Package Ucimlrepo Reference Manual

ucimlrepo The goal of ucimlrepo is to download and import data sets directly into R from the UCI Machine Learning Repository. [!IMPORTANT] This package is an unoffical port of the Python ucimlrepo package. [!NOTE] Want to have datasets alongside a help documentation entry? Check out the {ucidata} R package! The package provides a small selection of data sets from the UC Irvine Machine Learning Repository alongside of help entries.

Installation You can install the development version of ucimlrepo from GitHub with: # install.packages("remotes") remotes::install_github("coatless-rpkg/ucimlrepo") Usage To use ucimlrepo , load the package using: library(ucimlrepo) With the package now loaded, we can download a dataset using the fetch_ucirepo() function or use the list_available_datasets() function to view a list of available datasets. Download data For example, to download the iris dataset, we can use: # Fetch a dataset by name iris_by_name <- fetch_ucirepo(name = "iris") names(iris_by_name) #> [1] "data" "metadata" "variables" There are many levels to the data returned.

For example, we can extract the original data frame containing the iris dataset using: iris_uci <- iris_by_name$data$original head(iris_uci) #> sepal length sepal width petal length petal width class #> 1 5.1 3.5 1.4 0.2 Iris-setosa #> 2 4.9 3.0 1.4 0.2 Iris-setosa #> 3 4.7 3.2 1.3 0.2 Iris-setosa #> 4 4.6 3.1 1.5 0.2 Iris-setosa #> 5 5.0 3.6 1.4 0.2 Iris-setosa #> 6 5.4 3.9 1.7 0.4 Iris-setosa Alternatively, we could retrieve two data frames, one for the features and one for the targets: iris_features <- iris_by_name$data$features iris_targets <- iris_by_name$data$targets We can then view the first few rows of each data frame: head(iris_features) #> sepal length sepal width petal length petal width #> 1 5.1 3.5 1.4 0.2 #> 2 4.9 3.0 1.4 0.2 #> 3 4.7 3.2 1.3 0.2 #> 4 4.6 3.1 1.5 0.2 #> 5 5.0 3.6 1.4 0.2 #> 6 5.4 3.9 1.7 0.4 head(iris_targets) #> class #> 1 Iris-setosa #> 2 Iris-setosa #> 3 Iris-setosa #> 4 Iris-setosa #> 5 Iris-setosa #> 6 Iris-setosa Alternatively, you can also directly query by using an ID found by using list_available_datasets() or by looking up the dataset on the UCI ML Repo website: # Fetch a dataset by id iris_by_id <- fetch_ucirepo(id = 53) View list of data sets We can also view a list of data sets available for download using the list_available_datasets() function: # List available datasets list_available_datasets() [!NOTE] Not all 600+ datasets on UCI ML Repo are available for download using the package.

The current list of available datasets can be viewed here. If you would like to see a specific dataset added, please submit a comment on an issue ticket in the upstream repository.

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