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dataProfilerR  

Automated Exploratory Data Analysis and Dataset Profiling
View on CRAN: Click here


Download and install dataProfilerR package within the R console
Install from CRAN:
install.packages("dataProfilerR")

Install from Github:
library("remotes")
install_github("cran/dataProfilerR")

Install by package version:
library("remotes")
install_version("dataProfilerR", "0.2.1")



Attach the package and use:
library("dataProfilerR")
Maintained by
Muhammad Farooqi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-24
Latest Update: 2026-06-24
Description:
Profiles a data frame with minimal input: column type inference, missing-value analysis, distributional summary statistics (including skewness and kurtosis), normality tests, outlier detection, correlation and categorical-association analysis, date-column profiling, grouped comparisons and an overall data-quality score, alongside a set of 'ggplot2' visualisations. A single entry point, profile_data(), returns a structured S3 object holding metadata, statistics, diagnostics and plots, with print(), summary() and plot() methods, and report() renders the whole profile to a self-contained HTML file. Statistical methods include the Shapiro-Wilk normality test as implemented by Royston (1995) <doi:10.2307/2986146> and the Anderson-Darling test following Stephens (1974) <doi:10.1080/01621459.1974.10480196>, with power comparisons of these tests in Yap and Sim (2011) <doi:10.1080/00949655.2010.520163>, and the categorical association measure of Cramer (1946, ISBN:9780691080048).
How to cite:
Muhammad Farooqi (2026). dataProfilerR: Automated Exploratory Data Analysis and Dataset Profiling. R package version 0.2.1, https://cran.r-project.org/web/packages/dataProfilerR. Accessed 14 Jul. 2026.
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