3 - R and RStudio Basics
- Introduction to RStudio
- Introduction to Core R Data Types
- Introduction to R Control Flow
- Overview of R Data Input and Output
- R Data Wrangling: Transformation using Base R
- Basic RStudio tour: console, editor, environment/build/git, help/packages
- How to run RStudio: Application, Server, Cloud
- Basic Data Types
- Vector, Matrix, … of
- Date, Datetime, factors, …
- If time: More on types, dispatch, classes, …
- Compound Types
- Not Covered
- Language Object
- Getting Data In is part of just about any analysis!
- R excels at this
- truly broad coverage of file formats
- as well as ‘backends’ such as databases
- or different web-based APIs
- Our focus: read/write of csv data
- Mention other formats: json, xml, …
- Efficient R-specific storage: rds
- Mention protobuf, msgpack, feather, fst, …
- Data wrangling topics
- modifying by adding columns
- subsetting and summaries
- conditional operation by groups
- merging (and its relationship to SQL joins)
- functional programming approaches
- Chapter 4: Basics of R in Lander, R for Everyone, 2017.
- Chapter 5: Advanced Data Structures
in Lander, R for Everyone, 2017.
- Chapter 7: R Programming Structures in Matloff, Art of R Programming, 2011.
- Chapter 6: Reading Data into R in Lander, R for Everyone, 2017.
- Chapter 5: Data Frames in Matloff, Art of R Programming, 2011.
- Chapter 6: Factor And Tables in Matloff, Art of R Programming, 2011.
- Sections 1 and 2 of Chapter 11, Group Manipulations in Lander, R for Everyone, 2017.