In project-evident/evidentiaRy: Easily Install and Load Useful Packages and Functions

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evidentiaRy

Overview

'evidentiaRy' (/ˌevəˈden(t)shəRē/) is a set of packages and functions that help non-profit organizations wrangle data and perform small and big tests of change. This package is designed to make it easy to install and load multiple packages and helpful functions in a single step.

This package was seeded by cloning the 'tidyverse' described at https://tidyverse.org. The tidyverse is a set of packages that work in harmony because they share common data representations and API design. The tidyverse package is designed to make it easy to install and load core packages from the tidyverse in a single command.

Installation

# Install from CRAN (at some point)
# install.packages("evidentiaRy")

# Or the development version from GitHub
# install.packages("devtools")
devtools::install_github("project-evident/evidentiaRy")

Usage

library(evidentiaRy) will load the core evidentiaRy packages:

• 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.
• stringr, for strings.
• forcats, for factors.

You also get a condensed summary of conflicts with other packages you have loaded:

library(evidentiaRy)

You can see conflicts created later with evidentiaRy_conflicts():

library(MASS)
evidentiaRy_conflicts()

And you can check that all tidyverse packages are up-to-date with evidentiaRy_update():

evidentiaRy_update()
#> The following packages are out of date:
#>  * broom (0.4.0 -> 0.4.1)
#>  * DBI   (0.4.1 -> 0.5)
#>  * Rcpp  (0.12.6 -> 0.12.7)
#> Update now?
#> 
#> 1: Yes
#> 2: No

Packages

As well as the core tidyverse, installing this package also installs a selection of other packages that you're likely to use frequently, but probably not in every analysis. This includes packages for:

• Working with specific types of vectors:

  • hms, for times.
  • lubridate, for date/times.

• Importing other types of data:

  • feather, for sharing with Python and other languages.
  • 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.

• Modelling

  • modelr, for modelling within a pipeline
  • broom, for turning models into tidy data

project-evident/evidentiaRy documentation built on May 23, 2019, 4:05 a.m.