with-r-and-ggplot2-elearning

ggplot2 qplot r rstudio

Last synced: 9 months ago
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Develop informative and aesthetic visualizations that enable effective data analysis in less time

• Host: GitHub
• URL: https://github.com/trainingbypackt/applied-data-visualization-with-r-and-ggplot2-elearning
• Owner: TrainingByPackt
• License: mit
• Created: 2019-01-17T11:33:23.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2019-01-24T05:00:39.000Z (over 7 years ago)
• Last Synced: 2025-07-14T03:05:21.122Z (11 months ago)
• Topics: ggplot2, qplot, r, rstudio
• Language: R
• Homepage:
• Size: 22.5 KB
• Stars: 2
• Watchers: 2
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# Applied Data Visualization with R and ggplot2

When data is presented to you in a graphical or pictorial format, you can analyze it more effectively. This course begins by introducing you to basic concepts, such as grammar of graphics and geometric objects. It then goes on to explain these concepts in detail with examples. Once you are comfortable with basics, you can learn all about the advanced plotting techniques, such as box plots and density plots. With this course, you can transform data into the useful material and make data analysis interesting and fun.

## What you will learn

* Set up the R environment, RStudio, and understand the structure of ggplot2

* Distinguish variables and use best practices to visualize them

* Change visualization defaults to reveal more information about data

* Implement the grammar of graphics in ggplot2 such as scales and faceting

* Build complex and aesthetic visualizations with ggplot2 analysis methods

* Logically and systematically explore complex relationships

* Compare variables in a single visual, with advanced plotting methods

### Hardware requirements

For an optimal experience, we recommend the following hardware configuration:

* **Processor**: Intel Core i5 or equivalent

* **Memory**: 4GB RAM

* **Storage**: 35 GB available space

### Software requirements

* **OS**: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit

* **Browser**: Google Chrome, Latest Version