Bug fixes
diff --git a/pkgdown.yml b/pkgdown.yml
index 9609921..2ea782e 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,7 +2,7 @@ pandoc: 3.1.11
pkgdown: 2.1.0
pkgdown_sha: ~
articles: {}
-last_built: 2024-08-31T06:31Z
+last_built: 2024-08-31T06:50Z
urls:
reference: https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference
article: https://r-pkg.thecoatlessprofessor.com/ucimlrepo/articles
diff --git a/search.json b/search.json
index 829db7e..ff55274 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 ucimlrepo authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"James Joseph Balamuta. Author, maintainer, copyright holder. Philip Truong. Author, copyright holder.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Balamuta J, Truong P (2024). ucimlrepo: Explore UCI ML Repository Datasets. R package version 0.0.2, https://github.com/coatless-rpkg/ucimlrepo, https://archive.ics.uci.edu/, https://r-pkg.thecoatlessprofessor.com/ucimlrepo/.","code":"@Manual{, title = {ucimlrepo: Explore UCI ML Repository Datasets}, author = {James Joseph Balamuta and Philip Truong}, year = {2024}, note = {R package version 0.0.2, https://github.com/coatless-rpkg/ucimlrepo, https://archive.ics.uci.edu/}, url = {https://r-pkg.thecoatlessprofessor.com/ucimlrepo/}, }"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"ucimlrepo-","dir":"","previous_headings":"","what":"Explore UCI ML Repository Datasets","title":"Explore UCI ML Repository Datasets","text":"goal ucimlrepo download import data sets directly R UCI Machine Learning Repository. [!IMPORTANT] package unoffical port Python ucimlrepo package. [!NOTE] Want datasets alongside help documentation entry? Check {ucidata} R package! package provides small selection data sets UC Irvine Machine Learning Repository alongside help entries.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Explore UCI ML Repository Datasets","text":"can install development version ucimlrepo GitHub :","code":"# install.packages(\"remotes\") remotes::install_github(\"coatless-rpkg/ucimlrepo\")"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Explore UCI ML Repository Datasets","text":"use ucimlrepo, load package using: package now loaded, can download dataset using fetch_ucirepo() function use list_available_datasets() function view list available datasets.","code":"library(ucimlrepo)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"download-data","dir":"","previous_headings":"Usage","what":"Download data","title":"Explore UCI ML Repository Datasets","text":"example, download iris dataset, can use: many levels data returned. example, can extract original data frame containing iris dataset using: Alternatively, retrieve two data frames, one features one targets: can view first rows data frame: Alternatively, can also directly query using ID found using list_available_datasets() looking dataset UCI ML Repo website:","code":"# Fetch a dataset by name iris_by_name <- fetch_ucirepo(name = \"iris\") names(iris_by_name) #> [1] \"data\" \"metadata\" \"variables\" 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 iris_features <- iris_by_name$data$features iris_targets <- iris_by_name$data$targets 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 # Fetch a dataset by id iris_by_id <- fetch_ucirepo(id = 53)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"view-list-of-data-sets","dir":"","previous_headings":"Usage","what":"View list of data sets","title":"Explore UCI ML Repository Datasets","text":"can also view list data sets available download using list_available_datasets() function: [!NOTE] 600+ datasets UCI ML Repo available download using package. current list available datasets can viewed . like see specific dataset added, please submit comment issue ticket upstream repository.","code":"# List available datasets list_available_datasets()"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_fetch_response.html","id":null,"dir":"Reference","previous_headings":"","what":"Empty Fetch Response — empty_fetch_response","title":"Empty Fetch Response — empty_fetch_response","text":"Internal function create empty fetch response.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_fetch_response.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Empty Fetch Response — empty_fetch_response","text":"","code":"empty_fetch_response()"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_fetch_response.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Empty Fetch Response — empty_fetch_response","text":"list containing dataset metadata, dataframes, variable info properties.","code":""},{"path":[]},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_search_response.html","id":null,"dir":"Reference","previous_headings":"","what":"Empty Search Response — empty_search_response","title":"Empty Search Response — empty_search_response","text":"Internal function create empty search response.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_search_response.