<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>ropensci-champions.r-universe.dev</title><link>https://ropensci-champions.r-universe.dev</link><description>Recent package updates in ropensci-champions</description><generator>R-universe</generator><image><url>https://github.com/ropensci-champions.png</url><title>R packages by ropensci-champions</title><link>https://ropensci-champions.r-universe.dev</link></image><lastBuildDate>Fri, 22 May 2026 14:15:16 GMT</lastBuildDate><item><title>[ropensci-champions] chartkickR 0.0.0.9000</title><author>bilqiiswunmi@gmail.com (Bilikisu Olatunji)</author><description>Provides an R interface to the Chartkick.js JavaScript
charting library using the htmlwidgets framework. The package
allows users to create interactive line, bar, column, area,
pie, donut, scatter, bubble, geo, and timeline charts from R
data frames with minimal code.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/26300057757</link><pubDate>Fri, 22 May 2026 14:15:16 GMT</pubDate><r:package>chartkickR</r:package><r:version>0.0.0.9000</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/BWOlatunji/chartkickR</r:upstream></item><item><title>[ropensci-champions] bulkreadr 1.2.2.9000</title><author>gbganalyst@gmail.com (Ezekiel Ogundepo)</author><description>Designed to simplify and streamline the process of reading
and processing large volumes of data in R, this package offers
a collection of functions tailored for bulk data operations. It
enables users to efficiently read multiple sheets from
Microsoft Excel and Google Sheets workbooks, as well as various
CSV files from a directory. The data is returned as organized
data frames, facilitating further analysis and manipulation.
Ideal for handling extensive data sets or batch processing
tasks, bulkreadr empowers users to manage data in bulk
effortlessly, saving time and effort in data preparation
workflows. Additionally, the package seamlessly works with
labelled data from SPSS and Stata.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/24935878641</link><pubDate>Sat, 25 Apr 2026 16:17:28 GMT</pubDate><r:package>bulkreadr</r:package><r:version>1.2.2.9000</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/gbganalyst/bulkreadr</r:upstream><r:article><r:source>intro-to-bulkreadr.Rmd</r:source><r:filename>intro-to-bulkreadr.html</r:filename><r:title>Importing &amp; exporting bulk data</r:title><r:created>2025-04-28 10:42:04</r:created><r:modified>2025-04-28 11:52:41</r:modified></r:article><r:article><r:source>labelled-data.Rmd</r:source><r:filename>labelled-data.html</r:filename><r:title>Introduction to labelled data</r:title><r:created>2024-02-25 21:58:33</r:created><r:modified>2026-03-20 12:42:20</r:modified></r:article><r:article><r:source>other-functions.Rmd</r:source><r:filename>other-functions.html</r:filename><r:title>Other Utility Functions in bulkreadr</r:title><r:created>2024-02-25 21:58:33</r:created><r:modified>2026-04-25 16:17:28</r:modified></r:article></item><item><title>[ropensci-champions] naijR 0.7.0</title><author>victorordu@outlook.com (Victor Ordu)</author><description>A set of convenience functions as well as
geographical/political data about Nigeria, aimed at simplifying
work with data and information that are specific to the
country.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/25483261651</link><pubDate>Sun, 08 Mar 2026 07:20:23 GMT</pubDate><r:package>naijR</r:package><r:version>0.7.0</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/ropensci/naijR</r:upstream><r:article><r:source>interactive.Rmd</r:source><r:filename>interactive.html</r:filename><r:title>Approach to Correcting Misspelt Local Government Areas</r:title><r:created>2022-01-28 15:26:50</r:created><r:modified>2023-08-10 10:33:07</r:modified></r:article><r:article><r:source>nigeria-maps.Rmd</r:source><r:filename>nigeria-maps.html</r:filename><r:title>nigeria-maps</r:title><r:created>2020-05-15 20:25:43</r:created><r:modified>2026-03-06 19:24:37</r:modified></r:article></item><item><title>[ropensci-champions] pcir 0.0.0.9000</title><author>francesca@alumni.usp.br (Francesca Belem Lopes Palmeira)</author><description>Provides functions to calculate, compare, and visualize
