What you would learn in Mastering Data Visualization with R and ggplot2 - 2022 course?
R is an open-source, well-developed, and simple programming language ideal for statistical computing, statistical analysis, and more.
Visualization of data in R allows you to create charts, maps, and 3D graphs with the aid of RGL and better understand the order of events. R is a fantastic platform for the analysis of facts that is capable of creating nearly every kind of graph. R is a language that provides an environment for statistical computing and graphics. It is also highly flexible and easy to work with for growing visualizations.
One of the strengths of R is the ability to create appealing plots that require minimal programming. Data visualization is turning data into useful information. R Programming allows you to analyze this art form by providing integrated features and libraries to create visualizations and display information. R can be used to assist with four distinct pix platforms: base graphics grid graphics, lattice graphics, and ggplot2. Base pictures is the default pix machine used in R, which is the simplest among the four systems to work with and offers numerous valuable tools designed explicitly for exploratory snapshots in which we want to investigate what's in the data of a new dataset.
Copy your text here and click "Next" to watch this article rewriter perform the thing. There are numerous R classes and lectures available on the internet. But, R has a steep learning curve, and college students are often overwhelmed. It's a different path!
The path we follow is step-by-step. Every time we make a course, we expand upon the lessons we have already learned and move one step ahead.
Following each video, you look up a new idea that you can apply immediately. The best part is to research through examples.
This course is filled with real-world analytical issues that you'll investigate to resolve. A few of them we'll solve together, while others you will complete as homework.
You'll be able to learn subjects like;
The concept that lies behind statistics plots the basis of the ggplot2
Data transformation using tidyr and dplyr
Exploratory Data Analysis (EDA)
EDA to study the effects of two variables within various statistical plots
Combine ggplot2 and RMarkdown to finish your analysis, and generate HTML-based reports
Create other plots by mixing ggplot2 with additional libraries such as word cloud parallel coordinates plot radar plot, heat map, etc.
Modify your plot's themes
Create subplots with cowplot library
Highlight information on your plots using the GHighlight library
Content of the Course:
Data visualization is a fundamental aspect of the foundations
Utilize ggplot2 to create numerous standard statistical plots
Learn how to code with R at a decent level
Learn how to modify R studio to meet your needs
Learn how you can customize R studio to meet your personal preferences
Transform data before visualization being applied
Learn to create Visualisations and Graphs with the accurate DATA
Learn about essential data pre-processing and Wrangling in R Studio
Read-In Data In The R Environment from a variety of sources
Learning to visualize Real Data and process it
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