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Empty Search Response — empty_search_response","text":"","code":"empty_search_response()"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_search_response.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Empty Search Response — empty_search_response","text":"data frame three empty columns 'id', 'name', 'url'.","code":""},{"path":[]},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch UCI ML Repository Dataset — fetch_ucirepo","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"Loads dataset UCI ML Repository, including dataframes metadata information.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"","code":"fetch_ucirepo(name, id)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"name Character. Dataset name, substring name. id Integer. Dataset ID UCI ML Repository.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"list containing dataset metadata, dataframes, variable info properties. data: Contains dataset matrices pandas dataframes ids: Dataframe ID columns features: Dataframe feature columns targets: Dataframe target columns original: Dataframe consisting IDs, features, targets headers: List variable names/headers metadata: Contains metadata information dataset. uci_id: Unique dataset identifier UCI repository name: Name dataset UCI repository repository_url: Link dataset webpage UCI repository data_url: Link raw data file abstract: Short description dataset area: Subject area e.g. life science, business tasks: Associated machine learning tasks e.g. classification, regression characteristics: Dataset types e.g. multivariate, sequential num_instances: Number rows samples num_features: Number feature columns feature_types: Data types features target_col: Name target column(s) index_col: Name index column(s) has_missing_values: Whether dataset contains missing values missing_values_symbol: Indicates symbol represents missing entries (dataset missing values) year_of_dataset_creation: Year data set created dataset_doi: DOI registered dataset links UCI repo dataset page creators: List dataset creator names intro_paper: Information dataset's published introductory paper external_url: URL external dataset page. field exist linked datasets .e. hosted UCI additional_info: Descriptive free text dataset summary: General summary purpose: purpose dataset created? funded_by: funded creation dataset? instances_represent: instances dataset represent? recommended_data_splits: recommended data splits? sensitive_data: dataset contain data might considered sensitive way? preprocessing_description: data preprocessing performed? variable_info: Additional free text description variables citation: Citation Requests/Acknowledgements variables: Contains variable details presented tabular/dataframe format name: Variable name role: Whether variable ID, feature, target type: Data type e.g. categorical, integer, continuous demographic: Indicates whether variable represents demographic data description: Short description variable units: Variable units non-categorical data missing_values: Whether missing values variable's column","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"provide name id, .","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"","code":"# Access Data by Name iris_dl <- fetch_ucirepo(name = \"iris\") # Access original data iris_uci <- iris_dl$data$original # Access features and targets iris_features <- iris_dl$data$features iris_targets <- iris_dl$data$targets # Access Data by ID iris_dl <- fetch_ucirepo(id = 53)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":null,"dir":"Reference","previous_headings":"","what":"List Available Datasets from UCI ML Repository — list_available_datasets","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"Prints list datasets can imported via fetch_ucirepo function.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"","code":"list_available_datasets(filter, search, area)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"filter Character. Optional query filter available datasets based label. search Character. Optional query search available datasets name. area Character. Optional query filter available datasets based subject area.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"data frame containing list available datasets columns : id: Integer ID data set. name: Name Dataset url: Download location data set event search fails, data frame returned empty.