Suggests: covr, crayon, dplyr (>= 0.7.8), httr, knitr, rmarkdown,

Title: Tools at the Intersection of 'purrr' and 'dplyr'
Description: Some functions at the intersection of 'dplyr' and 'purrr' that
Imports: magrittr (>= 1.5), dplyr (>= 0.4.3), purrr, Rcpp, lazyeval (>=

Imports: magrittr (>= 1.5), dplyr (>= 0.4.3), purrr, Rcpp

Imports: magrittr (>= 1.5), dplyr (>= 0.8.0), purrr (>= 0.2.2), Rcpp

Description: Some functions at the intersection of 'dplyr' and
Imports: dplyr (>= 0.8.0), magrittr (>= 1.5), purrr (>= 0.2.2), Rcpp

Title: Add Progress Bars to Mapping Functions
Description: Provides functions to easily add progress bars to
Imports: R6, assertthat, glue, hms, methods, pkgcond, purrr, testextra,
Suggests: covr, datasets, stringi, testthat, tibble

Description: Create sliders from left, right, top and bottom which may include any html or 'Shiny' input or output.

Title: Send push notifications using Pushover
Description: A package for sending push notifications to iOS and Android

Description: A package for sending push notifications to mobile devices (iOS and

Title: Send Push Notifications using Pushover
Description: Send push notifications to mobile devices or the desktop using Pushover. These notifications can display job status, results, scraped web data, or any other text or numeric data.

Title: Send Push Notifications using 'Pushover'
person("Brian", "Connelly", , "bdc@bconnelly.net", role = c("aut", "cre"),
Description: Send push notifications to mobile devices or the desktop
using 'Pushover' <https://pushover.net>. These notifications can
display things such as results, job status, plots, or any other text
Imports: checkmate, cli, glue, httr, rlang
Packaged: 2021-11-15 23:33:18 UTC; bconnelly
Author: Brian Connelly [aut, cre] (<https://orcid.org/0000-0002-9948-0379>)

Title: Assembling Data Sets for Non-Linear Mixed Effects Modeling
person(c("Olivier"), "Barriere", role = "aut"),
person(c("Mario"), "Gonzalez Sales", role = c("aut", "cre"), email = "mario@modelinggreatsolutions.com")
Maintainer: Mario Gonzalez Sales <mario@modelinggreatsolutions.com>
Description: To Simplify the time consuming and error prone task of assembling complex data sets for non-linear mixed effects modeling. Users are able to select from different absorption processes such as zero and first order, or a combination of both. Furthermore, data sets containing data from several entities, responses, and covariates can be simultaneously assembled.
Imports: utils, lubridate, stats, readxl, reshape, reshape2, sqldf,
kableExtra, plyr, dplyr, tidyverse, readr
Suggests: rmarkdown, knitr, devtools, testthat