Showing 119 of total 119 results (show query)

guangchuangyu

hexSticker:Create Hexagon Sticker in R

Helper functions for creating reproducible hexagon sticker purely in R.

Maintained by Guangchuang Yu. Last updated 2 months ago.

ggplot2hexagon-stickerlogostickersvisualization

11.0 match 769 stars 11.94 score 1.3k scripts 8 dependents

jgraux

DepLogo:Dependency Logo

Plots dependency logos from a set of aligned input sequences.

Maintained by Jan Grau. Last updated 1 years ago.

18.5 match 1 stars 2.41 score 26 scripts

nflverse

nflreadr:Download 'nflverse' Data

A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.

Maintained by Tan Ho. Last updated 4 months ago.

nflnflfastrnflversesports-data

1.8 match 66 stars 12.46 score 476 scripts 10 dependents

lcbc-uio

lcbcr:LCBC brand package

Functions and setups with brand styling and lab general setups.

Maintained by Athanasia Mo Mowinckel. Last updated 3 years ago.

6.9 match 3.00 score 2 scripts

ropensci

weatherOz:An API Client for Australian Weather and Climate Data Resources

Provides automated downloading, parsing and formatting of weather data for Australia through API endpoints provided by the Department of Primary Industries and Regional Development ('DPIRD') of Western Australia and by the Science and Technology Division of the Queensland Government's Department of Environment and Science ('DES'). As well as the Bureau of Meteorology ('BOM') of the Australian government precis and coastal forecasts, and downloading and importing radar and satellite imagery files. 'DPIRD' weather data are accessed through public 'APIs' provided by 'DPIRD', <https://www.agric.wa.gov.au/weather-api-20>, providing access to weather station data from the 'DPIRD' weather station network. Australia-wide weather data are based on data from the Australian Bureau of Meteorology ('BOM') data and accessed through 'SILO' (Scientific Information for Land Owners) Jeffrey et al. (2001) <doi:10.1016/S1364-8152(01)00008-1>. 'DPIRD' data are made available under a Creative Commons Attribution 3.0 Licence (CC BY 3.0 AU) license <https://creativecommons.org/licenses/by/3.0/au/deed.en>. SILO data are released under a Creative Commons Attribution 4.0 International licence (CC BY 4.0) <https://creativecommons.org/licenses/by/4.0/>. 'BOM' data are (c) Australian Government Bureau of Meteorology and released under a Creative Commons (CC) Attribution 3.0 licence or Public Access Licence ('PAL') as appropriate, see <http://www.bom.gov.au/other/copyright.shtml> for further details.

Maintained by Rodrigo Pires. Last updated 23 days ago.

dpirdbommeteorological-dataweather-forecastaustraliaweatherweather-datameteorologywestern-australiaaustralia-bureau-of-meteorologywestern-australia-agricultureaustralia-agricultureaustralia-climateaustralia-weatherapi-clientclimatedatarainfallweather-api

2.3 match 32 stars 8.54 score 40 scripts

m-py

anticlust:Subset Partitioning via Anticlustering

The method of anticlustering partitions a pool of elements into groups (i.e., anticlusters) with the goal of maximizing between-group similarity or within-group heterogeneity. The anticlustering approach thereby reverses the logic of cluster analysis that strives for high within-group homogeneity and clear separation between groups. Computationally, anticlustering is accomplished by maximizing instead of minimizing a clustering objective function, such as the intra-cluster variance (used in k-means clustering) or the sum of pairwise distances within clusters. The main function anticlustering() gives access to optimal and heuristic anticlustering methods described in Papenberg and Klau (2021; <doi:10.1037/met0000301>), Brusco et al. (2020; <doi:10.1111/bmsp.12186>), Papenberg (2024; <doi:10.1111/bmsp.12315>), and Papenberg et al. (2025; <doi:10.1101/2025.03.03.641320>). The optimal algorithms require that an integer linear programming solver is installed. This package will install 'lpSolve' (<https://cran.r-project.org/package=lpSolve>) as a default solver, but it is also possible to use the package 'Rglpk' (<https://cran.r-project.org/package=Rglpk>), which requires the GNU linear programming kit (<https://www.gnu.org/software/glpk/glpk.html>), the package 'Rsymphony' (<https://cran.r-project.org/package=Rsymphony>), which requires the SYMPHONY ILP solver (<https://github.com/coin-or/SYMPHONY>), or the commercial solver Gurobi, which provides its own R package that is not available via CRAN (<https://www.gurobi.com/downloads/>). 'Rglpk', 'Rsymphony', 'gurobi' and their system dependencies have to be manually installed by the user because they are only suggested dependencies. Full access to the bicriterion anticlustering method proposed by Brusco et al. (2020) is given via the function bicriterion_anticlustering(), while kplus_anticlustering() implements the full functionality of the k-plus anticlustering approach proposed by Papenberg (2024). Some other functions are available to solve classical clustering problems. The function balanced_clustering() applies a cluster analysis under size constraints, i.e., creates equal-sized clusters. The function matching() can be used for (unrestricted, bipartite, or K-partite) matching. The function wce() can be used optimally solve the (weighted) cluster editing problem, also known as correlation clustering, clique partitioning problem or transitivity clustering.

