Published 07/2022
Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.5 GB | Duration: 15 lectures • 8h 20m
Data Visualization using R Programming Language. GGplot2, Data Analysis, Data Preparation, Data Sciene Tools, RStudio
What you’ll learn
Foundations of data visualization
Use ggplot2 for creating many different standard statistical plots
Learn to program in R at a good level
Learn how to customize R studio to suit your preferences
Learn how to customize R studio to suit your preferences
Transform data before visualization is applied
Learn how to build Visualisations and Graphs from REAL DATA
Learn basic Data Pre-processing & Wrangling In R Studio
Read In Data Into The R Environment From Different Sources
Learning to Visualize Real Data and Process it
Requirements
No prior knowledge or experience required
Interest in data science and data visualization.
Description
R is an open-source, well-developed, and easy programming language for statistical computing, statistics analysis, etc.
R has inbuilt visualization libraries that assist to existing & visualize information in a brief manner with the assistance of ggplot2, lattice, excessive charter, leaflets, etc. ggplot2 makes it less complicated to build customized plots & helps in producing multi-layered graphics. Lattice help in visualizing multi-varied statistics while excessive charters is a visualisation library in JavaScript.
Data visualisation in R helps to build maps, and 3D plots with the help of RGL and to understand the sequence of events. R is a wonderful platform for facts analysis, successful in creating almost any kind of graph. R is a language and surroundings for statistical computing and graphics. R is additionally extraordinarily bendy and effortless to use when it comes to growing visualisations.
One of its capabilities of R is to produce properly pleasant plots with minimal code. Data visualization is the art of how to flip numbers into useful knowledge. R Programming lets you analyze this art by supplying a set of built-in features and libraries to build visualizations and present data. R helps 4 different pix systems: base graphics, grid graphics, lattice graphics, and ggplot2. Base pics is the default pics machine in R, the easiest of the four systems to examine to use, and presents a wide variety of useful tools, specifically for exploratory snapshots where we desire to study what is in an unfamiliar dataset.
Paste your text right here and click on “Next” to watch this article rewriter do it is thing.There are a lot of R courses and lectures out there. However, R has a very steep mastering curve and college students frequently get overwhelmed. This path is different!
This path is truly step-by-step. In every new tutorial, we build on what had already learned and go one extra step forward.
After each video, you research a new treasured concept that you can practice right away. And the satisfactory section is that you research thru stay examples.
This education is packed with real-life analytical challenges which you will research to solve. Some of these we will remedy together, some you will have as homework exercises.
you will learn topics like;
The idea behind statistical plots, the foundation of ggplot2
Data transformation with dplyr and tidyr
Exploratory data analysis (EDA)
EDA for exploring two or more variables in different statistical plots
Combine ggplot2 with RMarkdown to wrap up your analysis and produce HTML reports
Create some additional types of plots by combining ggplot2 and supplementary libraries like word cloud, parallel coordinates plot, heat map, radar plot, etc.
Customize the plot’s theme
Create subplots using cowplot library
Highlight data on your plot with gghighlight library
Who this course is for
This course is for you if you want to learn how to program in R
This course is for you if you like challenges
Students Interested In Getting Started With Data Science Applications In The R & R Studio Environment
Students Interested in Gaining Exposure to Common R Packages Such As ggplot2
Those Interested in Learning About Different Kinds of Data Visualisations
Those Interested in Learning to Create Publication Quality Visualisations
Aspiring data scientists, statisticians or data (business) analysts
Anyone whose work is related with data presentation or extracting insights from the data
Anyone whose job, research or hobby is related to visualizing data
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