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"","code":"list_available_datasets(search = \"iris\") #> ------------------------------------------------------------- #> The following datasets are available for search query \"iris\": #> ------------------------------------------------------------- #> name id #> Iris 53 #> list_available_datasets(area = \"social science\") #> ------------------------------------- #> The following datasets are available: #> For subject area: social science #> ------------------------------------- #> name id #> Adult 2 #> Balance Scale 12 #> Balloons 13 #> Census Income 20 #> Hayes-Roth 44 #> Nursery 76 #> Congressional Voting Records 105 #> US Census Data (1990) 116 #> Census-Income (KDD) 117 #> Statlog (German Credit Data) 144 #> Communities and Crime 183 #> Communities and Crime Unnormalized 211 #> Bike Sharing 275 #> Student Performance 320 #> Drug Consumption (Quantified) 373 #> Autism Screening Adult 426 #> Gender by Name 591 #> Predict Students' Dropout and Academic Success 697 #> Power Consumption of Tetouan City 849 #> Higher Education Students Performance Evaluation 856 #> list_available_datasets(filter = \"python\") # Required for now... #> -------------------------------------------- #> The following python datasets are available: #> -------------------------------------------- #> name #> Abalone #> Adult #> Annealing #> Audiology (Standardized) #> Auto MPG #> Automobile #> Balance Scale #> Balloons #> Breast Cancer #> Breast Cancer Wisconsin (Original) #> Breast Cancer Wisconsin (Prognostic) #> Breast Cancer Wisconsin (Diagnostic) #> Pittsburgh Bridges #> Car Evaluation #> Census Income #> Chess (King-Rook vs. King-Pawn) #> Chess (King-Rook vs. King) #> Connect-4 #> Credit Approval #> Japanese Credit Screening #> Computer Hardware #> Contraceptive Method Choice #> Covertype #> Cylinder Bands #> Dermatology #> Echocardiogram #> Ecoli #> Flags #> Glass Identification #> Haberman's Survival #> Hayes-Roth #> Heart Disease #> Hepatitis #> Horse Colic #> Image Segmentation #> Ionosphere #> Iris #> ISOLET #> Lenses #> Letter Recognition #> Liver Disorders #> Lung Cancer #> Lymphography #> Molecular Biology (Splice-junction Gene Sequences) #> MONK's Problems #> Mushroom #> Musk (Version 1) #> Musk (Version 2) #> Nursery #> Page Blocks Classification #> Optical Recognition of Handwritten Digits #> Pen-Based Recognition of Handwritten Digits #> Post-Operative Patient #> Primary Tumor #> Servo #> Shuttle Landing Control #> Solar Flare #> Soybean (Large) #> Soybean (Small) #> Challenger USA Space Shuttle O-Ring #> Spambase #> SPECT Heart #> SPECTF Heart #> Tic-Tac-Toe Endgame #> Congressional Voting Records #> Waveform Database Generator (Version 1) #> Wine #> Yeast #> Zoo #> US Census Data (1990) #> Census-Income (KDD) #> El Nino #> Statlog (Australian Credit Approval) #> Statlog (German Credit Data) #> Statlog (Heart) #> Statlog (Landsat Satellite) #> Statlog (Image Segmentation) #> Statlog (Shuttle) #> Statlog (Vehicle Silhouettes) #> Connectionist Bench (Sonar, Mines vs. Rocks) #> Cloud #> Poker Hand #> MAGIC Gamma Telescope #> Mammographic Mass #> Forest Fires #> Concrete Compressive Strength #> Ozone Level Detection #> Parkinsons #> Blood Transfusion Service Center #> Communities and Crime #> Acute Inflammations #> Wine Quality #> Parkinsons Telemonitoring #> Cardiotocography #> Steel Plates Faults #> Communities and Crime Unnormalized #> Vertebral Column #> Bank Marketing #> ILPD (Indian Liver Patient Dataset) #> Skin Segmentation #> Individual Household Electric Power Consumption #> Energy Efficiency #> Fertility #> ISTANBUL STOCK EXCHANGE #> User Knowledge Modeling #> EEG Eye State #> Banknote Authentication #> Gas Sensor Array Drift at Different Concentrations #> Bike Sharing #> Thoracic Surgery Data #> Airfoil Self-Noise #> Wholesale customers #> Combined Cycle Power Plant #> Diabetes 130-US Hospitals for Years 1999-2008 #> Tennis Major Tournament Match Statistics #> Dow Jones Index #> Student Performance #> Phishing Websites #> Diabetic Retinopathy Debrecen #> Online News Popularity #> Chronic Kidney Disease #> Mice Protein Expression #> Default of Credit Card Clients #> Online Retail #> Occupancy Detection #> Air Quality #> Polish Companies Bankruptcy #> Dota2 Games Results #> Facebook Metrics #> HTRU2 #> Drug Consumption (Quantified) #> Appliances Energy Prediction #> Website Phishing #> YouTube Spam Collection #> Beijing PM2.5 #> Cervical Cancer (Risk Factors) #> Stock Portfolio Performance #> Sales Transactions Weekly #> Daily Demand Forecasting Orders #> Autistic Spectrum Disorder Screening Data for Children #> Autism Screening Adult #> Absenteeism at work #> Breast Cancer Coimbra #> Drug Reviews (Druglib.com) #> Drug Reviews (Drugs.com) #> Superconductivty Data #> Student Academics Performance #> Online Shoppers Purchasing Intention Dataset #> Electrical Grid Stability Simulated Data #> Real Estate Valuation #> Travel Reviews #> Travel Review Ratings #> Facebook Live Sellers in Thailand #> Metro Interstate Traffic Volume #> Hepatitis C Virus (HCV) for Egyptian patients #> Heart Failure Clinical Records #> Early Stage Diabetes Risk Prediction #> Pedestrians in Traffic #> Cervical Cancer Behavior Risk #> Estimation of Obesity Levels Based On Eating Habits and Physical Condition #> Rice (Cammeo and Osmancik) #> Algerian Forest Fires #> Gas Turbine CO and NOx Emission Data Set #> Apartment for Rent Classified #> Seoul Bike Sharing