README.md
In ucimlrepo: Explore UCI ML Repository Datasets

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.

You can install the development version of ucimlrepo from GitHub with:

# install.packages("remotes")
remotes::install_github("coatless-rpkg/ucimlrepo")

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.

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)

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.