the Potential for Conflict Index (PCI), a descriptive statistic
that summarizes the level of agreement or disagreement among
stakeholders.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/25986118159</link><pubDate>Wed, 21 May 2025 19:07:06 GMT</pubDate><r:package>pcir</r:package><r:version>0.0.0.9000</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/fblpalmeira/pcir</r:upstream></item><item><title>[ropensci-champions] agroclimatico 1.1.0</title><author>paola.corrales@cima.fcen.uba.ar (Paola Corrales)</author><description>Conjunto de funciones para calcular índices y estadísticos
climáticos hidrológicos a partir de datos tidy. Incluye una
función para graficar resultados georeferenciados y e
información cartográfica.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/25367093292</link><pubDate>Mon, 05 May 2025 06:00:56 GMT</pubDate><r:package>agroclimatico</r:package><r:version>1.1.0</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/AgRoMeteorologiaINTA/agroclimatico</r:upstream><r:article><r:source>estadisticas-e-indices-climaticos.Rmd</r:source><r:filename>estadisticas-e-indices-climaticos.html</r:filename><r:title>Estadísticas e índices climáticos</r:title><r:created>2020-11-15 23:42:57</r:created><r:modified>2024-07-29 10:56:55</r:modified></r:article></item><item><title>[ropensci-champions] odbr 0.1.1</title><author>hsvab@hsvab.eng.br (Haydee Svab)</author><description>Download data from Brazil's Origin Destination Surveys.
The package covers both data from household travel surveys,
dictionaries of variables, and the spatial geometries of
surveys conducted in different years and across various urban
areas in Brazil. For some cities, the package will include
enhanced versions of the data sets with variables &quot;harmonized&quot;
across different years.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/25718403315</link><pubDate>Thu, 13 Feb 2025 12:27:21 GMT</pubDate><r:package>odbr</r:package><r:version>0.1.1</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/hsvab/odbr</r:upstream><r:article><r:source>odbr.Rmd</r:source><r:filename>odbr.html</r:filename><r:title>Introduction to odbr</r:title><r:created>2023-10-12 06:12:47</r:created><r:modified>2025-02-12 13:48:14</r:modified></r:article></item><item><title>[ropensci-champions] bbsTaiwan 1.0.0</title><author>sunnyyctseng@gmail.com (Sunny Tseng)</author><description>The goal of bbsTaiwan is to streamline the retrieval and
analysis of Taiwan Breeding Bird Survey (BBS) data. This
package facilitates data access from GBIF, where Taiwan BBS
data are stored. While the data is openly available on GBIF,
its complex arrangement in the Darwin Core format can make it
challenging to understand and use, often requiring advanced
data wrangling skills. The bbsTaiwan package is designed to
simplify this process, making it easier to access and utilize
Taiwan BBS data.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/26022448713</link><pubDate>Mon, 23 Sep 2024 09:48:27 GMT</pubDate><r:package>bbsTaiwan</r:package><r:version>1.0.0</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/SunnyTseng/bbsTaiwan</r:upstream><r:article><r:source>bbsTaiwan.Rmd</r:source><r:filename>bbsTaiwan.html</r:filename><r:title>bbsTaiwan</r:title><r:created>2024-03-29 16:35:44</r:created><r:modified>2024-09-23 01:59:05</r:modified></r:article></item><item><title>[ropensci-champions] eph 1.0.2</title><author>carolinapradier@gmail.com (Carolina Pradier)</author><description>Tools to download and manipulate the Permanent Household
Survey from Argentina (EPH is the Spanish acronym for Permanent
Household Survey). e.g: get_microdata() for downloading the
datasets, get_poverty_lines() for downloading the official
poverty baskets, calculate_poverty() for the calculation of
stating if a household is in poverty or not, following the
official methodology. organize_panels() is used to concatenate
observations from different periods, and organize_labels() adds
the official labels to the data. The implemented methods are
based on INDEC (2016)
&lt;http://www.estadistica.ec.gba.gov.ar/dpe/images/SOCIEDAD/EPH_metodologia_22_pobreza.pdf&gt;.