Demand #> Iranian Churn #> Bone marrow transplant: children #> COVID-19 Surveillance #> HCV data #> Taiwanese Bankruptcy Prediction #> Myocardial infarction complications #> Student Performance on an Entrance Examination #> Gender by Name #> Productivity Prediction of Garment Employees #> AI4I 2020 Predictive Maintenance Dataset #> Dry Bean #> In-Vehicle Coupon Recommendation #> Predict Students' Dropout and Academic Success #> Auction Verification #> NATICUSdroid (Android Permissions) #> Toxicity #> DARWIN #> Accelerometer Gyro Mobile Phone #> Glioma Grading Clinical and Mutation Features #> Multivariate Gait Data #> Land Mines #> Single Elder Home Monitoring: Gas and Position #> Sepsis Survival Minimal Clinical Records #> Secondary Mushroom #> Power Consumption of Tetouan City #> Raisin #> Steel Industry Energy Consumption #> Higher Education Students Performance Evaluation #> Risk Factor Prediction of Chronic Kidney Disease #> Maternal Health Risk #> Room Occupancy Estimation #> Cirrhosis Patient Survival Prediction #> SUPPORT2 #> National Health and Nutrition Health Survey 2013-2014 (NHANES) Age Prediction Subset #> AIDS Clinical Trials Group Study 175 #> CDC Diabetes Health Indicators #> Recipe Reviews and User Feedback #> Forty Soybean Cultivars from Subsequent Harvests #> Differentiated Thyroid Cancer Recurrence #> Infrared Thermography Temperature #> National Poll on Healthy Aging (NPHA) #> Regensburg Pediatric Appendicitis #> RT-IoT2022 #> PhiUSIIL Phishing URL (Website) #> id #> 1 #> 2 #> 3 #> 8 #> 9 #> 10 #> 12 #> 13 #> 14 #> 15 #> 16 #> 17 #> 18 #> 19 #> 20 #> 22 #> 23 #> 26 #> 27 #> 28 #> 29 #> 30 #> 31 #> 32 #> 33 #> 38 #> 39 #> 40 #> 42 #> 43 #> 44 #> 45 #> 46 #> 47 #> 50 #> 52 #> 53 #> 54 #> 58 #> 59 #> 60 #> 62 #> 63 #> 69 #> 70 #> 73 #> 74 #> 75 #> 76 #> 78 #> 80 #> 81 #> 82 #> 83 #> 87 #> 88 #> 89 #> 90 #> 91 #> 92 #> 94 #> 95 #> 96 #> 101 #> 105 #> 107 #> 109 #> 110 #> 111 #> 116 #> 117 #> 122 #> 143 #> 144 #> 145 #> 146 #> 147 #> 148 #> 149 #> 151 #> 155 #> 158 #> 159 #> 161 #> 162 #> 165 #> 172 #> 174 #> 176 #> 183 #> 184 #> 186 #> 189 #> 193 #> 198 #> 211 #> 212 #> 222 #> 225 #> 229 #> 235 #> 242 #> 244 #> 247 #> 257 #> 264 #> 267 #> 270 #> 275 #> 277 #> 291 #> 292 #> 294 #> 296 #> 300 #> 312 #> 320 #> 327 #> 329 #> 332 #> 336 #> 342 #> 350 #> 352 #> 357 #> 360 #> 365 #> 367 #> 368 #> 372 #> 373 #> 374 #> 379 #> 380 #> 381 #> 383 #> 390 #> 396 #> 409 #> 419 #> 426 #> 445 #> 451 #> 461 #> 462 #> 464 #> 467 #> 468 #> 471 #> 477 #> 484 #> 485 #> 488 #> 492 #> 503 #> 519 #> 529 #> 536 #> 537 #> 544 #> 545 #> 547 #> 551 #> 555 #> 560 #> 563 #> 565 #> 567 #> 571 #> 572 #> 579 #> 582 #> 591 #> 597 #> 601 #> 602 #> 603 #> 697 #> 713 #> 722 #> 728 #> 732 #> 755 #> 759 #> 760 #> 763 #> 799 #> 827 #> 848 #> 849 #> 850 #> 851 #> 856 #> 857 #> 863 #> 864 #> 878 #> 880 #> 887 #> 890 #> 891 #> 911 #> 913 #> 915 #> 925 #> 936 #> 938 #> 942 #> 967 #>"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/ucimlrepo-package.html","id":null,"dir":"Reference","previous_headings":"","what":"ucimlrepo: Explore UCI ML Repository Datasets — ucimlrepo-package","title":"ucimlrepo: Explore UCI ML Repository Datasets — ucimlrepo-package","text":"Find import datasets University California Irvine Machine Learning (UCI ML) Repository R. Supports working data UCI ML repository inside R scripts, notebooks, 'Quarto'/'RMarkdown' documents. Access UCI ML repository directly https://archive.ics.uci.edu/.","code":""},{"path":[]},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/ucimlrepo-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"ucimlrepo: Explore UCI ML Repository Datasets — ucimlrepo-package","text":"Maintainer: James Joseph Balamuta james.balamuta@gmail.com (ORCID) [copyright holder] Authors: Philip Truong ucirepository@gmail.com [copyright holder]","code":""},{"path":[]},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/news/index.html","id":"features-0-0-2","dir":"Changelog","previous_headings":"","what":"Features","title":"ucimlrepo 0.0.2","text":"Improved graceful errors fetch_ucirepo() list_available_datasets() resources found/available. (#3, thanks Prof. Ripley!)","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/news/index.html","id":"bug-fixes-0-0-2","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"ucimlrepo 0.0.2","text":"Fixed internal subset issue fetch_ucirepo() metadata repository whitespace characters variable names. (#2)","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/news/index.html","id":"ucimlrepo-001","dir":"Changelog","previous_headings":"","what":"ucimlrepo 0.0.1","title":"ucimlrepo 0.0.1","text":"CRAN release: 2024-07-27","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/news/index.html","id":"features-0-0-1","dir":"Changelog","previous_headings":"","what":"Features","title":"ucimlrepo 0.0.1","text":"fetch_ucirepo(): Download dataset UCI ML Repository. list_available_datasets(): List available datasets UCI ML Repository.","code":""}]
