R for Data Analysis

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Enrolled:32

Level

Beginner
Duration

8 hours 30 minutes
Last Updated

November 26, 2023
Enrollment validity

Enrollment validity: 365 days
Certificate

Certificate of completion

About Course

Just as an artist wields a brush to create stunning visuals, R empowers you to manipulate, explore, and breathe life into your data through its statistical computing and graphics capabilities. Join us on this captivating journey where you will learn to harness R's open-source magic, navigate its extensive libraries, and orchestrate flexible data handling to unveil the hidden stories within. From fitting and manipulating data and interpreting statistical models to unleashing the power of data visualization, this course will equip you with the tools to compose symphonies of insights and conduct awe-inspiring analyses. No prior knowledge required, just your curiosity and a desire to unlock the true potential of your data. Embark on this adventure and let your data come alive in ways you never imagined. Welcome to the realm of R.

Introduction to R and Data Analytics
Setting the Stage and Getting to Understand R
Data manipulation techniques using R
Reshape, filter, and aggregate data for analysis
Explore statistical concepts and hypothesis testing
Creating Visual Masterpieces: Data Visualization
Advanced Analytics: Modeling and Prediction
Predictive modeling using R
Integration with Data Analysis Toolkit
Develop a holistic approach to data exploration and interpretation
Real-world Data Analysis Projects
Hands-on projects inspired by real-world scenarios

Course Curriculum

Introduction

Introduction – Where Did R come from

00:52
Where Did R come from I

02:00
Where Did R come from II

01:18

Installing Base R and Rstudio

The Basics

Managing Workspace, Importing, and Saving

Vector Manipulation

Vector Functions

Indexing with Vectors []

Matrices and DataFrame

Advanced DataFrame Manipulation and Dplyr

Plotting

Introduction

00:33
Plot()

04:41
Scatter Plot – plot()

08:35
Histogram – hist()

05:35
Combining Histogram – hist()

05:32
Bar Plot – barplot()

07:18
Clustered Bar Plot – barplot()

06:48
Low-level Plotting

06:07
Grid() and Text()

09:21
Saving the Plots

04:22

Grammar of Graphics – GGPlot

Dates and Times

Control Structure

Functions

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R for Data Analysis

About Course

What will I learn?

Course Curriculum

Introduction

Introduction – Where Did R come from

Where Did R come from I

Where Did R come from II

Installing Base R and Rstudio

DOWNLOAD COURSE ATTENDANT FILE !

Introduction

Installing R Studio

The Four Studio Windows

Libraries and Packages

The Basics

The Basics

Objects in R

Attributes in R

Managing Workspace, Importing, and Saving

Introduction – Importing, Managing, and Saving Data

Workplace Management Functions

Creating Project Files in R

Importing .csv and Libraries

Vector Manipulation

Introduction – Vector Manipulation

Vector Manipulation I

Vector Manipulation II

Vector Manipulation III

Vector Manipulation IV

Vector Functions

Introduction – Vector Functions

Vector Functions I

Vector Functions II

Vector Functions III

Vector Functions IV

Indexing with Vectors []

Indexing with Vector I

Indexing with Vector II

Indexing with Vector III

Indexing with Vector IV

Indexing with Vector V

Indexing with Vector VI

Matrices and DataFrame

What are Matrices and DataFrame?

Creating Matrices and DataFrame

Working with DataFrame in R

DataFrame Column Names

Slicing with Subset()

Slicing DataFrames

With()

Advanced DataFrame Manipulation and Dplyr

Introduction

Order(); Sorting Data

Merge(); Combining Data

Aggregate(); Group Data

Select()

Filter() and Arrange()

Rename() and Mutate()

Pipe Operator

Group By() and Summarize()

Plotting

Introduction

Plot()

Scatter Plot – plot()

Histogram – hist()

Combining Histogram – hist()

Bar Plot – barplot()

Clustered Bar Plot – barplot()

Low-level Plotting

Grid() and Text()

Saving the Plots

Grammar of Graphics – GGPlot

Introduction

Grammar of Graphics (ggPlot2)

Bar and Column with ggPlot2

Bringing Dplyr to Charts

Box Plot and Scatter Plot

Facets and Themes

Other graphics

Dates and Times