As this package works with the argentinian Permanent Household
Survey and its main audience is from this country, the
documentation was written in Spanish.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/26145486108</link><pubDate>Tue, 06 Aug 2024 17:01:23 GMT</pubDate><r:package>eph</r:package><r:version>1.0.2</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/ropensci/eph</r:upstream><r:article><r:source>eph.Rmd</r:source><r:filename>eph.html</r:filename><r:title>Ejemplo de uso del paquete eph</r:title><r:created>2019-11-11 00:39:16</r:created><r:modified>2023-09-14 23:15:18</r:modified></r:article><r:article><r:source>estimacion_pobreza.Rmd</r:source><r:filename>estimacion_pobreza.html</r:filename><r:title>Estimación de Pobreza e Indigencia</r:title><r:created>2020-06-16 18:11:56</r:created><r:modified>2024-06-19 16:01:52</r:modified></r:article></item><item><title>[ropensci-champions] karel 0.1.1.9001</title><author>marcosprunello@gmail.com (Marcos Prunello)</author><description>This is the R implementation of Karel the robot, a
programming language created by Dr. R. E. Pattis at Stanford
University in 1981. Karel is an useful tool to teach
introductory concepts about general programming, such as
algorithmic decomposition, conditional statements, loops, etc.,
in an interactive and fun way, by writing programs to make
Karel the robot achieve certain tasks in the world she lives
in. Originally based on Pascal, Karel was implemented in many
languages through these decades, including 'Java', 'C++',
'Ruby' and 'Python'. This is the first package implementing
Karel in R.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/25911280132</link><pubDate>Sat, 27 Jul 2024 00:24:38 GMT</pubDate><r:package>karel</r:package><r:version>0.1.1.9001</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/ropensci/karel</r:upstream><r:article><r:source>a_intro_progrbasics_es.Rmd</r:source><r:filename>a_intro_progrbasics_es.html</r:filename><r:title>1 - Introducción y nociones básicas</r:title><r:created>2021-08-08 16:18:54</r:created><r:modified>2024-07-27 00:24:38</r:modified></r:article><r:article><r:source>a_intro_progrbasics_en.Rmd</r:source><r:filename>a_intro_progrbasics_en.html</r:filename><r:title>1 - Introduction and programming basics</r:title><r:created>2023-06-14 23:52:14</r:created><r:modified>2024-07-27 00:24:38</r:modified></r:article><r:article><r:source>b_meetingkarel_es.Rmd</r:source><r:filename>b_meetingkarel_es.html</r:filename><r:title>2 - Conociendo a Karel</r:title><r:created>2021-08-08 16:18:54</r:created><r:modified>2024-03-27 23:31:58</r:modified></r:article><r:article><r:source>b_meetingkarel_en.Rmd</r:source><r:filename>b_meetingkarel_en.html</r:filename><r:title>2 - Meeting Karel</r:title><r:created>2023-06-14 23:52:14</r:created><r:modified>2024-04-24 15:06:31</r:modified></r:article><r:article><r:source>c_decomposition_en.Rmd</r:source><r:filename>c_decomposition_en.html</r:filename><r:title>3 - Algorithmic decomposition</r:title><r:created>2023-06-16 02:59:09</r:created><r:modified>2024-04-24 15:06:31</r:modified></r:article><r:article><r:source>c_decomposition_es.Rmd</r:source><r:filename>c_decomposition_es.html</r:filename><r:title>3 - Descomposición algorítmica</r:title><r:created>2021-08-08 16:18:54</r:created><r:modified>2024-03-27 23:31:58</r:modified></r:article><r:article><r:source>d_controlstructures_en.Rmd</r:source><r:filename>d_controlstructures_en.html</r:filename><r:title>4 - Control structures</r:title><r:created>2023-06-16 