+[{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 ucimlrepo authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"James Joseph Balamuta. Author, maintainer, copyright holder. Philip Truong. Author, copyright holder.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Balamuta J, Truong P (2024). ucimlrepo: Explore UCI ML Repository Datasets. R package version 0.0.2, https://github.com/coatless-rpkg/ucimlrepo, https://archive.ics.uci.edu/, https://r-pkg.thecoatlessprofessor.com/ucimlrepo/.","code":"@Manual{, title = {ucimlrepo: Explore UCI ML Repository Datasets}, author = {James Joseph Balamuta and Philip Truong}, year = {2024}, note = {R package version 0.0.2, https://github.com/coatless-rpkg/ucimlrepo, https://archive.ics.uci.edu/}, url = {https://r-pkg.thecoatlessprofessor.com/ucimlrepo/}, }"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"ucimlrepo-","dir":"","previous_headings":"","what":"Explore UCI ML Repository Datasets","title":"Explore UCI ML Repository Datasets","text":"goal ucimlrepo download import data sets directly R UCI Machine Learning Repository. [!IMPORTANT] package unoffical port Python ucimlrepo package. [!NOTE] Want datasets alongside help documentation entry? Check {ucidata} R package! package provides small selection data sets UC Irvine Machine Learning Repository alongside help entries.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Explore UCI ML Repository Datasets","text":"can install development version ucimlrepo GitHub :","code":"# install.packages(\"remotes\") remotes::install_github(\"coatless-rpkg/ucimlrepo\")"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Explore UCI ML Repository Datasets","text":"use ucimlrepo, load package using: package now loaded, can download dataset using fetch_ucirepo() function use list_available_datasets() function view list available datasets.","code":"library(ucimlrepo)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"download-data","dir":"","previous_headings":"Usage","what":"Download data","title":"Explore UCI ML Repository Datasets","text":"example, download iris dataset, can use: many levels data returned. example, can extract original data frame containing iris dataset using: Alternatively, retrieve two data frames, one features one targets: can view first rows data frame: Alternatively, can also directly query using ID found using list_available_datasets() looking dataset UCI ML Repo website:","code":"# Fetch a dataset by name iris_by_name <- fetch_ucirepo(name = \"iris\") names(iris_by_name) #> [1] \"data\" \"metadata\" \"variables\" 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 iris_features <- iris_by_name$data$features iris_targets <- iris_by_name$data$targets 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 # Fetch a dataset by id iris_by_id <- fetch_ucirepo(id = 53)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/index.html","id":"view-list-of-data-sets","dir":"","previous_headings":"Usage","what":"View list of data sets","title":"Explore UCI ML Repository Datasets","text":"can also view list data sets available download using list_available_datasets() function: [!NOTE] 600+ datasets UCI ML Repo available download using package. current list available datasets can viewed . like see specific dataset added, please submit comment issue ticket upstream repository.","code":"# List available datasets list_available_datasets()"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_fetch_response.html","id":null,"dir":"Reference","previous_headings":"","what":"Empty Fetch Response — empty_fetch_response","title":"Empty Fetch Response — empty_fetch_response","text":"Internal function create empty fetch response.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_fetch_response.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Empty Fetch Response — empty_fetch_response","text":"","code":"empty_fetch_response()"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_fetch_response.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Empty Fetch Response — empty_fetch_response","text":"list containing dataset metadata, dataframes, variable info properties.","code":""},{"path":[]},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_search_response.html","id":null,"dir":"Reference","previous_headings":"","what":"Empty Search Response — empty_search_response","title":"Empty Search Response — empty_search_response","text":"Internal function create empty search response.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_search_response.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Empty Search Response — empty_search_response","text":"","code":"empty_search_response()"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/empty_search_response.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Empty Search Response — empty_search_response","text":"data frame three empty columns 'id', 'name', 'url'.","code":""},{"path":[]},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch UCI ML Repository Dataset — fetch_ucirepo","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"Loads dataset UCI ML Repository, including dataframes metadata information.