Mastering Data Visualization with R and ggplot2 – 2022

R 是用于统计计算、统计分析等的开源、开发良好且易于编程的语言。

R 具有内置的可视化库，可帮助现有的 & 借助 ggplot2、lattice、过度宪章、传单等，以简短的方式可视化信息。有助于产生多层图形。Lattice 有助于可视化多变量统计数据，而过多的章程是 JavaScript 中的可视化库。

R 中的数据可视化有助于在 RGL 的帮助下构建地图和 3D 绘图，并了解事件的顺序。R 是一个出色的事实分析平台，几乎可以成功创建任何类型的图形。R 是一种用于统计计算和图形的语言和环境。在不断增长的可视化方面，R 也非常灵活且易于使用。

R 的一项功能是用最少的代码生成适当的令人愉快的图。数据可视化是如何将数字转化为有用知识的艺术。R Programming 允许您通过提供一组内置功能和库来构建可视化和呈现数据来分析这种艺术。R 支持 4 种不同的像素系统：基本图形、网格图形、点阵图形和 ggplot2。Base pics 是 R 中的默认图片机器，是四个系统中最容易检查使用的，并提供了各种有用的工具，特别是用于我们希望研究不熟悉数据集中内容的探索性快照。

将您的文本粘贴到此处，然后单击“下一步”以观看本文重写者所做的事情。那里有很多 R 课程和讲座。然而，R 的掌握曲线非常陡峭，大学生经常不知所措。这条路不一样！

这条路真的是一步一步来的。在每一个新教程中，我们都会在已经学习的基础上再往前走一步。

在每个视频之后，您都会研究一个可以立即练习的新的宝贵概念。令人满意的部分是你通过留下的例子进行研究。

这种教育充满了现实生活中的分析挑战，您将研究以解决这些挑战。其中一些我们将一起补救，一些您将作为家庭作业练习。

您将学习以下主题；

统计图背后的思想，ggplot2 的基础

使用 dplyr 和 tidyr 进行数据转换

探索性数据分析 (EDA)

EDA 用于探索不同统计图中的两个或多个变量

将 ggplot2 与 RMarkdown 结合起来完成您的分析并生成 HTML 报告

通过结合 ggplot2 和补充库（如词云、平行坐标图、热图、雷达图等）来创建一些其他类型的图。

自定义剧情主题

使用 cowplot 库创建子图

使用 gghighlight 库突出显示绘图上的数据

Data Visualization using R Programming Language. GGplot2, Data Analysis, Data Preparation, Data Sciene Tools, RStudio

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

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