The Tidyverse

As we move through the rest of this course we will be working with a group of packages called the Tidyverse. These packages form a core set of functions that will allow you to perform most any type of data cleaning or analysis you will need to do. We will use the following from the tidyverse

ggplot2, for data visualisation.

dplyr, for data manipulation.

tidyr, for data tidying.

readr, for data import.

purrr, for functional programming.

tibble, for tibbles, a modern re-imagining of data frames.

The Tidyverse can be broken don into many different classes of functions and tools:

Data Import Specific

DBI, for databases.

haven, for SPSS, SAS and Stata files.

httr, for web apis.

jsonlite for JSON.

readxl, for .xls and .xlsx files.

rvest, for web scraping.

xml2, for XML.

Data Manipulation Specific

hms, for times.

stringr, for strings.

lubridate, for date/times.

forcats, for factors.

Modeling Specific

modelr, for simple modelling within a pipeline

broom, for turning models into tidy data