|
Introducing R and RStudio IDE
|
R is a powerful, popular open-source scripting language
You can customize the layout of RStudio, and use the project feature to manage the files and packages used in your analysis
RStudio allows you to run R in an easy-to-use interface and makes it easy to find help
|
|
R Basics
|
Effectively using R is a journey of months or years. Still you don’t have to be an expert to use R and you can start using and analyzing your data with with about a day’s worth of training
It is important to understand how data are organized by R in a given object type and how the mode of that type (e.g. numeric, character, logical, etc.) will determine how R will operate on that data.
Working with vectors effectively prepares you for understanding how data are organized in R.
|
|
R Basics continued - factors and data frames
|
It is easy to import data into R from tabular formats including Excel. However, you still need to check that R has imported and interpreted your data correctly
There are best practices for organizing your data (keeping it tidy) and R is great for this
Base R has many useful functions for manipulating your data, but all of R’s capabilities are greatly enhanced by software packages developed by the community
|
|
Aggregating and Analyzing Data with dplyr
|
Use the dplyr package to manipulate data frames.
Use glimpse() to quickly look at your data frame.
Use select() to choose variables from a data frame.
Use filter() to choose data based on values.
Use mutate() to create new variables.
Use group_by() and summarize() to work with subsets of data.
|
|
Data Visualization with ggplot2
|
|
|
Producing Reports With knitr
|
Mix reporting written in R Markdown with software written in R.
Specify chunk options to control formatting.
Use knitr to convert these documents into PDF and other formats.
|