R Data Visualization - Basic Plots, Maps, and Pie Charts
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R Data Visualization - Basic Plots, Maps, and Pie Charts

Master the visualization capabilities of R to build interactive graphs, plots, and Pie charts
0.0 (0 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
11 students enrolled
Created by Packt Publishing
Last updated 6/2017
Current price: $10 Original price: $125 Discount: 92% off
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  • 3 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Create simple and quick visualizations using the basic graphic tools in R.
  • Implement interactive visualizations using ggplot2.
  • Perform predictive modeling and create animated applications.
  • Visualize data using different kind of Maps.
  • Learn to create Plot function and merge multiple charts.
View Curriculum
  • Basic knowledge of R programming is expected.

R is an open source language for data analysis and graphics. It is platform-independent and allows users to load various packages as well as develop their own packages to interpret data better.This video is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization with R.

We start - off with the basics of R plots and an introduction to heat maps and customizing them. After this, we gradually take you through creating interactive maps using the googleVis package. Finally, we generate choropleth maps and contouring maps, bubble plots, and pie charts.

About the Author

Atmajit Singh Gohil works as a senior consultant at a consultancy firm in New York City. After graduating, he worked in the financial industry as a Fixed Income Analyst. 

He has a master's degree in financial economics from the State University of New York (SUNY), Buffalo. He also graduated with a Master of Arts degree in economics from the University of Pune, India. He loves to read blogs on data visualization and loves to go out on hikes in his free time.

Who is the target audience?
  • If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this video is for you.
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Curriculum For This Course
37 Lectures
A Simple Guide to R
10 Lectures 39:34

This video gives an overview of the entire course.

Preview 03:24

R comes loaded with some basic packages, but the R community is rapidly growing and active R users are constantly developing new packages for R.

Installing Packages and Getting Help in R

Everything in R is in the form of objects. Objects can be manipulated in R.

Data Types and Special Values in R

We will dive into R's capability with regard to matrices and edit (add, delete, or replace) elements of a matrix.

Matrices and Editing a Matrix in R

One of the useful and widely used functions in R is the data.frame() function.

Data Frames and Editing a Data Frame in R

Once we have processed our data, we need to save it to an external device or send it to our colleagues. It is possible to export data in R in many different formats.

Importing and Exporting Data in R

Most of the tasks in R are performed using functions. A function in R has the same utility as functions in Arithmetic.

Writing a Function and if else Statement in R

If we want to perform an action repeatedly in R, we can utilize the loop functionality.

Basic and Nested Loops in R

R has some very handy functions, such as apply, sapply, tapply, and mapply, that can be used to reduce the task of writing complicated statements.

The apply, lapply, sapply, and tapply Functions

One quick and easy way to edit a plot is by generating the plot in R and then using Inkspace or any other software to edit it.

Using and Saving par to Beautify a Plot in R
Basic and Interactive Plots
8 Lectures 55:10

Scatter plots are used primarily to conduct a quick analysis of the relationships among different variables in our data.

Preview 13:12

We will display multivariate data on a scatter plot and also introduce interactive scatter plots.

Connecting Points and Generating an Interactive Scatter Plot

The advantage of using the Google Chart API in R is the flexibility it provides in making interactive plots.

A Simple and Interactive Bar Plot

Line plots are simply lines connecting all the x and y dots. They are very easy to interpret and are widely used to display an upward or downward trend in data.

Introduction to Line Plot and Its Effective Story

Gantt charts are used to track the progress of a project displayed against time.

Generating an Interactive Gantt/Timeline Chart in R

Plot a histogram using the googleVis package and merge more than one histogram on the same page.

Merging Histograms

The advantage of the Google Chart API is the interactivity and the ease with which they can be attached to a web page.

Making an Interactive Bubble Plot

The waterfall plots or staircase plots are observed mostly in financial reports.

Constructing a Waterfall Plot in R
Heat Maps and Dendrograms
7 Lectures 29:26

This video helps you get introduced to the concept of dendrograms.

Preview 06:47

This video teaches you to create a plot which is easy to study and more informative.

Creating Dendrograms with Colors and Labels

Heat maps are a visual representation of data, wherein each value in a matrix is represented with a color. This video shows you how to create a heat map.

Creating Heat Maps

This video dives into plotting a heat map by customizing colors.

Generating a Heat Map with Customized Colors

This video teaches you to integrate a dendrogram and heat map into a single plot.

Generating an Integrated Dendrogram and a Heat Map

R allows us to plot three-dimensional interactive heat maps using the heat map package.

Creating a Three-Dimensional Heat Map and Stereo Map

Tree maps are basically rectangles placed adjacent to each other. The size of each rectangle is directly proportional to the data being used in the visualization.

Constructing A Tree Map in R
7 Lectures 33:59

We encounter maps on a daily basis, be it for directions or to infer information regarding the distribution of data. Maps have been widely used to plot various types of data in R.

Preview 04:28

Choropleth maps can be state level as well as county level. In this video, we will plot well-being data on a state level.

Introducing Choropleth Maps

Contour maps are used to display data related to temperature or topographic information.

A Guide to Contour Maps

For each region, a bubble or a pie chart is used that represents percentage.

Constructing Maps with bubbles

Overlaying maps with text is not a very prominent medium of displaying information.

Integrating Text with Maps

The shapefile package in R can be used to read a shapefile, add the processed data to our shapefile, and then save it in the shapefile format.

Introducing Shapefiles

The idea of a cartogram is to show the gravity of the issue or data being studied.

Creating Cartograms
The Pie Chart and Its Alternatives
5 Lectures 22:34

Pie charts are a great visualization technique to represent data and help viewers understand statistical data.

Preview 05:48

Labels are important as they give the information about the sections of the pie chart. We will include labels inside the pie chart in this video.

Constructing Pie Charts with Labels

Donut charts have advantages over pie charts with respect to the area and efficiency in visualizing information.

Creating Donut Plots and Interactive Plots

Instead of using multiple pie charts for comparing data, we can use slope charts.

Generating a Slope Chart

Fan plots are an alternative to pie charts and are useful in differential and comparative analysis.

Constructing a Fan Plot
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