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Mastering Data Visualization with R

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Mastering Data Visualization with R, available at $74.99, has an average rating of 4.61, with 76 lectures, 3 quizzes, based on 524 reviews, and has 4138 subscribers.

You will learn about Understand which plots are suitable for different types of data, ensuring you choose the best visualization method for your analysis. Learn to analyze and understand your data thoroughly before creating any plots, leading to more accurate and insightful visualizations. Master the art of data visualization by creating various types of graphs using R's base package, lattice, and ggplot2 packages. Gain hands-on experience through a case study on selecting a diamond, illustrating the use of ggplot() for complex data visualization tasks. Develop the ability to create clear, informative, and aesthetically pleasing visualizations that effectively communicate your data insights. Learn to use the lattice package for creating multi-panel plots, allowing for a more comprehensive view of your data. Apply data visualization techniques to real-world scenarios, improving your ability to present data-driven insights compellingly. Enhance your resume with advanced data visualization skills in R, making you a valuable asset in data-driven roles. Gain confidence in your ability to transform complex data into clear and actionable visual insights using R. This course is ideal for individuals who are Data Science, Six Sigma and other professionals interested in data visualization It is particularly useful for Data Science, Six Sigma and other professionals interested in data visualization.

Enroll now: Mastering Data Visualization with R

Summary

Title: Mastering Data Visualization with R

Price: $74.99

Average Rating: 4.61

Number of Lectures: 76

Number of Quizzes: 3

Number of Published Lectures: 76

Number of Published Quizzes: 2

Number of Curriculum Items: 79

Number of Published Curriculum Objects: 78

Original Price: $74.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understand which plots are suitable for different types of data, ensuring you choose the best visualization method for your analysis.
  • Learn to analyze and understand your data thoroughly before creating any plots, leading to more accurate and insightful visualizations.
  • Master the art of data visualization by creating various types of graphs using R's base package, lattice, and ggplot2 packages.
  • Gain hands-on experience through a case study on selecting a diamond, illustrating the use of ggplot() for complex data visualization tasks.
  • Develop the ability to create clear, informative, and aesthetically pleasing visualizations that effectively communicate your data insights.
  • Learn to use the lattice package for creating multi-panel plots, allowing for a more comprehensive view of your data.
  • Apply data visualization techniques to real-world scenarios, improving your ability to present data-driven insights compellingly.
  • Enhance your resume with advanced data visualization skills in R, making you a valuable asset in data-driven roles.
  • Gain confidence in your ability to transform complex data into clear and actionable visual insights using R.

Who Should Attend

  • Data Science, Six Sigma and other professionals interested in data visualization

Target Audiences

  • Data Science, Six Sigma and other professionals interested in data visualization

This course will help you draw meaningful knowledge from the data you have.

Three systems of data visualization in R are covered in this course:

A. Base Graphics    B. Lattice package  C. GGPlot2

     

A. Types of graphs covered in the course using the base R package:

Single Continuous Variable:  Histogram, Density Plot, Box-Whisker Plot 

Single Discrete Variable:Bar Chart 

Two Continuous Variable: Scatter Plot

Two Variable: One Continuous, One Discrete: Box-Whisker Plot, Pie Chart, Dot Chart, Strip Chart 

Two Variables: Both Discrete:Mosaic Plot, Stacked Bar Plot       

Time series:Line Charts

B. Types of graphs covered in the Lattice package:
Histogram, Density Plot, Box-Whisker Plot, Bar Chart, Scatter Plot, Dot Chart, Strip Chart

C. Graphs covered in GGPlot2 package:
In this section you will learn about 7 layers in ggplot() and how to use these. In addition there is a project of selecting a diamond from the dataset  of 54000 diamonds, based on my budget.

Commonly Used Graphs: Histogram, Density Plot, Box-Whisker Plot, Bar Chart, Scatter Plot, Dot Chart, Strip Chart

What are other students saying about this course?

  • Very thorough. Covers all the details without glossing over anything. Good consistent pace and nice short segments. Very diligent in always saying what keys he was pressing during the demos, which is often overlooked. Excellent course. (5 stars byRoger Holeywell)

  • Explanations are clear and coherent. This course is well structured and very-very useful. Thank you so much for your help! (5 stars byMartina Katalin Szabó)

  • Todos os cursos oferecidos pelo Prof. Sandeep Kumar na Udemy são excelentes, especialmente em análise e visualização de dados.(5 stars by Jose Maria Nogueira da Costa )

