Prerequisites
0.1
This is work in progress
0.2
Motivation
0.3
Motivation for base R solutions
0.4
Structure of this book
0.5
Contribution
0.6
Conventions
0.6.1
Tasks
0.6.2
Solutions
0.6.3
Example task
I Idioms
1
Idioms
1.1
The four basic principles to a tidy API
1.1.1
Reuse existing data structures.
1.1.2
Compose simple functions with the pipe.
1.1.3
Embrace functional programming.
1.1.4
Design for humans.
1.2
Resources
2
Non-standard evaluation
2.1
Formulas
2.2
Resources
II Data access
3
Read and write data
3.1
Flatfiles
3.2
Internet/Urls
3.3
Database connections
3.4
Cubes
3.5
Distributed Systems
3.6
Resources
III Acting on common data structures
4
Data frames and tibbles
4.1
Basic operations and related stuff
4.2
Reshaping wide and long data
4.3
Typical mutate statements
4.3.1
Split and paste
4.3.2
Conditionals
4.3.3
IDs
4.3.4
Other stuff
4.4
Formatting
4.5
Joins
4.6
Tibbles
4.7
Resources
IV Atomics
5
Strings
5.1
Basic string operations
5.2
Pattern matching
5.2.1
Regular expressions
5.2.2
Modifiers
5.3
List output
5.4
Resources
6
Factors
6.1
Resources
7
Dates and times
7.1
Dates
7.2
Dates and Times
7.3
Intervals
7.4
Resources
8
Lists
9
List columns within data frames
10
Tidy data structures
V Applications
11
Models
11.1
Resources
12
Statistics
12.1
Resources
13
Text mining
13.1
Resources
14
Time series
14.1
Resources
15
Web scraping
15.1
Resources
VI Ohter stuff
16
Utilities
16.1
Control structures
16.2
Pipes
16.3
Resources
17
Testchapter
17.1
New contributions
17.2
Proposal for Description
18
RStudio project management
18.1
Project types
18.2
Project options
18.3
Version control
18.4
Packrat and package dependencies
18.5
Addins
18.6
Miscellaneous
19
Labelled data
19.1
Basic operations
20
Spatial data
20.1
IO
20.2
Objects
20.3
Arithmetics
20.4
Plots
20.5
Resources
Tidyverse Cookbook
13
Text mining
13.1
Resources
Tidy Text Mining with R