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"","code":"fetch_ucirepo(name, id)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"name Character. Dataset name, substring name. id Integer. Dataset ID UCI ML Repository.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"list containing dataset metadata, dataframes, variable info properties. data: Contains dataset matrices pandas dataframes ids: Dataframe ID columns features: Dataframe feature columns targets: Dataframe target columns original: Dataframe consisting IDs, features, targets headers: List variable names/headers metadata: Contains metadata information dataset. uci_id: Unique dataset identifier UCI repository name: Name dataset UCI repository repository_url: Link dataset webpage UCI repository data_url: Link raw data file abstract: Short description dataset area: Subject area e.g. life science, business tasks: Associated machine learning tasks e.g. classification, regression characteristics: Dataset types e.g. multivariate, sequential num_instances: Number rows samples num_features: Number feature columns feature_types: Data types features target_col: Name target column(s) index_col: Name index column(s) has_missing_values: Whether dataset contains missing values missing_values_symbol: Indicates symbol represents missing entries (dataset missing values) year_of_dataset_creation: Year data set created dataset_doi: DOI registered dataset links UCI repo dataset page creators: List dataset creator names intro_paper: Information dataset's published introductory paper external_url: URL external dataset page. field exist linked datasets .e. hosted UCI additional_info: Descriptive free text dataset summary: General summary purpose: purpose dataset created? funded_by: funded creation dataset? instances_represent: instances dataset represent? recommended_data_splits: recommended data splits? sensitive_data: dataset contain data might considered sensitive way? preprocessing_description: data preprocessing performed? variable_info: Additional free text description variables citation: Citation Requests/Acknowledgements variables: Contains variable details presented tabular/dataframe format name: Variable name role: Whether variable ID, feature, target type: Data type e.g. categorical, integer, continuous demographic: Indicates whether variable represents demographic data description: Short description variable units: Variable units non-categorical data missing_values: Whether missing values variable's column","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"provide name id, .","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/fetch_ucirepo.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch UCI ML Repository Dataset — fetch_ucirepo","text":"","code":"# Access Data by Name iris_dl <- fetch_ucirepo(name = \"iris\") # Access original data iris_uci <- iris_dl$data$original # Access features and targets iris_features <- iris_dl$data$features iris_targets <- iris_dl$data$targets # Access Data by ID iris_dl <- fetch_ucirepo(id = 53)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":null,"dir":"Reference","previous_headings":"","what":"List Available Datasets from UCI ML Repository — list_available_datasets","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"Prints list datasets can imported via fetch_ucirepo function.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"","code":"list_available_datasets(filter, search, area)"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"filter Character. Optional query filter available datasets based label. search Character. Optional query search available datasets name. area Character. Optional query filter available datasets based subject area.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"data frame containing list available datasets columns : id: Integer ID data set. name: Name Dataset url: Download location data set event search fails, data frame returned empty.","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/list_available_datasets.