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## Video Description

Communicate and engage with interactive charts and graphs

In Detail

We process and analyse data to solve problems, so it doesn’t help anybody if you can’t communicate your findings to the world. This pragmatic Learning Path takes you through a brief refresher on R before diving right into coverage that has you creating interactive publication-ready graphs and visualizations. Let your data do all the talking, rather than the other way around.

Prerequisites: A functional understanding of R

• Introduction to R Programming

• Learning R for Data Visualization

• R Graph Essentials

• Building Interactive Graphs with ggplot2 and Shiny

• PATH PRODUCTS

This path navigates across the following products (in sequential order):

• Introduction to R Programming (3h 46m)

• R Graph Essentials (1h 57m)

1. Chapter 1 : Introduction to R Programming
1. The Course Overview 00:04:54
2. Installing R 00:03:46
3. Installing RStudio 00:04:36
4. Installing Packages 00:04:50
5. Data Types and Data Structures 00:03:05
6. Vectors 00:05:44
7. Random Numbers, Rounding, and Binning 00:04:00
8. Missing Values 00:02:47
9. The which() Operator 00:03:11
10. Lists 00:04:35
11. Set Operations 00:02:09
12. Sampling and Sorting 00:02:52
13. Check Conditions 00:02:17
14. For Loops 00:02:34
15. Dataframes 00:08:30
16. Importing and Exporting Data 00:06:30
17. Matrices and Frequency Tables 00:03:41
18. Merging Dataframes 00:02:26
19. Aggregation 00:02:48
20. Melting and Cross Tabulations with dcast() 00:03:58
21. Dates 00:05:35
22. String Manipulation 00:05:14
23. Functions 00:05:34
24. Debugging and Error Handling 00:04:30
25. Fast Loops with apply() 00:04:27
26. Fast Loops with sapply(), lapply() and vapply() 00:02:00
27. Creating and Customizing an R Plot 00:07:03
28. Drawing Plots with 2 Y Axes 00:02:23
29. Multiplots and Custom Layouts 00:03:08
30. Creating Basic Graph Types 00:04:47
31. Univariate Analysis 00:06:16
32. Normal Distribution, Central Limit Theorem, and Confidence Intervals 00:05:32
33. Correlation and Covariance 00:03:03
34. Chi-sq Statistic 00:04:42
35. ANOVA 00:04:54
36. Statistical Tests 00:05:14
37. Project 1 – Data Munging and Summarizing 00:11:31
38. Project 2 – Visualization with Base Graphics 00:05:42
39. Project 3 – Statistical Inference 00:03:50
40. Pipes with Magrittr 00:05:21
41. The 7 Data Manipulation Verbs 00:05:19
42. Aggregation and Special Functions 00:03:36
43. Two Table Verbs 00:02:43
44. Working With Databases 00:05:30
45. Understanding Basics, Filter, and Select 00:07:34
46. Understanding Syntax, Creating and Updating Columns 00:04:06
47. Aggregating Data, .N, and .I 00:04:21
48. data.table 00:04:17
49. Fast Loops with set(), Keys, and Joins 00:09:13
2. Chapter 2 : Learning R for Data Visualization
1. The Course Overview 00:05:32
2. Preview of R Plotting Functionalities 00:03:16
3. Introducing the Dataset 00:03:21
6. Exporting Data 00:04:19
7. Creating Histograms 00:05:01
8. The Importance of Box Plots 00:03:44
9. Plotting Bar Charts 00:02:43
10. Plotting Multiple Variables – Scatterplots 00:03:07
11. Dealing with Time – Time-series Plots 00:02:38
12. Handling Uncertainty 00:04:15
13. Changing Theme 00:03:07
14. Changing Colors 00:03:20
15. Modifying Axis and Labels 00:02:40
17. Adding Text Inside and Outside of the Plot 00:05:02
18. Multi-plots 00:03:59
19. Exporting Plots as Images 00:03:24
20. Adjusting the Page Size 00:02:33
21. Getting Started with Interactive Plotting 00:02:44
22. Creating Interactive Histograms and Box Plots 00:04:55
