Package {DataSum}

Type: Package
Title: Modern Data Summaries and Diagnostic Reports for Statistical Analysis
Version: 1.0.0
Description: Provides robust, NA-aware data summaries, variable diagnostics, normality decisions, missingness and outlier checks, and reproducible diagnostic report scaffolding for statistical analysis. DataSum is designed for researchers, professors, scientists, and analysts who need trustworthy first-pass insight into tabular data before modeling or publication.
License: GPL (≥ 3)
Encoding: UTF-8
RoxygenNote: 7.3.3
URL: https://github.com/Uzairkhan11w/DataSum, https://uzairkhan11w.github.io/DataSum/
BugReports: https://github.com/Uzairkhan11w/DataSum/issues
Depends: R (≥ 4.1.0)
Imports: nortest
Suggests: knitr, quarto, rmarkdown, shiny, testthat (≥ 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-13 18:47:22 UTC; runner
Author: Uzair Javid Khan [aut, cre], Immad Ahmad Shah [aut], Sukhdev Mishra [aut]
Maintainer: Uzair Javid Khan <uzairkhan11w@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-13 22:30:08 UTC

DataSum: Modern Data Summaries and Diagnostic Reports

Description

DataSum provides robust, NA-aware summaries, data profiles, normality diagnostics, outlier checks, reproducible report scaffolding, and an optional Shiny app for statistical data inspection.

See Also

summarize_vector(), summarize_data(), profile_data(), datasum_report(), run_datasum_app()

Create a DataSum Diagnostic Report

Description

Creates a self-contained Quarto source file containing dataset diagnostics, variable summaries, warnings, and formula definitions. Set render = TRUE to render the report through the optional quarto package.

Usage

datasum_report(
  data,
  path = NULL,
  format = c("qmd", "html", "pdf", "docx"),
  title = "DataSum Diagnostic Report",
  by = NULL,
  alpha = 0.05,
  digits = 3,
  render = FALSE
)

Arguments

data

A data frame or tibble.

path

Output path. When render = FALSE, this should usually end in .qmd. If omitted, a temporary .qmd file is created.

format

One of "qmd", "html", "pdf", or "docx".

title

Report title.

by

Optional grouping columns passed to profile_data().

alpha

Significance level for normality decisions.

digits

Optional number of digits used to round numeric output.

render

Logical; if TRUE, render the Quarto document. Rendering requires the optional quarto package and a working Quarto installation.

Value

The generated file path, invisibly.

Examples

report <- datasum_report(iris, render = FALSE)
file.exists(report)

Profile a Data Frame

Description

Builds a dataset-level profile containing variable summaries, dataset shape, missingness, duplicate-row counts, type counts, and warnings that deserve analyst attention.

Usage

profile_data(data, by = NULL, alpha = 0.05, digits = NULL)

Arguments

data

A data frame or tibble.

by

Optional grouping columns passed to summarize_data().

alpha

Significance level for normality decisions.

digits

Optional number of digits used to round numeric output.

Value

A datasum_profile list with dataset, summary, and warnings.

Examples

profile <- profile_data(iris)
profile$dataset

Launch the DataSum Shiny App

Description

Opens an interactive Shiny interface for uploading a CSV file, inspecting dataset diagnostics, visualizing a selected variable, and downloading a reproducible DataSum report source file.

Usage

run_datasum_app(data = NULL)

Arguments

data

Optional data frame used as the starting dataset. If omitted, the app starts with datasets::iris until a CSV is uploaded.

Value

A Shiny application object.

Examples

if (requireNamespace("shiny", quietly = TRUE)) {
  app <- run_datasum_app(iris)
}

Summarize a Data Frame

Description

Applies summarize_vector() to every column in a data frame. Optional grouped summaries are supported by passing one or more grouping column names to by.

Usage

summarize_data(data, by = NULL, alpha = 0.05, digits = NULL)

Arguments

data

A data frame or tibble.

by

Optional character vector of grouping columns.

alpha

Significance level for normality decisions.

digits

Optional number of digits used to round numeric output.

Value

A data.frame, one row per summarized variable and group.

Examples

summarize_data(iris)
summarize_data(iris, by = "Species")

Summarize a Single Vector

Description

Computes a one-row, NA-aware diagnostic summary for one vector. Numeric vectors receive robust and classical statistics, outlier counts, and a normality diagnostic. Non-numeric vectors receive safe type, missingness, uniqueness, and mode summaries.

Usage

summarize_vector(x, name = NA_character_, alpha = 0.05, digits = NULL)

Arguments

x

A vector.

name

Optional variable name to store in the variable column.

alpha

Significance level for the normality decision. Defaults to 0.05.

digits

Optional number of digits used to round numeric output. By default, numeric values are not rounded.

Value

A one-row data.frame with summary statistics and diagnostics.

Examples

summarize_vector(c(1, 2, 2, NA, 5), name = "score")
summarize_vector(factor(c("control", "treatment", "control")))