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List Available Datasets from UCI ML Repository — list_available_datasets","text":"","code":"list_available_datasets(search = \"iris\") #> ------------------------------------------------------------- #> The following datasets are available for search query \"iris\": #> ------------------------------------------------------------- #> name id #> Iris 53 #> list_available_datasets(area = \"social science\") #> ------------------------------------- #> The following datasets are available: #> For subject area: social science #> ------------------------------------- #> name id #> Adult 2 #> Balance Scale 12 #> Balloons 13 #> Census Income 20 #> Hayes-Roth 44 #> Nursery 76 #> Congressional Voting Records 105 #> US Census Data (1990) 116 #> Census-Income (KDD) 117 #> Statlog (German Credit Data) 144 #> Communities and Crime 183 #> Communities and Crime Unnormalized 211 #> Bike Sharing 275 #> Student Performance 320 #> Drug Consumption (Quantified) 373 #> Autism Screening Adult 426 #> Gender by Name 591 #> Predict Students' Dropout and Academic Success 697 #> Power Consumption of Tetouan City 849 #> Higher Education Students Performance Evaluation 856 #> list_available_datasets(filter = \"python\") # Required for now... #> -------------------------------------------- #> The following python datasets are available: #> -------------------------------------------- #> name #> Abalone #> Adult #> Annealing #> Audiology (Standardized) #> Auto MPG #> Automobile #> Balance Scale #> Balloons #> Breast Cancer #> Breast Cancer Wisconsin (Original) #> Breast Cancer Wisconsin (Prognostic) #> Breast Cancer Wisconsin (Diagnostic) #> Pittsburgh Bridges #> Car Evaluation #> Census Income #> Chess (King-Rook vs. King-Pawn) #> Chess (King-Rook vs. King) #> Connect-4 #> Credit Approval #> Japanese Credit Screening #> Computer Hardware #> Contraceptive Method Choice #> Covertype #> Cylinder Bands #> Dermatology #> Echocardiogram #> Ecoli #> Flags #> Glass Identification #> Haberman's Survival #> Hayes-Roth #> Heart Disease #> Hepatitis #> Horse Colic #> Image Segmentation #> Ionosphere #> Iris #> ISOLET #> Lenses #> Letter Recognition #> Liver Disorders #> Lung Cancer #> Lymphography #> Molecular Biology (Splice-junction Gene Sequences) #> MONK's Problems #> Mushroom #> Musk (Version 1) #> Musk (Version 2) #> Nursery #> Page Blocks Classification #> Optical Recognition of Handwritten Digits #> Pen-Based Recognition of Handwritten Digits #> Post-Operative Patient #> Primary Tumor #> Servo #> Shuttle Landing Control #> Solar Flare #> Soybean (Large) #> Soybean (Small) #> Challenger USA Space Shuttle O-Ring #> Spambase #> SPECT Heart #> SPECTF Heart #> Tic-Tac-Toe Endgame #> Congressional Voting Records #> Waveform Database Generator (Version 1) #> Wine #> Yeast #> Zoo #> US Census Data (1990) #> Census-Income (KDD) #> El Nino #> Statlog (Australian Credit Approval) #> Statlog (German Credit Data) #> Statlog (Heart) #> Statlog (Landsat Satellite) #> Statlog (Image Segmentation) #> Statlog (Shuttle) #> Statlog (Vehicle Silhouettes) #> Connectionist Bench (Sonar, Mines vs. Rocks) #> Cloud #> Poker Hand #> MAGIC Gamma Telescope #> Mammographic Mass #> Forest Fires #> Concrete Compressive Strength #> Ozone Level Detection #> Parkinsons #> Blood Transfusion Service Center #> Communities and Crime #> Acute Inflammations #> Wine Quality #> Parkinsons Telemonitoring #> Cardiotocography #> Steel Plates Faults #> Communities and Crime Unnormalized #> Vertebral Column #> Bank Marketing #> ILPD (Indian Liver Patient Dataset) #> Skin Segmentation #> Individual Household Electric Power Consumption #> Energy Efficiency #> Fertility #> ISTANBUL STOCK EXCHANGE #> User Knowledge Modeling #> EEG Eye State #> Banknote Authentication #> Gas Sensor Array Drift at Different Concentrations #> Bike Sharing #> Thoracic Surgery Data #> Airfoil Self-Noise #> Wholesale customers #> Combined Cycle Power Plant #> Diabetes 130-US Hospitals for Years 1999-2008 #> Tennis Major Tournament Match Statistics #> Dow Jones Index #> Student Performance #> Phishing Websites #> Diabetic Retinopathy Debrecen #> Online News Popularity #> Chronic Kidney Disease #> Mice Protein Expression #> Default of Credit Card Clients #> Online Retail #> Occupancy Detection #> Air Quality #> Polish Companies Bankruptcy #> Dota2 Games Results #> Facebook Metrics #> HTRU2 #> Drug Consumption (Quantified) #> Appliances Energy Prediction #> Website Phishing #> YouTube Spam Collection #> Beijing PM2.5 #> Cervical Cancer (Risk Factors) #> Stock Portfolio Performance #> Sales Transactions Weekly #> Daily Demand Forecasting Orders #> Autistic Spectrum Disorder Screening Data for Children #> Autism Screening Adult #> Absenteeism at work #> Breast Cancer Coimbra #> Drug Reviews (Druglib.com) #> Drug Reviews (Drugs.com) #> Superconductivty Data #> Student Academics Performance #> Online Shoppers Purchasing Intention Dataset #> Electrical Grid Stability Simulated Data #> Real Estate Valuation #> Travel Reviews #> Travel Review Ratings #> Facebook Live Sellers in Thailand #> Metro Interstate Traffic Volume #> Hepatitis C Virus (HCV) for Egyptian patients #> Heart Failure Clinical Records #> Early Stage Diabetes Risk Prediction #> Pedestrians in Traffic #> Cervical Cancer Behavior Risk #> Estimation of Obesity Levels Based On Eating Habits and Physical Condition #> Rice (Cammeo and Osmancik) #> Algerian Forest Fires #> Gas Turbine CO and NOx Emission Data Set #> Apartment for Rent Classified #> Seoul Bike Sharing Demand #> Iranian Churn #> Bone marrow transplant: children #> COVID-19 Surveillance #> HCV data #> Taiwanese Bankruptcy Prediction #> Myocardial infarction