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ucimlrepo package

Package to easily import datasets from the UC Irvine Machine Learning Repository into scripts and notebooks.
Current Version: 0.0.7

Installation

In a Jupyter notebook, install with the command

!pip3 install -U ucimlrepo

Restart the kernel and import the module ucimlrepo.

Example Usage

from ucimlrepo import fetch_ucirepo, list_available_datasets

# check which datasets can be imported
list_available_datasets()

# import dataset
heart_disease = fetch_ucirepo(id=45)
# alternatively: fetch_ucirepo(name='Heart Disease')

# access data
X = heart_disease.data.features
y = heart_disease.data.targets
# train model e.g. sklearn.linear_model.LinearRegression().fit(X, y)

# access metadata
print(heart_disease.metadata.uci_id)
print(heart_disease.metadata.num_instances)
print(heart_disease.metadata.additional_info.summary)

# access variable info in tabular format
print(heart_disease.variables)

fetch_ucirepo

Loads a dataset from the UCI ML Repository, including the dataframes and metadata information.

Parameters

Provide either a dataset ID or name as keyword (named) arguments. Cannot accept both.

  • id: Dataset ID for UCI ML Repository
  • name: Dataset name, or substring of name

Returns

  • dataset
    • data: Contains dataset matrices as pandas dataframes
      • ids: Dataframe of ID columns
      • features: Dataframe of feature columns
      • targets: Dataframe of target columns
      • original: Dataframe consisting of all IDs, features, and targets
      • headers: List of all variable names/headers
    • metadata: Contains metadata information about the dataset
      • See Metadata section below for details
    • variables: Contains variable details presented in a tabular/dataframe format
      • name: Variable name
      • role: Whether the variable is an ID, feature, or target
      • type: Data type e.g. categorical, integer, continuous
      • demographic: Indicates whether the variable represents demographic data
      • description: Short description of variable
      • units: variable units for non-categorical data
      • missing_values: Whether there are missing values in the variable's column

list_available_datasets

Prints a list of datasets that can be imported via fetch_ucirepo

Parameters

  • filter: Optional keyword argument to filter available datasets based on a category
    • Valid filters: aim-ahead
  • search: Optional keyword argument to search datasets whose name contains the search query

Returns

none

Metadata

  • uci_id: Unique dataset identifier for UCI repository
  • name
  • abstract: Short description of dataset
  • area: Subject area e.g. life science, business
  • task: Associated machine learning tasks e.g. classification, regression
  • characteristics: Dataset types e.g. multivariate, sequential
  • num_instances: Number of rows or samples
  • num_features: Number of feature columns
  • feature_types: Data types of features
  • target_col: Name of target column(s)
  • index_col: Name of index column(s)
  • has_missing_values: Whether the dataset contains missing values
  • missing_values_symbol: Indicates what symbol represents the missing entries (if the dataset has missing values)
  • year_of_dataset_creation
  • dataset_doi: DOI registered for dataset that links to UCI repo dataset page
  • creators: List of dataset creator names
  • intro_paper: Information about dataset's published introductory paper
  • repository_url: Link to dataset webpage on the UCI repository
  • data_url: Link to raw data file
  • additional_info: Descriptive free text about dataset
    • summary: General summary
    • purpose: For what purpose was the dataset created?
    • funding: Who funded the creation of the dataset?
    • instances_represent: What do the instances in this dataset represent?
    • recommended_data_splits: Are there recommended data splits?
    • sensitive_data: Does the dataset contain data that might be considered sensitive in any way?
    • preprocessing_description: Was there any data preprocessing performed?
    • variable_info: Additional free text description for variables
    • citation: Citation Requests/Acknowledgements
  • external_url: URL to external dataset page. This field will only exist for linked datasets i.e. not hosted by UCI

Links