Udemy

Data Visualization with R and ggplot2

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  • 2,096 名學生
  • 更新於 10/2024
4.4
(279 個評分)
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課程資料

報名日期*
全年招生
課程級別
學習模式
修業期
20 小時 41 分鐘
教學語言
英語
授課導師
Marko Intihar, PhD
評分
4.4
(279 個評分)
*提示: 以上時間表僅供參考,以機構網站為準。

課程簡介

Data Visualization with R and ggplot2

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

Today we live in a world where tons of data is generated every second. We need to analyze data to get some useful insight. One of the strongest weapons for data insight is data visualization. Probably you have heard this one before: "A picture tells more than a thousand words combined ". Therefore to tell stories from the data we need tools for producing adequate and amazing graphics. Here R as one of the most rapidly growing tools in the fields of data science and statistics provides needed assistance. If you combine R with its library ggplot2 you get one of the deadliest tools for data visualization, which grows every day and is freely accessible to anyone.


This course is designed to first give you quick and proper theoretical foundations for creating statistical plots. Then you dive into the world of exploratory data analysis where you are confronted with different datasets and creating a wide variety of statistical plots.


If you take this course, you will learn a ton of new things. Here are just a few topics you will be engaged with:

  • The grammar of graphics (the idea behind statistical plots, the foundation of ggplot2)

  • Data transformation with dplyr and tidyr (crash course included)

  • Exploratory data analysis (EDA) (statistical plots for exploring one continuous or one discrete variable)

  • EDA for exploring two or more variables (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 (word cloud, parallel coordinates plot, heat map, radar plot, ...)

  • Draw maps to show the spread of coronavirus disease

  • Customize the plot's theme

  • Create subplots using cowplot library

  • Highlight data on your plot with gghighlight library

  • and much more...


Course includes:

  • over 20 hours of lecture videos,

  • R scripts and additional data (provided in the course material),

  • engagement with assignments, where you have to test your skills,

  • assignments walkthrough videos (where you can check your results).

All being said this makes one of Udemy's most comprehensive courses for data visualization using R and ggplot2.


Enroll today and become the master of data visualization!!!


課程章節

  • 11 個章節
  • 110 堂課
  • 第 1 章 Course intro
  • 第 2 章 ggplot2 foundations
  • 第 3 章 Data wrangling crash course
  • 第 4 章 Exploratory data analysis
  • 第 5 章 Explore two variables
  • 第 6 章 Explore many variables
  • 第 7 章 Analysis wrap up with RMarkdown
  • 第 8 章 ggplot2 for standard plots and beyond
  • 第 9 章 Additional plot customization
  • 第 10 章 Mimic graphics challenge
  • 第 11 章 Course outro

課程內容

  • Visualize data, Foundations of data visualization (Grammar of Graphics and ggplot2), Transform data before visualization is applied (data wrangling libraries), Apply exploratory data analysis techniques with R and ggplot2, Wrap up analysis using RMarkdown reports, Use ggplot2 for creating many different standard statistical plots


評價

  • T
    Touchanun Komonpaisarn
    3.5

    Sometimes, the pace of typing is too fast and the multi lines of previous commands are off the screen , so it can be difficult for the students to follow.

  • T
    Thomas Goj
    5.0

    Alles wurde sehr schön Schritt für Schritt erklärt. Auch wenn ich ggplot2 schon länger verwende, so habe ich dennoch einiges neues gelernt, was ich nun anwenden kann. Fantastisch!

  • A
    Andrea Carpignani
    3.0

    The course is overall a nice one, and there are plenty of topics treated during the sessions. I have struggled a little to complete it, because of the amount of different areas touched very briefly. Also, when the instructor teaches, he often seem to speak to himself, rather than to the audience, and sometimes he just goes on with his coding without really explaining the rationale of what he is about to do. It is a good course to follow through, but only if there is already an idea of what it is going on. Otherwise, it can easily become frustrating for this lack of explanation.

  • G
    Gabriel Castañeda
    5.0

    Excelent Professor. I like the way he explains. I'm looking for a course similar to this one with the same quality for SQL and Python.

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