complications #> Student Performance on an Entrance Examination #> Gender by Name #> Productivity Prediction of Garment Employees #> AI4I 2020 Predictive Maintenance Dataset #> Dry Bean #> In-Vehicle Coupon Recommendation #> Predict Students' Dropout and Academic Success #> Auction Verification #> NATICUSdroid (Android Permissions) #> Toxicity #> DARWIN #> Accelerometer Gyro Mobile Phone #> Glioma Grading Clinical and Mutation Features #> Multivariate Gait Data #> Land Mines #> Single Elder Home Monitoring: Gas and Position #> Sepsis Survival Minimal Clinical Records #> Secondary Mushroom #> Power Consumption of Tetouan City #> Raisin #> Steel Industry Energy Consumption #> Higher Education Students Performance Evaluation #> Risk Factor Prediction of Chronic Kidney Disease #> Maternal Health Risk #> Room Occupancy Estimation #> Cirrhosis Patient Survival Prediction #> SUPPORT2 #> National Health and Nutrition Health Survey 2013-2014 (NHANES) Age Prediction Subset #> AIDS Clinical Trials Group Study 175 #> CDC Diabetes Health Indicators #> Recipe Reviews and User Feedback #> Forty Soybean Cultivars from Subsequent Harvests #> Differentiated Thyroid Cancer Recurrence #> Infrared Thermography Temperature #> National Poll on Healthy Aging (NPHA) #> Regensburg Pediatric Appendicitis #> RT-IoT2022 #> PhiUSIIL Phishing URL (Website) #> id #> 1 #> 2 #> 3 #> 8 #> 9 #> 10 #> 12 #> 13 #> 14 #> 15 #> 16 #> 17 #> 18 #> 19 #> 20 #> 22 #> 23 #> 26 #> 27 #> 28 #> 29 #> 30 #> 31 #> 32 #> 33 #> 38 #> 39 #> 40 #> 42 #> 43 #> 44 #> 45 #> 46 #> 47 #> 50 #> 52 #> 53 #> 54 #> 58 #> 59 #> 60 #> 62 #> 63 #> 69 #> 70 #> 73 #> 74 #> 75 #> 76 #> 78 #> 80 #> 81 #> 82 #> 83 #> 87 #> 88 #> 89 #> 90 #> 91 #> 92 #> 94 #> 95 #> 96 #> 101 #> 105 #> 107 #> 109 #> 110 #> 111 #> 116 #> 117 #> 122 #> 143 #> 144 #> 145 #> 146 #> 147 #> 148 #> 149 #> 151 #> 155 #> 158 #> 159 #> 161 #> 162 #> 165 #> 172 #> 174 #> 176 #> 183 #> 184 #> 186 #> 189 #> 193 #> 198 #> 211 #> 212 #> 222 #> 225 #> 229 #> 235 #> 242 #> 244 #> 247 #> 257 #> 264 #> 267 #> 270 #> 275 #> 277 #> 291 #> 292 #> 294 #> 296 #> 300 #> 312 #> 320 #> 327 #> 329 #> 332 #> 336 #> 342 #> 350 #> 352 #> 357 #> 360 #> 365 #> 367 #> 368 #> 372 #> 373 #> 374 #> 379 #> 380 #> 381 #> 383 #> 390 #> 396 #> 409 #> 419 #> 426 #> 445 #> 451 #> 461 #> 462 #> 464 #> 467 #> 468 #> 471 #> 477 #> 484 #> 485 #> 488 #> 492 #> 503 #> 519 #> 529 #> 536 #> 537 #> 544 #> 545 #> 547 #> 551 #> 555 #> 560 #> 563 #> 565 #> 567 #> 571 #> 572 #> 579 #> 582 #> 591 #> 597 #> 601 #> 602 #> 603 #> 697 #> 713 #> 722 #> 728 #> 732 #> 755 #> 759 #> 760 #> 763 #> 799 #> 827 #> 848 #> 849 #> 850 #> 851 #> 856 #> 857 #> 863 #> 864 #> 878 #> 880 #> 887 #> 890 #> 891 #> 911 #> 913 #> 915 #> 925 #> 936 #> 938 #> 942 #> 967 #>"},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/ucimlrepo-package.html","id":null,"dir":"Reference","previous_headings":"","what":"ucimlrepo: Explore UCI ML Repository Datasets — ucimlrepo-package","title":"ucimlrepo: Explore UCI ML Repository Datasets — ucimlrepo-package","text":"Find import datasets University California Irvine Machine Learning (UCI ML) Repository R. Supports working data UCI ML repository inside R scripts, notebooks, 'Quarto'/'RMarkdown' documents. Access UCI ML repository directly https://archive.ics.uci.edu/.","code":""},{"path":[]},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/reference/ucimlrepo-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"ucimlrepo: Explore UCI ML Repository Datasets — ucimlrepo-package","text":"Maintainer: James Joseph Balamuta james.balamuta@gmail.com (ORCID) [copyright holder] Authors: Philip Truong ucirepository@gmail.com [copyright holder]","code":""},{"path":[]},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/news/index.html","id":"features-0-0-2","dir":"Changelog","previous_headings":"","what":"Features","title":"ucimlrepo 0.0.2","text":"Improved graceful errors fetch_ucirepo() list_available_datasets() resources found/available. (#3, thanks Prof. Ripley!) Speed fetch_ucirepo() large data frames switching using base functionals instead growing vector loop sorting variable roles. (#6)","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/news/index.html","id":"bug-fixes-0-0-2","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"ucimlrepo 0.0.2","text":"Fixed internal subset issue fetch_ucirepo() metadata repository whitespace characters variable names. (#2)","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/news/index.html","id":"ucimlrepo-001","dir":"Changelog","previous_headings":"","what":"ucimlrepo 0.0.1","title":"ucimlrepo 0.0.1","text":"CRAN release: 2024-07-27","code":""},{"path":"https://r-pkg.thecoatlessprofessor.com/ucimlrepo/news/index.html","id":"features-0-0-1","dir":"Changelog","previous_headings":"","what":"Features","title":"ucimlrepo 0.0.1","text":"fetch_ucirepo(): Download dataset UCI ML Repository. list_available_datasets(): List available datasets UCI ML Repository.","code":""}]