Graphics in R: Data Visualization and Data Analysis with R

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Nkosingimele Ngcobo || hi-mathstats

13:14:55

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1 - Introduction

1 - Introduction to the Course.mp4

08:09

2 - R and R Studio set up

2 - R 422 and R Studio download and installation.mp4

03:14

3 - R studio walkthrough.mp4

02:37

3 - R for Beginners Data Structures Crash

4 - Creating vectors with c function.mp4

02:35

5 - Creating named vectors with names function.mp4

03:33

6 - Vectors Attributes.mp4

12:06

7 - Matrices Creating matrices with rbind and cbind.mp4

04:16

8 - Matrices Creating matrices with matrix function.mp4

02:20

9 - Matrices creating matrices with names.mp4

02:18

10 - Arrays Creating Arrays in r.mp4

01:29

11 - Arrays Attributes subsets.mp4

04:50

12 - Creating lists.mp4

03:32

13 - subscripting lists subsets of a list.mp4

04:02

14 - Referencing elements in a list.mp4

03:09

15 - Appending elements in a list.mp4

03:21

16 - Creating dataframe.mp4

02:38

17 - Querying data frames attributes.mp4

03:08

18 - Selecting columns in a data frame.mp4

04:04

4 - Introduction to Factors in R

19 - Creating factors in R.mp4

02:50

20 - Factors with factor levels.mp4

03:15

21 - grep and gsub functions.mp4

06:39

5 - Importing data into R with tidyverse package

22 - Importing a csv file in r.mp4

02:19

23 - Importing an excel file in r with tidyverse package.mp4

03:28

6 - Data Analysis Transformation and Manipulation

24 - Introduction to Data Manipulation.mp4

01:44

25 - sorting datasets with sort function.mp4

01:44

26 - Appending.mp4

02:30

27 - Duplicated Values.mp4

06:29

7 - Merging with merge function

28 - Understanding Merging.mp4

02:03

29 - Merging data frames with merge function.mp4

04:45

30 - left right outer merging using merge function.mp4

07:45

8 - reshape package melting and casting

31 - what is melting and casting.mp4

04:56

32 - melting with melt function.mp4

07:42

33 - casting with cast function.mp4

02:47

9 - tidyr package gather and spread function

34 - introduction to gather and spread function.mp4

03:11

35 - gather function.mp4

06:53

36 - spread function.mp4

02:58

10 - dplyr package

37 - Introduction to dplyr package for data analysis.mp4

04:32

38 - create a tabledf object from a data frame.mp4

02:55

39 - dplyr sort descending and ascending with arrange function.mp4

03:34

40 - subscripting with filter and select function.mp4

04:20

41 - add a new column with mutate function.mp4

03:24

42 - inner join function.mp4

01:50

43 - dplyr merging functions.mp4

07:09

44 - what is a pipe operator.mp4

04:10

45 - pipe operator example.mp4

08:17

11 - Graphics in R Beginner Level

46 - Introduction to Graphics.mp4

03:49

47 - Graphic device create pdf file.mp4

01:41

48 - Graphic device create image device.mp4

01:29

49 - Introduction to the plot function.mp4

03:30

50 - Plot function in R.mp4

07:43

51 - Plot Types.mp4

01:15

52 - Line Graph with base R.mp4

08:35

53 - Introduction to low level graphics functions in R.mp4

04:08

54 - Adding points and lines.mp4

03:37

55 - Adding text.mp4

02:16

56 - Adding Legend.mp4

