Suggests: testthat (>= 0.11.0), roxygen2 (>= 5.0.1), Rhipe, lattice
X-CRAN-Comment: Orphaned and corrected on 2018-08-19 as check problems

Title: Access and Use Spain Government's API
Authors@R: c(person("Adrian", "Perez", email = "adrianpelopez@gmail.com", role =
"cre"), person("Francisco", "Charte", email = "francisco@fcharte.com", role =
Description: Functions intended to work with the API of the Spain Government <https://datos.gob.es/en/apidata> that allows you to download, analyze and generate information through datasets obtained from the API. The API containing information about multiples topics from the municipalities and organizations of Spain, it is possible to find URIs corresponding to the primary sector taxonomy and the identification of geographical coverage defined in Annexes IV and V <https://www.boe.es/diario_boe/txt.php?id=BOE-A-2013-2380> (NTI).
Imports: stringr, dplyr, readr, httr, stringi, jsonlite, graphics,
readxl, readODS, yaml, shiny, shinythemes, shinycssloaders,

Description: This contains versions of standard data frame functions in
R, modified to avoid making extra copies of inputs.  This is

Title: Familiarity with Dataframes Before Data Manipulation
Authors@R: person("Ashrith", "Reddy", email = "ashrithssreddy@gmail.com", role = c("aut", "cre"))
Description: Real life data is muddy, fuzzy and unpredictable. This makes data manipulations tedious and bringing the data to right shape alone is a major chunk of work. Functions in this package help us get an understanding of dataframes to dramatically reduces data coding time.
The package describes the datatypes of columns, generates frequency of each value in a dataframe column, creates percentile table and determines level of dataset.
Imports: tibble, data.table, magrittr, openxlsx, dplyr, plyr, tidyr

Imports: tibble, data.table, magrittr, openxlsx, dplyr, plyr, tidyr,
Packaged: 2020-06-26 06:22:25 UTC; Ashrith Reddy

Packaged: 2020-11-10 08:45:15 UTC; Ashrith Reddy

Packaged: 2022-04-04 06:56:02 UTC; Ashrith Reddy