Maintained by Martin Papenberg. Last updated 1 days ago.

1.5 match 34 stars 9.25 score 60 scripts 2 dependents

bczernecki

thunder:Computation and Visualisation of Atmospheric Convective Parameters

Allow to compute and visualise convective parameters commonly used in the operational prediction of severe convective storms. Core algorithm is based on a highly optimized 'C++' code linked into 'R' via 'Rcpp'. Highly efficient engine allows to derive thermodynamic and kinematic parameters from large numerical datasets such as reanalyses or operational Numerical Weather Prediction models in a reasonable amount of time. Package has been developed since 2017 by research meteorologists specializing in severe thunderstorms. The most relevant methods used in the package based on the following publications Stipanuk (1973) <https://apps.dtic.mil/sti/pdfs/AD0769739.pdf>, McCann et al. (1994) <doi:10.1175/1520-0434(1994)009%3C0532:WNIFFM%3E2.0.CO;2>, Bunkers et al. (2000) <doi:10.1175/1520-0434(2000)015%3C0061:PSMUAN%3E2.0.CO;2>, Corfidi et al. (2003) <doi:10.1175/1520-0434(2003)018%3C0997:CPAMPF%3E2.0.CO;2>, Showalter (1953) <doi:10.1175/1520-0477-34.6.250>, Coffer et al. (2019) <doi:10.1175/WAF-D-19-0115.1>, Gropp and Davenport (2019) <doi:10.1175/WAF-D-17-0150.1>, Czernecki et al. (2019) <doi:10.1016/j.atmosres.2019.05.010>, Taszarek et al. (2020) <doi:10.1175/JCLI-D-20-0346.1>, Sherburn and Parker (2014) <doi:10.1175/WAF-D-13-00041.1>, Romanic et al. (2022) <doi:10.1016/j.wace.2022.100474>.

Maintained by Bartosz Czernecki. Last updated 12 months ago.

capecinconvective-parametersdownload-soundinghodographrawinsondesevere-weatherthundertornadocpp

2.1 match 45 stars 6.31 score 7 scripts

loelschlaeger

oeli:Utilities for Developing Data Science Software

Some general helper functions that I (and maybe others) find useful when developing data science software.

Maintained by Lennart Oelschläger. Last updated 4 months ago.

openblascpp

1.8 match 2 stars 5.42 score 1 scripts 4 dependents

lcbc-uio

noasr:NOAS convenience functions

Functions created to work well with LCBC's Nephew of All Spreadsheet data.

Maintained by Athanasia Mo Mowinckel. Last updated 4 years ago.

3.2 match 3.00 score 4 scripts

alexym1

fusionchartsR:Embedding FusionCharts in R

FusionCharts provides awesome and minimalist functions to make beautiful interactive charts <https://www.fusioncharts.com/>.

Maintained by Alex Yahiaoui Martinez. Last updated 3 months ago.

2.0 match 6 stars 4.40 score 42 scripts

jiaxiangbu

add2ggplot:Add to 'ggplot2'

Create 'ggplot2' themes and color palettes.

Maintained by Jiaxiang Li. Last updated 5 years ago.

ggplot-extensionggplot2-theme

2.0 match 4 stars 4.30 score 8 scripts

scholaempirica

reschola:The Schola Empirica Package

A collection of utilies, themes and templates for data analysis at Schola Empirica.

Maintained by Jan Netík. Last updated 5 months ago.

1.8 match 4 stars 4.83 score 14 scripts

carlosyanez

customthemes:custom theming for ggplot, for personal use

Collection of (ggplot) theming options for personal use.

Maintained by Carlos Yanez Santibanez. Last updated 3 years ago.

3.4 match 1 stars 1.70 score 1 scripts

txwri

twriTemplates:Templates for TWRI reports

Provides word and pdf Rmarkdown templates that meet TWRI branding guidance.

Maintained by Michael Schramm. Last updated 1 years ago.

ggplot2-themermarkdown

2.0 match 1.78 score 12 scripts