06:27

57 - Multiple displays with par function.mp4

03:44

58 - Coding Exercise Instructions.html

59 - Coding Exercise Solution.mp4

03:51

12 - Data Visualization in R Beginner Level

60 - Introduction to Data Visualizations.mp4

02:17

61 - Barplots Pie Charts The understanding.mp4

05:10

62 - Barplots in R Favorite EPL team mock survey dataset.mp4

04:59

63 - Controlling width and space of the bars.mp4

02:36

64 - Adding Titles to barplot.mp4

01:19

65 - Adding legend and creating a horizontal bar plot.mp4

05:54

66 - Stacked and Grouped Bar plots.mp4

06:43

67 - Pie Chart in R.mp4

01:39

68 - Pie Chart with percentages with R.mp4

04:54

69 - Histogram The understanding.mp4

03:03

70 - Histogram with R.mp4

05:31

71 - Histogram with value marker Histogram with mean and labels.mp4

02:19

72 - Histogram with Kernel density KDE in r.mp4

02:26

73 - Multiple Histograms.mp4

02:23

74 - Boxplot The understanding.mp4

03:06

75 - Boxplot in R.mp4

11:00

76 - Adding means to a boxplot.mp4

02:59

77 - Scatterplots The understanding.mp4

02:07

78 - Scatterplot revisited.mp4

06:10

13 - Beginner Project Financial Budget Analysis

79 - Project Outline.html

79 - financial-budget.csv

80 - Project Solution.mp4

14:02

81 - Percentage Distributions of the Funds.mp4

06:34

14 - Beginner Project Billionaires Analysis

82 - Billionaire.csv

82 - Project Outline.html

83 - Analyzing Billionaires by their Net Worth using R programming.mp4

11:30

15 - Intermediate Data Visualization Graphics with GGPLOT 2

84 - Understanding ggplot2 package.mp4

02:54

16 - ggplot2 package qplot function in action

85 - Understanding qplot function.mp4

02:21

86 - Visualization with qplot function in R.mp4

03:52

87 - qplot function adding geometric layers.mp4

10:47

88 - devices with ggplot2 ggsave fucntion.mp4

03:24

89 - Available geometric layers in ggplot2 regular expression.mp4

06:17

90 - Creating scatterplots and line graphs with geometric layers with qplot function.mp4

05:59

91 - smooth with qplot function.mp4

02:55

92 - grouped scatterplots with qplot.mp4

07:04

93 - qplot adding text to a scatterplot.mp4

04:16

94 - Boxplot and violin plot with qplot function.mp4

04:41

95 - Histogram with qplot function.mp4

03:45

96 - Creating density plot with qplot function.mp4

01:53

17 - ggplot2 ggplot function in action

97 - What are Aesthetics.mp4

02:54

98 - Understanding ggplot2 with ggplot function.mp4

11:01

99 - Visualization with ggplot function.mp4

13:22

100 - Aesthetics in R.mp4

06:47

101 - Creating scatterplots with ggplot function.mp4

08:00

102 - Example Visualizing gdp growth with ggplot function.mp4

05:23

102 - gdp.zip

103 - Grouped line chart with ggplot function.mp4

09:13

104 - Ecommerce website visits with ggplot function Barplots with ggplot2.mp4

11:32

104 - ecom.zip

105 - Visualizing stock returns with ggplot function Boxplots with ggplot2.mp4

09:41

105 - stock-returns.zip

106 - Stock returns with ggplot Aesthetics in boxplots.mp4

07:00

107 - Ecommerce website visits with ggplot function Create histogram with ggplot2.mp4

07:00

107 - web-visits.zip

108 - Ecommerce website visits with ggplot function Histogram mapping with ggplot2.mp4