Course Curriculum

Chapter 1: *** Section 1: Introduction and Getting Started with R ***

Lecture 1: Section 1: Introduction

Lecture 2: R Studio First Look

Lecture 3: Data Types in R

Lecture 4: Vector

Lecture 5: Factor

Lecture 6: List

Lecture 7: Matrix

Lecture 8: Data Frame

Lecture 9: Section 1 Downloads: R Code File and Notes File

Chapter 2: *** Section 2: Explore the Data Before Visualization ***

Lecture 1: Section 2: Introduction

Lecture 2: Exploring Datasets Available in the R Base Package

Lecture 3: Datasets Available in ggplot2 Package

Lecture 4: Section 2 Downloads: R Code File and Notes File

Chapter 3: *** Section 3: Planning for Visualization – What Plot to Use? ***

Lecture 1: Section 3: Introduction

Lecture 2: Plotting single continuous variable

Lecture 3: Plotting single discrete variable

Lecture 4: Plotting two continuous variables

Lecture 5: Plotting one continuous and one discrete variable

Lecture 6: Plotting two discrete variables

Lecture 7: Plotting time series

Lecture 8: Section 3 Downloads: Notes File

Chapter 4: *** Section 4: Visualization Using R Base Commands ***

Lecture 1: Section 4: Introduction

Lecture 2: 1 Plotting Histogram

Lecture 3: 2 Density Plot

Lecture 4: 3 Box Plot

Lecture 5: 4 Bar Plot

Lecture 6: 5 Scatter Plot

Lecture 7: 5a Scatter Plot Part 2

Lecture 8: 6 Box Plot by group

Lecture 9: 7 Pie Chart

Lecture 10: 8 Dot Chart

Lecture 11: 9 Strip Chart

Lecture 12: 10 Mosaic Chart

Lecture 13: 11 Stacked Bar Chart

Lecture 14: 12 Time Series

Lecture 15: Section 4 Downloads: R Code File and Notes File

Lecture 16: Assignment 1 : Plots Using Base R Commands

Chapter 5: *** Section 5: Visualization Using Lattice Package ***

Lecture 1: Section 5: Introduction

Lecture 2: Introduction to Lattice Plots

Lecture 3: Drawing a Histogram using Lattice Package – Part 1

Lecture 4: Drawing a Histogram using Lattice Package – Part 2

Lecture 5: Drawing a Histogram using Lattice Package – Part 3

Lecture 6: Density Plot Using Lattice – Part 1

Lecture 7: Density Plot Using Lattice – Part 2

Lecture 8: Box and Whisker Plot Using Lattice

Lecture 9: Bar Plot Using Lattice

Lecture 10: Scatter Plot Using Lattice

Lecture 11: Scatter Plot Matrix Using Lattice

Lecture 12: 3D Scatter Plot Using Lattice

Lecture 13: Dot and Strip Plots

Lecture 14: Section 5 Downloads: R Code File and Notes File

Lecture 15: Assignment 2: Plots Using Lattice Package

Chapter 6: *** Section 6: Visualization Using ggplot2 Package ***

Lecture 1: Section 6: Introduction

Lecture 2: Introduction to ggplot2 Package

Lecture 3: Your First Visualization Using ggplot2 Package

Lecture 4: A Few More geoms with Single Continuous Variable

Lecture 5: Project Introduction: Selecting a Diamond

Lecture 6: Project: Analyzing Diamonds by Carat Size – Part 1

Lecture 7: Project: Analyzing Diamonds by Carat Size – Part 2

Lecture 8: Project: Analyzing Diamonds by Cut

Lecture 9: Project: Analyzing Diamonds by Color

Lecture 10: Project: Analyzing Diamonds by Clarity – Final Selection

Lecture 11: Data and Aesthetics Layers in ggplot

Lecture 12: Aethetics Layer – Part 2

Lecture 13: geom Layer in ggplot

Lecture 14: facets Layer in ggplot

Lecture 15: stats Layer in ggplot

Lecture 16: coord Layer in ggplot – Changing Scale

Lecture 17: coord Later in ggplot – Changing Ratio

Lecture 18: coord Layer in ggplot – Polar Coordinates and Pie Chart

Lecture 19: coord Layer in ggplot – Axis Transformation

Lecture 20: Themes Layer in ggplot

Lecture 21: Quick and Easy – qplot()

Lecture 22: Section 6 Downloads: R Code File and Notes File

Lecture 23: Assignment 3: Plots Using GGPlot2 Package

Chapter 7: Bonus Section

Lecture 1: BONUS LECTURE

Instructors

Rating Distribution

  • 1 stars: 3 votes
  • 2 stars: 12 votes
  • 3 stars: 45 votes
  • 4 stars: 183 votes
  • 5 stars: 281 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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