% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utilities.R
\name{search_data}
\alias{search_data}
\title{Search Datasets}
\usage{
search_data(...)
}
\arguments{
\item{...}{Filter expressions. Each argument is a comparison expression
evaluated against the dataset metadata. Supported columns:
\describe{
  \item{\code{n}}{Sample size (numeric). Operators: \code{==, >, <, >=, <=}.}
  \item{\code{p}}{Number of variables (numeric). Operators: \code{==, >, <, >=, <=}.}
  \item{\code{subject}}{Subject area (character). Case-insensitive partial match with \code{==}.
    Areas: Agriculture, Automotive, Biology, Biometrics, Botany, Chemistry, Climate,
    Criminology, Demographics, Digital media, Economics, Education, Energy,
    Engineering, Environment, Finance, Food science, Forestry, Genomics,
    Healthcare, Marine biology, Medical, Methodology, Public services,
    Socioeconomics, Sociology, Sports, Transportation, Zoology.}
  \item{\code{type}}{Symbolic format (character). Exact match with \code{==}.
    Types correspond to the dataset name suffix:
    \code{"int"} (interval), \code{"hist"} (histogram),
    \code{"mix"} (mixed), \code{"distr"} (distribution),
    \code{"its"} (interval time series), \code{"modal"} (modal),
    \code{"iGAP"} (interval in iGAP format).}
  \item{\code{task}}{Analytical tasks (character). Case-insensitive partial match with \code{==}.
    Tasks: Clustering, Classification, Regression, PCA, Descriptive statistics,
    Discriminant analysis, Visualization, Spatial analysis, Time series, Aggregation.}
  \item{\code{tag}}{Keywords (character). Case-insensitive partial match with \code{==}.
    Use \code{tag == "all"} to list all datasets.}
  \item{\code{book}}{Book reference short name (character). Case-insensitive partial match
    with \code{==}. Available books:
    \code{SDA_2006} (Billard & Diday, 2006),
    \code{CMD_2020} (Billard & Diday, 2020),
    \code{SODAS_2008} (Diday & Noirhomme-Fraiture, 2008).}
}}
}
\value{
A data frame with one row per matching dataset and the following
columns: \code{name}, \code{n}, \code{p}, \code{subject}, \code{type},
\code{task}, \code{tag}, \code{book}.
}
\description{
Search and filter the dataSDA dataset catalog by metadata
criteria including sample size, number of variables, subject area,
symbolic format, analytical tasks, keywords, and book reference.
}
\details{
For character columns (\code{subject}, \code{type}, \code{task}, \code{tag},
\code{book}), the \code{==} operator performs a case-insensitive substring
match (using \code{grepl}). The \code{type} column uses short suffix-based
labels that match the dataset name suffix (e.g., \code{type == "int"}
matches all \code{.int} datasets).

For numeric columns (\code{n}, \code{p}), standard comparison operators
are used with exact semantics.

When no arguments are provided, or when \code{tag == "all"} is used,
all datasets are returned.
}
\examples{
# List all datasets
search_data()

# Filter by symbolic format (suffix-based)
search_data(type == "hist")

# Filter by analytical task and size
search_data(task == "Regression", n > 10)

# Filter by book reference
search_data(book == "SDA_2006")

# Combine multiple filters
search_data(type == "int", task == "Clustering", subject == "Biology")

# Filter by size range
search_data(n >= 20, n <= 100, p < 10)

}
\references{
Billard, L. and Diday, E. (2006). \emph{Symbolic Data Analysis:
Conceptual Statistics and Data Mining}. Wiley, Chichester.

Billard, L. and Diday, E. (2020). \emph{Clustering Methodology for
Symbolic Data}. Wiley.

Diday, E. and Noirhomme-Fraiture, M. (Eds.) (2008). \emph{Symbolic Data
Analysis and the SODAS Software}. Wiley.
}