02:16

18 - ggplot2 project Billionaires Analysis with ggplot2 package

109 - Billionaire.csv

109 - Project Outline Material.html

110 - Analyzing Billionares using ggplot2 Solution walkthrough.mp4

10:50

19 - Lattice Package

111 - 4.Lattice-Package.pptx

111 - Introduction to Lattice Package.html

112 - Creating scatterplots with Lattice Package.mp4

06:54

112 - diamonds.csv

113 - Grouped Scatterplots with lattice package.mp4

03:24

114 - Grouping scatterplots with panels.mp4

01:28

115 - Creating Bargraphs with lattice package.mp4

02:56

116 - Grouped bar graphs with lattice package.mp4

01:58

117 - Grouping bar charts with panels using lattice package.mp4

03:40

118 - Creating Boxplots with lattice package.mp4

04:39

119 - Controlling layout with lattice package.mp4

00:59

120 - Creating dot plot and strip plot with lattice package.mp4

05:19

121 - Creating Histogram with lattice package.mp4

04:12

122 - Creating density plot with lattice package.mp4

01:33

123 - Understanding lattice panel functions.mp4

02:34

124 - Lattice package panel functions in R.mp4

06:13

125 - Creating a panel function with Lattice Package.mp4

05:06

20 - Lattice Package project Home Loan Approvals Visualization project

126 - Home Loans Approval dataset.html

126 - home-loans.csv

127 - Home loan approval analysis with lattice package Solution.mp4

15:36

21 - Going Further with Data Visualizations

128 - Handling devices in R Switching between devices in r.mp4

04:28

129 - Closing devices in r.mp4

02:07

130 - Layout function in r.mp4

04:50

131 - showing layout with layoutshow.mp4

05:24

22 - ggplot2 scales and guides

132 - What is scaling in ggplot2.mp4

03:30

133 - scalexcontinous.mp4

08:12

134 - scaleycontinous.mp4

03:14

135 - scalecolormanual.mp4

07:26

136 - scalefillmanual.mp4

06:55

137 - scaleshapemanual.mp4

06:12

138 - scalesizemanual.mp4

07:31

139 - scalealphacontinous.mp4

06:31

140 - ggplot2 with guide guide guidelegend.mp4

14:31

141 - ggplot2 with guide argument guidecolorbar.mp4

03:40

23 - Faceting with gglot2

142 - Faceting aka paneling.mp4

07:16

143 - ggplot facetwrap.mp4

07:33

144 - ggplot facetgrid.mp4

03:28

24 - ggplot2 themes

145 - ggplot2 themes examples.mp4

07:15

146 - ggplot2 legend themes.mp4

06:36

147 - ggplot2 global themes.mp4

03:06

25 - Credit Card Approvals Visualization Project

148 - Credit Card Approval dataset description.html

148 - credit-cards.csv

149 - Credit Card Approvals project solution with ggplot2.mp4

16:38

150 - Credit Card Approvals project solution with ggplot2 continue.mp4

06:56

26 - Interactive r plots ggvis package from shiny

151 - ggvis package explained.mp4

05:27

152 - Scatterplot with ggvis package.mp4

05:27

153 - ggvis interactive scatter plot ggvis input slider.mp4

05:46

154 - ggvis addaxis labels title.mp4

06:04

155 - ggvis addlegend.mp4

02:21

156 - ggvis add regression line confidence intervals.mp4

03:23

157 - ggvis barplot or bar graph line graph with points.mp4

03:09

158 - ggvis boxplot and interactive histogram example.mp4

03:46

27 - Supermarket Sales Visualization Project

159 - Supermarket Sales data and outline.html

159 - market.csv

160 - Supermarket Sales Analysis solution walkthrough.mp4

08:23

161 - Supermarket Sales Analysis solution walkthrough part 2.mp4

12:45

28 - 3d scatter plots in r

162 - 3D Scatterplot example in r.mp4

05:45

163 - 3D Scatterplot in r group by shapes.mp4

04:00

164 - 3D Scatterplot in r group by color.mp4

01:43

165 - 3D Scatterplot in r group by shapes and color.mp4

05:43

Description

Advance your data visualization skills using r packages. Master ggplot2, lattice, interactive plots with ggvis package

What You'll Learn?

Visualize real world datasets in the professional industries such as finance, health, insurance, marketing, sales
How to visualize data with ggplot2 package
Statistical Data visualizations with qplot function
Statistical Data visualizations with ggplot function
Master themes in R using ggplot2 package
Master Faceting with facet_wrap() and facet_grid()
Master scaling and guides R using scaling functions from ggplot2 package
Use plot function in R to create histograms, box and whisker plots, scatterplots, pie charts, barplots
Intermediate Data Visualization with the lattice package
How to use lattice package to create grouped scatterplots, barcharts
Master panel functions and high level functions in lattice package
How to switch between Graphics devices in R
Learn how to use ggvis package
How to create interactive plots with ggvis package from shiny
Create interactive scatterplots, histograms, boxplots with input slider from ggvis package
Data Analysis with dplyr package
Data Analysis with tidyr package
Data Analysis with reshape package
Factors in R and regular expressions
Master 3D Scatterplots in R
Use ggplot2 to visualize real world datasets
Use lattice package to visualize real world datasets
Create interactive plots from real world datasets with ggvis package

Who is this for?

Beginners in R programmers who are not in a rush to master everything at once

Beginner R programmers who want to learn data visualization

Absolute beginners in Programming

University or college students wanting to learn data visualizations using R

Post graduates students who are keen on using R for exploration and data analysis

More details

Description
Learn data visualizations by projects that use real world datasets in the professional industries such as finance, marketing, sales etc.

