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Automatically Create n-Dimensional Plots From Tabular Data
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selkamand/gg1d
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Warning
We strongly recommend that you migrate to theggEDA package, which provides aricher feature set, ongoing maintenance, and enhanced performance. Thegg1d package is no longer under active development and will onlyreceive essential bug-fixes.
Effortlessly visualize all columns in a data frame with verticallyaligned plots and automatic plot selection based on variable type. Plotsare fully interactive, and custom tooltips can be added.
A graphical user interface to all gg1d visualisations is available athttps://CCICB.github.io/featurepeeker/
Why 1 dimensional plots?
To understand trends in your data, especially correlative relationshipsbetween 2 or more features, it can be useful to densely stack visualrepresentations of each feature vertically, regardless of data type. Byunifying the
gg1d can be used for exploratory data analysis (EDA) or to producepublication quality graphics summarizing a dataset.
install.packages("gg1d")You can install the development version of gg1d fromGitHub with:
if (!require("remotes")) install.packages("remotes")remotes::install_github("selkamand/gg1d")
Or from R-universe with:
install.packages("gg1d",repos="https://ropensci.r-universe.dev")
For examples of interactive gg1d plots see thegg1dgallery
# Load librarylibrary(gg1d)# Read datapath_gg1d<- system.file("example.csv",package="gg1d")df<- read.csv(path_gg1d,header=TRUE,na.strings="")# Plot data, sort by Glassesgg1d(df,col_id="ID",col_sort="Glasses",interactive=FALSE,verbose=FALSE,options= gg1d_options(legend_nrow=2))
Customise colours by supplying a named list to thepalettes argument
gg1d(df,col_id="ID",col_sort="Glasses",palettes=list("EyeColour"= c(Brown="rosybrown4",Blue="steelblue",Green="seagreen" )),interactive=FALSE,verbose=FALSE,options= gg1d_options(legend_nrow=2))
For datasets with many observations and mostly numeric features,parallel coordinate plots may be more appropriate.
ggparallel(data=minibeans,col_colour="Class",order_columns_by="auto",interactive=FALSE)#> ℹ Ordering columns based on mutual information with [Class]
ggparallel(data=minibeans,col_colour="Class",highlight="DERMASON",order_columns_by="auto",interactive=FALSE )#> ℹ Ordering columns based on how well they differentiate 1 group from the rest [DERMASON] (based on mutual information)
ggparallel(data=minibeans,order_columns_by="auto",interactive=FALSE )#> ℹ To add colour to plot set `col_colour` to one of: Class#> ℹ Ordering columns to minimise crossings#> ℹ Choosing axis order via repetitive nearest neighbour with two-opt refinement
All types of contributions are encouraged and valued. See ourguide tocommunitycontributions fordifferent ways to help.
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Automatically Create n-Dimensional Plots From Tabular Data
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