23. Plotting Interactive Bar Charts 00:03:12
24. Creating Interactive Scatterplots 00:02:58
25. Developing Interactive Time-series Plots 00:03:47
26. Getting Started with Shiny 00:04:09
27. Creating a Simple Website 00:04:52
28. File Input 00:03:09
29. Conditional Panels – UI 00:03:45
30. Conditional Panels – Servers 00:05:31
31. Deploying the Site 00:05:38
3. Chapter 3: R Graph Essentials
1. Introduction 00:02:02
2. Generating a Basic Plot with Titles 00:03:09
3. Putting Legends and Setting Margins 00:03:54
4. Putting Texts and Mathematical Expressions to the Plot 00:02:29
5. Symbols and Colors in the Plot 00:03:16
6. Saving the Plots in Various Formats 00:02:23
7. Controlling Axes and Boxes 00:02:25
8. Controlling Layouts and Splits 00:02:37
9. Controlling the Color of Plot Elements 00:02:12
10. Controlling Line Patterns and Width 00:02:14
11. Controlling Texts of Plot Elements 00:02:36
12. Pie Chart for One Variable 00:02:38
13. Bar Chart or Pareto Chart for One Variable 00:02:15
14. Bar Chart for More Than One Variable 00:02:05
15. Labeling the Pie and Bar Charts 00:02:28
16. Dot Charts 00:02:07
17. Stem-and-leaf Plots 00:03:01
18. Histogram, Comparison, and Handling Bins 00:02:54
19. Density, Rug Representation, and Overlay Plots 00:02:23
20. Boxplots and Parameters 00:02:14
21. Side-by-side Boxplots and Parameters 00:03:07
22. Scatter Plot and Parameters 00:02:31
23. Adding Straight Lines and Jitter Points 00:02:28
24. Adding Model Summaries in the Plot 00:03:45
25. Sub-grouping in a Scatter Plot 00:03:36
26. Conditioning Plots 00:01:32
27. Plotting Basic Line Graphs Using a Function 00:03:17
28. Default Time Series Plots 00:04:20
29. Plotting Date and Time Variables 00:02:01
30. Plotting Trend 00:02:11
31. Setting Appropriate Time Axes 00:02:00
32. Drawing Contour Plots in Base Package 00:02:00
33. Drawing Contour Plots in Lattice 00:01:45
34. Drawing Surfaceplot Using Base Graphics 00:01:49
35. Drawing Surfaceplot Using Lattice 00:02:10
36. Drawing an Interactive 3D Plot 00:02:11
37. Creating Maps 00:04:24
38. Interactive Options 00:04:47
39. R Commander 00:03:30
40. Trees and Clustering 00:02:42
41. RStudio Interface for Graphics 00:04:04
4. Chapter 4 : Building Interactive Graphs with ggplot2 and Shiny
1. Setting Up ggplot2 00:02:51
2. Understanding the Structure of a Plot 00:03:21
3. Mapping Data to Graphical Elements with Aesthetics 00:03:01
4. Understanding Some Subtleties with Aesthetics 00:03:01
5. Using ggplot2 in Scripts 00:02:47
6. Drawing Lines 00:02:28
7. Drawing Paths 00:01:46
8. Bar Charts 00:02:00
9. Histograms and Density Plots 00:02:48
10. Using Boxplots 00:02:33
11. Using Group and Color 00:02:07
12. Using Size and Color 00:01:57
13. Over Plotting Many Points with Jitter 00:02:07
14. Faceting with One Variable 00:01:39
15. Faceting with Two Variables 00:01:44
16. Linear Trends 00:01:56
17. Non-linear Trends 00:01:54
18. User-Defined Function 00:01:47
19. BigVis: Visualizing Big Data 00:02:10
20. BigVis: Smoothing Plots and Peeling Data 00:02:05
21. Controlling the Axes 00:02:19
22. Ordering Variables 00:01:55
23. Customizing the Color Palette for Categorical Variables 00:02:01
24. Customizing the Color Palette for Continuous Variables 00:02:49
25. Customizing the Axes Labels and the Legends 00:02:17
26. Creating Interactive Web Pages with Shiny 00:01:48
27. Understanding the Structure of a Shiny App 00:03:53
28. Rendering Text 00:02:46
29. Understanding Reactive Programming 00:03:54
30. Using a Button to Avoid Frequent Updates 00:02:18
31. Creating and Using Tabs 00:02:11
32. Scoping 00:02:52