Mastering in Visualization with R programming

Mastering in Visualization with R programming, available at $19.99, has an average rating of 3.85, with 92 lectures, based on 16 reviews, and has 426 subscribers.

You will learn about learn what is R Programming Visualization with R Base Graphics v/s Advanced Graphics using R analytics tool ggplot2 package googleVis package plotrix package Types of graphs basic plotting advanced plotting This course is ideal for individuals who are Freshers or experts or learners or Anaytics professional or data anayst or IT professional or R professional It is particularly useful for Freshers or experts or learners or Anaytics professional or data anayst or IT professional or R professional.

Enroll now: Mastering in Visualization with R programming

Summary

Title: Mastering in Visualization with R programming

Price: $19.99

Average Rating: 3.85

Number of Lectures: 92

Number of Published Lectures: 92

Number of Curriculum Items: 92

Number of Published Curriculum Objects: 92

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

learn what is R Programming
Visualization with R
Base Graphics v/s Advanced Graphics using R analytics tool
ggplot2 package
googleVis package
plotrix package
Types of graphs
basic plotting
advanced plotting

Who Should Attend

Freshers
experts
learners
Anaytics professional
data anayst
IT professional
R professional

Target Audiences

Freshers
experts
learners
Anaytics professional
data anayst
IT professional
R professional

This course is about R programming’s feature of visualizing the data. R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among data miners and statisticians for developing statistical software. R has many features like Programming feature, statistical feature and visualizing feature.

In this course first we’ll focusing towards Basic understanding of R programming and then from very basic to advanced graphics features with use of several packages like ggplot2, plotrix, googleVis etc. In this Course we’ll plot different kinds of specialised charts and graphs like bar plots, scatter plots, histograms, pie charts, google maps, wordclouds, box plot, organizational charts, pictographs, table plot, line graphs, nested barcharts, gantt chart, zoom in plot, fan plots, 3D plots, Radial plots, tree maps, heat maps, area charts, venn diagram and many more.

Course Curriculum

Chapter 1: Module 1: Introduction to the Course

Lecture 1: 1.1 What is Data Visualization?

Chapter 2: Module 2: Basic R Programming

Lecture 1: 2.1 Importance of Data Visualization

Lecture 2: 2.2 R programming Overview

Lecture 3: 2.3 Variables in R

Lecture 4: 2.4 Matrices and Vector

Lecture 5: 2.5 Dataframes and List

Lecture 6: 2.6 Factors and summary methods

Chapter 3: Module 3: Basic Plotting of Graphs in R programming

Lecture 1: 3.1 Plot Function

Lecture 2: 3.2 Adding Colors to a Graph- 1

Lecture 3: 3.3 Adding Colors to a Graph- 2

Lecture 4: 3.4 Adding Colors to a Graph-3

Chapter 4: Module 4: Types of Graphs

Lecture 1: 4.1 Types of Graphs

Lecture 2: 4.2 Line Graph

Lecture 3: 4.3 Scatter Plot

Lecture 4: 4.4 Barplot

Lecture 5: 4.5 Histogram

Lecture 6: 4.6 Pie Chart

Lecture 7: 4.7 Table Plot

Lecture 8: 4.8 Box Plot

Lecture 9: 4.9 Organizational Chart

Lecture 10: 4.10 Network Graph

Chapter 5: Module 5: Visualization using ggplot2 Package

Lecture 1: 5.1 Introduction to ggplot2 Package

Lecture 2: 5.2 qplot Function

Lecture 3: 5.3 Deep dive with ggplot2 Package

Lecture 4: 5.4 ggthemes

Lecture 5: 5.6 Facets

Lecture 6: 5.7 Legends

Lecture 7: 5.8 Annotation

Lecture 8: 5.9 Area Chart

Chapter 6: Module 6: Visualization using Plotrix Package

Lecture 1: 6.1 Introduction to plotrix package

Lecture 2: 6.2 Nested Bar Chart

Lecture 3: 6.3 Gantt Chart

Lecture 4: 6.4 Zoom-In-plot

Lecture 5: 6.5 Fan Plot

Lecture 6: 6.6 3D Pie Chart

Lecture 7: 6.7 Adding table to a Plot

Lecture 8: 6.8 Radial Plot

Chapter 7: Module 7: Visualization using googleVis Package

Lecture 1: 7.1 Introduction to googleVis Package

Lecture 2: 7.2 Combination Chart

Lecture 3: 7.3 Bubble Chart

Lecture 4: 7.4 Gauge Chart

Lecture 5: 7.5 Google Maps

Lecture 6: 7.6 Timeline Chart

Lecture 7: 7.7 Tree Map

Lecture 8: 7.8 Calendar Chart

Lecture 9: 7.9 Venn Diagram

Lecture 10: 7.10 WordCloud

Chapter 8: PROGRAMS CODE

Lecture 1: basic math

Lecture 2: variables

Lecture 3: MATRICES

Lecture 4: VECTORS

Lecture 5: DATA FRAME

Lecture 6: LIST

Lecture 7: FACTOR

Lecture 8: SUBSET

Lecture 9: SUMMARIZING

Lecture 10: PLOT FUNCTION

Lecture 11: RColorBrewer

Lecture 12: LINE GRAPH

Lecture 13: SCATTER PLOT

Lecture 14: BARPLOT

Lecture 15: HISTOGRAM

Lecture 16: PIE CHART

Lecture 17: TABLE PLOT

Lecture 18: BOX PLOT

Lecture 19: PICTOGRAM

Lecture 20: ORGANIZATIONAL CHART

Lecture 21: QPLOT

Lecture 22: GGPLOT

Lecture 23: GGTHEMES

Lecture 24: FACETS

Lecture 25: LEGEND

Lecture 26: ANNOTATION

Lecture 27: 3D PIE CHART

Lecture 28: TABLE PLOT

Lecture 29: FAN PLOT

Lecture 30: GANTT CHART

Lecture 31: NESTED BAR CHART

Lecture 32: RADIAL PLOT

Lecture 33: ZOOMINPLOT

Lecture 34: BUBBLE CHART

Lecture 35: CALENDAR CHART

Lecture 36: COMBO CHART

Lecture 37: GAUGE CHART

Lecture 38: GOOGLE MAPS

Lecture 39: TIMELINE CHART

Lecture 40: TREE MAP

Lecture 41: 3DSCATTER PLOT

Lecture 42: AREA CHART

Lecture 43: HEAT MAP

Lecture 44: VENN DIAGRAM

Lecture 45: WORDCLOUD

Instructors

Elementary Learners
Make learning online

Rating Distribution

1 stars: 1 votes
2 stars: 3 votes
3 stars: 3 votes
4 stars: 4 votes
5 stars: 5 votes

Frequently Asked Questions

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