# My 3 video presentations on “Essential R”

**R – Giga thoughts …**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

In this post I include my 3 video presentations on the topic “Essential R”. In these 3 presentations I cover the entire landscape of R. I cover the following

- R Language – The essentials
- Key R Packages (dplyr, lubridate, ggplot2, etc.)
- How to create R Markdown and share reports
- A look at Shiny apps
- How to create a simple R package

**Essential R – Part 1**

This video cover basic R data types – character, numeric, vectors, matrices, lists and data frames. It also touches on how to subset these data types

**Essential R – Part 2**

This video continues on how to subset dataframes (the most important data type) and some important packages. It also presents one of the most important job of a Data Scientist – that of cleaning and shaping the data. This is done with an example unclean data frame. It also touches on some key operations of dplyr like select, filter, arrange, summarise and mutate. Other packages like lubridate, quantmod are also included. This presentation also shows how to use base plot and ggplot2

**Essential R – Part 3**

This final session covers R Markdown , and touches on some of the key markdown elements. There is a brief overview of a simple Shiny app. Finally this presentation also shows the key steps to create an R package

These 3 R sessions cover most of the basic R topics that we tend to use in a our day-to-day R way of life. With this you should be able to hit the ground running!

Hope you enjoy these video presentation and also hope you have an even greater time with R!

Also see

1. Introducing QCSimulator: A 5-qubit quantum computing simulator in R

2. Computer Vision: Ramblings on derivatives, histograms and contours

3. Designing a Social Web Portal

4. Revisiting Whats up, Watson – Using Watson’s Question and Answer with Bluemix – Part 2

5. Re-introducing cricketr! : An R package to analyze performances of cricketers

To see all my posts click – Index of posts

**leave a comment**for the author, please follow the link and comment on their blog:

**R – Giga thoughts …**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.