Package: cassowaryr 2.0.2

Harriet Mason

cassowaryr: Compute Scagnostics on Pairs of Numeric Variables in a Data Set

Computes a range of scatterplot diagnostics (scagnostics) on pairs of numerical variables in a data set. A range of scagnostics, including graph and association-based scagnostics described by Leland Wilkinson and Graham Wills (2008) <doi:10.1198/106186008X320465> and association-based scagnostics described by Katrin Grimm (2016,ISBN:978-3-8439-3092-5) can be computed. Summary and plotting functions are provided.

Authors:Harriet Mason [aut, cre], Stuart Lee [aut], Ursula Laa [aut], Dianne Cook [aut]

cassowaryr_2.0.2.tar.gz
cassowaryr_2.0.2.zip(r-4.5)cassowaryr_2.0.2.zip(r-4.4)cassowaryr_2.0.2.zip(r-4.3)
cassowaryr_2.0.2.tgz(r-4.4-any)cassowaryr_2.0.2.tgz(r-4.3-any)
cassowaryr_2.0.2.tar.gz(r-4.5-noble)cassowaryr_2.0.2.tar.gz(r-4.4-noble)
cassowaryr_2.0.2.tgz(r-4.4-emscripten)cassowaryr_2.0.2.tgz(r-4.3-emscripten)
cassowaryr.pdf |cassowaryr.html✨
cassowaryr/json (API)
NEWS

# Install 'cassowaryr' in R:

install.packages('cassowaryr', repos = c('https://numbats.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/numbats/cassowaryr/issues

Datasets:

anscombe_tidy - Data from Anscombe's famous example in tidy format
datasaurus_dozen - Datasaurus_dozen data
datasaurus_dozen_wide - Datasaurus_dozen data
features - Simulated data with special features
numbat - A toy data set with a numbat shape hidden among noise variables
pk - Parkinsons data from UCI machine learning archive

On CRAN:

data-science data-visualization eda high-dimensional-data multivariate

5.95 score 3 stars 1 packages 25 scripts 398 downloads 24 exports 57 dependencies

Last updated 2 months agofrom:0db436e47c. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 13 2024
R-4.5-win	OK	Oct 13 2024
R-4.5-linux	OK	Oct 13 2024
R-4.4-win	OK	Oct 13 2024
R-4.4-mac	OK	Oct 13 2024
R-4.3-win	OK	Oct 13 2024
R-4.3-mac	OK	Oct 13 2024

Exports:calc_scags calc_scags_wide draw_alphahull draw_convexhull draw_mst sc_clumpy sc_clumpy_r sc_clumpy2 sc_convex sc_dcor sc_monotonic sc_outlying sc_skewed sc_skinny sc_sparse sc_sparse2 sc_splines sc_striated sc_striated2 sc_stringy sc_striped scree top_pairs top_scags

Dependencies:alphahull boot cli colorspace cpp11 crayon deldir dplyr energy fansi farver generics ggplot2 glue gsl gtable hms igraph interp isoband labeling lattice lifecycle magrittr MASS Matrix mgcv munsell nlme pillar pkgconfig polyclip prettyunits progress R.methodsS3 R.oo R.utils R6 RColorBrewer Rcpp RcppEigen rlang scales sgeostat sp spatstat.data spatstat.geom spatstat.random spatstat.univar spatstat.utils splancs tibble tidyselect utf8 vctrs viridisLite withr

An introduction to the cassowaryr package

Rendered fromcassowaryr.Rmdusingknitr::rmarkdownon Oct 13 2024.

Last update: 2022-04-07
Started: 2021-09-16

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Data from Anscombe's famous example in tidy format	anscombe_tidy
Compute selected scagnostics on subsets	calc_scags
Compute scagnostics on all possible scatter plots for the given data	calc_scags_wide
datasaurus_dozen data	datasaurus_dozen datasaurus_dozen_wide
Drawing the alphahull	draw_alphahull
Drawing the Convex Hull	draw_convexhull
Drawing the MST	draw_mst
Simulated data with special features	features
A toy data set with a numbat shape hidden among noise variables	numbat
Parkinsons data from UCI machine learning archive	pk
Compute clumpy scagnostic measure using MST	sc_clumpy sc_clumpy.default sc_clumpy.igraph sc_clumpy.scree
Compute robust clumpy scagnostic measure using MST	sc_clumpy_r sc_clumpy_r.default sc_clumpy_r.igraph sc_clumpy_r.scree
Compute adjusted clumpy measure using MST	sc_clumpy2 sc_clumpy2.default sc_clumpy2.igraph sc_clumpy2.scree
Compute convex scagnostic measure	sc_convex sc_convex.default sc_convex.list sc_convex.scree
Distance correlation index.	sc_dcor
Measure of Spearman Correlation	sc_monotonic
Compute outlying scagnostic measure using MST	sc_outlying sc_outlying.default sc_outlying.igraph sc_outlying.scree
Compute skewed scagnostic measure using MST	sc_skewed sc_skewed.default sc_skewed.igraph sc_skewed.scree
Compute skinny scagnostic measure	sc_skinny sc_skinny.default sc_skinny.list sc_skinny.scree
Compute sparse scagnostic measure using MST	sc_sparse sc_sparse.default sc_sparse.igraph sc_sparse.scree
Compute adjusted sparse measure using the alpha hull	sc_sparse2 sc_sparse2.default sc_sparse2.list sc_sparse2.scree
Spline based index.	sc_splines
Compute striated scagnostic measure using MST	sc_striated sc_striated.default sc_striated.igraph sc_striated.scree
Compute angle adjusted striated measure using MST	sc_striated2 sc_striated2.default sc_striated2.igraph sc_striated2.scree
Compute stringy scagnostic measure using MST	sc_stringy sc_stringy.default sc_stringy.igraph sc_stringy.scree
Measure of Discreteness	sc_striped
Pre-processing to generate scagnostic measures	scree
Calculate the top scagnostic for each pair of variables	top_pairs
Calculate the top pair of variables or group for each scagnostic	top_scags