dplyr, readr, stringr, jsonlite, lubridate, httr, purrr

dplyr, readr, stringr, jsonlite, lubridate, httr, purrr, curl

c(
person("Simon P.", "Couch", , "simonpatrickcouch@gmail.com", c("aut", "cre")),
person("Kaelyn", "Rosenberg", , "kaerosenberg@gmail.com", c("aut")),
person("Mark", "Padgham", , "mark.padgham@email.com", c("ctb")))
Supplies a set of functions to interface with bikeshare data
following the General Bikeshare Feed Specification, allowing users to query
and accumulate tidy datasets for specified cities/bikeshare programs.
Simon P. Couch [aut, cre],
Kaelyn Rosenberg [aut],
Mark Padgham [ctb]

A high performance interface to the Global Biodiversity
Information Facility, 'GBIF'.  In contrast to 'rgbif', which can
access small subsets of 'GBIF' data through web-based queries to
a central server, 'gbifdb' provides enhanced performance for R users
performing large-scale analyses on servers and cloud computing
providers, providing full support for arbitrary 'SQL' or 'dplyr'
operations on the complete 'GBIF' data tables (now over 1 billion
records, and over a terabyte in size). 'gbifdb' accesses a copy
of the 'GBIF' data in 'parquet' format, which is already readily
available in commercial computing clouds such as the Amazon Open
Data portal and the Microsoft Planetary Computer, or can be
accessed directly without downloading, or downloaded
to any server with suitable bandwidth and storage space.
The high-performance techniques for local and remote access
are described in <https://duckdb.org/why_duckdb>
and <https://arrow.apache.org/docs/r/articles/fs.html> respectively.
c(
person("Carl", "Boettiger", , "cboettig@gmail.com", c("aut", "cre"),
comment = c(ORCID = "0000-0002-1642-628X"))
)
spelling, dbplyr, testthat (>= 3.0.0), covr, knitr,
rmarkdown, aws.s3
Carl Boettiger [aut, cre] (<https://orcid.org/0000-0002-1642-628X>)

This package implements extensions
to Freund and Schapire's AdaBoost algorithm and J. Friedman's
gradient boosting machine. Includes regression methods for least
squares, absolute loss, logistic, Poisson, Cox proportional hazards
partial likelihood, and AdaBoost exponential loss.