This course will help you master data visualizations techniques and create graphics in R using packages such as ggplot2, lattice package and ggvis package from shiny for adding interactivity into you R graphics.

Real world datasets are used for projects. So, not only will you master the graphics in r, you will also be able to interpret your graphics and make an impressive plots. All done by yourself.

Why learn data visualization with R?

Data Visualization helps people see, interact with, and better understand the data. Whether simple or complex, the right visualization can bring everyone on the same page, regardless of their level of expertise.
Almost all the professional industries benefit from making data more understandable. Every STEM field benefits from data analysts that are able to understand dataâ€”and so do fields in government, finance, marketing, history, consumer goods, service industries, education, sports, and so on.

As the â€œage of Big Dataâ€ and "Artificial Intelligence (AI)"Â kicks into high gear, visualization is an increasingly key tool to make sense of the trillions of rows of data generated every day. Data visualization helps to tell stories by curating data into a form easier to understand, highlighting the trends and outliers. A good visualization tells a story, removing the noise from data and highlighting useful information.

With R tools such as ggplot2 , lattice package, we can create visually appealing graphics and data visualizations by writing few lines of code. For this purpose R is widely used and it is easy to use and understand when it comes to data visualizations, good appealing graphics, data analysis (dplyr) etc. Through R, we can easily customize our data visualization by changing axes, fonts, legends, annotations, and labels.

In this data visualization course you will learn the following:

R for beginners: Vectors, Matrices, Arrays, Data frames and Lists
Factors in R: Create factors, understand factor levels
regular expressions in r: grep and gsub functions
reshape package for data analysis: melt and casting functions
tidyr package for data analysis: gather and spread functions
dplyr package for data analysis: merge functions, filter, select, sort, arrange, pipe operator etc
After Mastering R Programming for beginners and Data Analysis, you will begin creating graphics with r and visualizations. Here is the summary overview of what you will learn:
Graphics in R: Beginner Level
Graphic Devices & Colors
The Plot Function
Low Level Functions
Data Visualization in R: Beginner Level
Barplots & Pie Charts
Histograms in r
Box and Whisker Plots
Scatterplots
Intermediate Data Visualization & Graphics in R
What is ggplot2?
qplot() function
ggplot() function
Data Visualization with Lattice Package
Lattice Graphics
High Level Functions in lattice package
Lattice Package panel functions
Going further with data visualization
How to Handle and switch between graphics
Controlling layout with layout function
ggplot2 scales and guides:
scale_x_continous, scale_y_continous, scale_color_manual,scale_fill_manual
scale_shape_manual,scale_shape_manual,scale_alpha_continous
guide_legend, gudei_colorbar
ggplot2 faceting: facet_wrap() vs facet_grid()
ggplot2 themes
ggvis package:
scatterplot with layers, interactive plots with input_slider(), add_legend(), add_axis etc
After completing the course you will receive the electronic certificate that you can add on your resume or CV and LinkedIn profile from Udemy.
The access to this course is also lifetime, hence you will learn at your own pace. The course is also updated regularly to ensure it meets all the students demands and students enrolled are learning latest version of r and r studio
I am certain with all the material covered in this course you will be able to advance you Data visualization and Data Analysis skills!
See you in the first lecture!

Who this course is for:
Beginners in R programmers who are not in a rush to master everything at once
Beginner R programmers who want to learn data visualization
Absolute beginners in Programming
University or college students wanting to learn data visualizations using R
Post graduates students who are keen on using R for exploration and data analysis

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Hi. I appreciate you taking your time to know more about me.Currently working as a Quantitative Analyst & Completing Masters in Data Science.I hold a Bachelor of Science in Applied Mathematics & Statistics. I also hold an Honors degree in Statistics in which I graduated cum laude. I have been tutoring students in Mathematics & Data Science. I have take time to advance myself in programming and coding in :- T-SQL -Python Programming for Data Science-R Programming- MATLAB - SAS Programming- Javascript, JQuery, HTML, CSSI have made everything clear in all the courses I have on Udemy. The courses don't only include looking into the code but also all the output is well explained and interpreted. I am certain when you enroll you will gain useful skills in all the courses.

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