Data Analysis and Visualization with R for beginners

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Bluelime Learning Solutions

1:55:32

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1. Getting Started

1. Introduction.mp4

00:20

2. What is R.html

3. Installing R on Windows.mp4

02:01

4.1 Download and install R on Mac.pdf

4. Installing R on Mac.html

5. What is R Studio.html

6. Installing R studio on Windows.mp4

01:50

7.1 Download and install R Studio.pdf

7. Installing R Studio on Mac.html

8. Exploring R Studio Default Interface.mp4

09:32

9. Creating a new project in R Studio.mp4

05:34

10. What are Packages.html

11. How to install Packages.mp4

04:19

12. Data sets vs Data frames.html

13. Loading Packages.mp4

06:38

2. Data Analysis & Visualization

1.1 sydneybeaches.csv

1. Importing data into R Studio.mp4

05:44

2. How to read data in a csv file with R.mp4

06:28

3. Installing Janitor Package.mp4

03:30

4. Cleaning columns.mp4

11:18

5. Selecting a subset of data.mp4

04:53

6. Performing multiple operations using Pipe operator.mp4

09:36

7. Creating new columns from existing columns.mp4

10:00

8. Create a new R Project.html

9.1 chocolate.csv

9. Load data into new project.mp4

06:08

10. What is Data Wrangling.html

11. Data Wrangling steps.html

12. Importance of data wrangling.html

13. Perform Data Wrangling on Data.mp4

12:25

14. Create a scatter plot.mp4

06:37

15. Create a bar graph.mp4

08:39

Description

Data exploration and Visualization using R

What You'll Learn?

Install R and RStudio
Create new R Projects
Create R variables (objects)
Install and load R Packages
Import data into R Studio
Perform data wrangling on your data
Pipe several functions into a dataset using the Pipe function
Create data visualizations using graphs
Read data into a variable

Who is this for?

Beginners to data analysis and visualization using R

More details

Description
R is a programming language. R is often used for statistical computing and graphical presentation to analyse and visualize data.
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, â€¦) and graphical techniques, and is highly extensible.
One of Râ€™s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.
R is available as Free Software under the terms of the Free Software Foundationâ€™s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes
an effective data handling and storage facility,
a suite of operators for calculations on arrays, in particular matrices,
a large, coherent, integrated collection of intermediate tools for data analysis,
graphical facilities for data analysis and display either on-screen or on hardcopy, and
a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.

RStudio is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
Who this course is for:
Beginners to data analysis and visualization using R

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