lintr (>= 2.0.0), R6, readr, repr, stringr, styler (>= 1.2.0),
Suggests: covr, fs, knitr, magrittr, mockery, processx, purrr, testthat

Title: Automated Setup and Auto Run for R Language Server
Authors@R: person("Jozef", "Hajnala", email = "jozef.hajnala@gmail.com", role = c("aut", "cre"))
Description: Allows to install the R 'languageserver' with all dependencies
into a separate library and use that independent installation
automatically when R is instantiated as a language server process.
Useful for making language server seamless to use without
SystemRequirements: procps (linux), tasklist (windows)

SystemRequirements: procps (linux), ps (macos), wmic (windows)

Title: Work with Look at NanoSIMS Data in R
Description: R interface for working with nanometer scale secondary ion mass
spectrometry (NanoSIMS) data exported from Look at NanoSIMS.
Authors@R: person("Sebastian", "Kopf", email = "sebastian.kopf@colorado.edu",
Imports: dplyr, tidyr, reshape2, ggplot2, lazyeval, R.matlab
Suggests: testthat, rmarkdown, knitr, covr

Imports: dplyr, tidyr, reshape2, ggplot2, rlang, R.matlab

Title: History of labour relations package
Authors@R: c(person("Richard", "Zijdeman", role = c("aut", "cre"),
person("Josemiguel", "Lana-Berasain", role = "ctb",
Description: This package is intended for researchers studying historical labour relations (see http://www.historyoflabourrelations.org). The package allows for easy access of excel files in the standard defined by the Global Collaboratory on the History of Labour Relations. The package also allows for visualisation of labour relations according to the Collaboratory's format.
Imports: data.table, grid, treemap, xlsx

Title: Analytics, Data Mining & Machine Learning Sidekick
person("Bernardo", "Lares", , "laresbernardo@gmail.com", c("aut", "cre")))
Description: R library for better/faster analytics, visualization, data mining, and machine learning
tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling,
Exploratory, and Scrapper, it helps the analyst or data scientist to get quick and robust
results, without the need of repetitive coding or extensive programming skills.
Imports: dplyr, ggplot2, h2o, httr, jsonlite, lubridate, magrittr,
openxlsx, patchwork, pROC, rlang, rpart, rvest, scales,
Suggests: beepr, DALEX, DBI, forecast, ggforce, ggrepel, googleAuthR,
googlesheets4, mice, quantmod, plotly, rdrop2, rlist,
rmarkdown, rtweet, skimr, sp, tm, wordcloud
Packaged: 2021-05-27 17:04:43 UTC; bernardolares