02:59:09</r:created><r:modified>2024-03-27 23:31:58</r:modified></r:article><r:article><r:source>d_controlstructures_es.Rmd</r:source><r:filename>d_controlstructures_es.html</r:filename><r:title>4 - Estructuras de control del código</r:title><r:created>2021-08-08 16:18:54</r:created><r:modified>2024-03-27 23:31:58</r:modified></r:article><r:article><r:source>e_examples_en.Rmd</r:source><r:filename>e_examples_en.html</r:filename><r:title>5 - Examples</r:title><r:created>2023-06-16 02:59:09</r:created><r:modified>2024-03-27 23:31:58</r:modified></r:article><r:article><r:source>e_examples_es.Rmd</r:source><r:filename>e_examples_es.html</r:filename><r:title>5 - Varios problemas de ejemplo</r:title><r:created>2021-08-08 16:18:54</r:created><r:modified>2024-03-27 23:31:58</r:modified></r:article><r:article><r:source>aa_get_started_en.Rmd</r:source><r:filename>aa_get_started_en.html</r:filename><r:title>Get started with Karel the robot</r:title><r:created>2023-06-15 23:52:16</r:created><r:modified>2024-04-24 15:06:31</r:modified></r:article><r:article><r:source>aa_get_started_es.Rmd</r:source><r:filename>aa_get_started_es.html</r:filename><r:title>Primeros pasos con la robot Karel</r:title><r:created>2023-06-15 23:52:16</r:created><r:modified>2024-03-27 23:31:58</r:modified></r:article></item><item><title>[ropensci-champions] rgeeExtra 0.1.0</title><author>csaybar@gmail.com (Cesar Aybar)</author><description>High-level API to process Google Earth Engine (GEE) raster
(ee.Image and ee.ImageCollection) and vector data (ee.Geometry,
ee.Feature, and ee.FeatureCollection). Popular Third-party GEE
algorithms are re-coded from Javascript and Python to R.</description><link>https://github.com/r-universe/ropensci-champions/actions/runs/25246191224</link><pubDate>Thu, 23 Nov 2023 14:17:14 GMT</pubDate><r:package>rgeeExtra</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://ropensci-champions.r-universe.dev</r:repository><r:upstream>https://github.com/r-earthengine/rgeeExtra</r:upstream><r:article><r:source>Aditional.Rmd</r:source><r:filename>Aditional.html</r:filename><r:title>Aditional</r:title><r:created>2023-11-22 23:29:23</r:created><r:modified>2023-11-22 23:29:23</r:modified></r:article><r:article><r:source>Feature.Rmd</r:source><r:filename>Feature.html</r:filename><r:title>Feature</r:title><r:created>2023-11-22 23:29:23</r:created><r:modified>2023-11-22 23:29:23</r:modified></r:article><r:article><r:source>FeatureCollection.Rmd</r:source><r:filename>FeatureCollection.html</r:filename><r:title>FeatureCollection</r:title><r:created>2023-11-22 23:29:23</r:created><r:modified>2023-11-22 23:29:23</r:modified></r:article><r:article><r:source>Features.Rmd</r:source><r:filename>Features.html</r:filename><r:title>Features</r:title><r:created>2023-08-18 10:52:23</r:created><r:modified>2023-11-22 23:29:23</r:modified></r:article><r:article><r:source>Image.Rmd</r:source><r:filename>Image.html</r:filename><r:title>Image</r:title><r:created>2023-11-22 23:29:23</r:created><r:modified>2023-11-22 23:29:23</r:modified></r:article><r:article><r:source>ImageCollection.Rmd</r:source><r:filename>ImageCollection.html</r:filename><r:title>ImageCollection</r:title><r:created>2023-11-22 23:29:23</r:created><r:modified>2023-11-22 23:29:23</r:modified></r:article><r:article><r:source>Introduction.Rmd</r:source><r:filename>Introduction.html</r:filename><r:title>Introduction</r:title><r:created>2023-06-18 12:09:10</r:created><r:modified>2023-08-18 10:52:23</r:modified></r:article></item></channel></rss>