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selkamand/ggparallel
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--- output: github_document --- <!-- README.md is generated from README.Rmd. Please edit that file --> ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" ) ``` # ggparallel <!-- badges: start --> [](https://lifecycle.r-lib.org/articles/stages.html#experimental) [](https://CRAN.R-project.org/package=ggparallel) [](https://github.com/selkamand/ggparallel/actions/workflows/R-CMD-check.yaml) [](https://app.codecov.io/gh/selkamand/ggparallel) <!-- badges: end --> ggparallel makes it easy to produce parallel coordinate plots. ## Installation You can install the development version of ggparallel like so: ``` r if (!require("remotes")) install.packages("remotes") remotes::install_github("selkamand/ggparallel") ``` ## Quick Start ```{r quick_start} library(ggparallel) ggparallel(iris) ``` More complex datasets, for example the dry bean [dataset](https://archive.ics.uci.edu/dataset/602/dry+bean+dataset) from the UCI Machine learning Repository ```{r} drybeans <- read.csv(system.file(package = "ggparallel", "dry_beans.csv")) ggparallel(drybeans) ggparallel(drybeans, col_colour = "Class") ```
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