person("Ma. Regina Paz S.", "Onglao", email = "monglao@ifc.org", role = c("cre", "aut")),
Author: Ma. Regina Paz S. Onglao [cre, aut],
Trade and Competitiveness Global Practice World Bank Group [cph]

Title: Wrapper for 'TCdata360' and 'Govdata360' API
person("Ma. Regina Paz", "Onglao-Drilon", email = "reg@drilon.com", role = c("cre", "aut")),
person("World Bank Group", email = "tcdata360@worldbank.org", role = "cph"))
of the 'TCdata360' and 'Govdata360' platforms at <https://tcdata360.worldbank.org/>
These application program interfaces provide access to over 5000 trade, competitiveness, and governance
Author: Ma. Regina Paz Onglao-Drilon [cre, aut],
Maintainer: Ma. Regina Paz Onglao-Drilon <reg@drilon.com>

person("Ramin", "Aliyev", email = "tcdata360@worldbank.org", role = "cre"),
person("Ma. Regina Paz", "Onglao-Drilon", email = "reg@drilon.com", role = "aut"),
person("World Bank Group", role = "cph"))

Imports: data.table, reshape2, jsonlite, utils

Title: Compare Two Data Frames and Summarise the Difference
Authors@R: c(person("Rob", "Noble-Eddy", email = "opensource@capitalone.com", role = c("aut", "cre")),
person("Sarah", "Johnston", role = c("aut")),
person("Sarah", "Pollicott", role = c("aut")),
person("Merlijn", "van Horssen", role = c("aut")),
person("Lukas", "Drapal", role = c("ctb")),
person("Nikolaos", "Perrakis", role = c("ctb")),
person("Nikhil", "Thomas Joy", role = c("ctb")),
person("Shahriar", "Asta", role = c("ctb")),
person("Karandeep", "Lidher", role = c("ctb")),
person("Dan", "Kellett", role = c("ctb")),
person("Kevin", "Chisholm", role = c("ctb")),
person("Laura", "Joy", role = c("ctb")),
person("Fergus", "Wadsley", role = c("ctb")),
person("Heather", "Hackett", role = c("ctb")),
person("David", "Robinson", role = c("ctb")),
person("Cheryl", "Renton", role = c("ctb")),
person("Matt", "Triggs", role = c("ctb")),
person("Krishan", "Bhasin", role = c("ctb")),
person("Carola", "Deppe", role = c("ctb"))
Description: Easy comparison of two tabular data
objects in R. Specifically designed to show differences between two sets of
data in a useful way that should make it easier to understand the differences,
and if necessary, help you work out how to remedy them. Aims
to offer a more useful output than all.equal() when your two data sets do not
match, but isn't intended to replace all.equal() as a way to test for equality.
Imports: dplyr, knitr, stringi, markdown
Suggests: testthat, data.table, tibble, bit64, rmarkdown, titanic