A collection of tools that support data diagnosis, exploration, and transformation. Data diagnostics provides information and visualization of missing values, outliers, and unique and negative values to help you understand the distribution and quality of your data. Data exploration provides information and visualization of the descriptive statistics of univariate variables, normality tests and outliers, correlation of two variables, and the relationship between the target variable and predictor. Data transformation supports binning for categorizing continuous variables, imputes missing values and outliers, and resolves skewness. And it creates automated reports that support these three tasks.
Version: 0.6.3 Depends: R (≥ 3.2.0) Imports: dplyr (≥ 0.7.6), showtext (≥ 0.9-4), sysfonts (≥ 0.7.1), ggplot2 (≥ 3.0.0), grid, gridExtra, hrbrthemes (≥ 0.8.0), htmltools, kableExtra, knitr (≥ 1.22), methods, mice, pagedown (≥ 0.15), purrr, reactable, rlang, rmarkdown, rpart, shiny, tibble, tidyr, tidyselect, utils Suggests: DBI, classInt, dbplyr, forecast (≥ 8.3), Hmisc, partykit, ppsr, prettydoc, randomForest, RSQLite, ranger, stringi Published: 2024-02-07 DOI: 10.32614/CRAN.package.dlookr Author: Choonghyun Ryu [aut, cre] Maintainer: Choonghyun Ryu <choonghyun.ryu at gmail.com> BugReports: https://github.com/choonghyunryu/dlookr/issues License: GPL-2 URL: https://github.com/choonghyunryu/dlookr/, https://choonghyunryu.github.io/dlookr/ NeedsCompilation: no Citation: dlookr citation info Materials: NEWS CRAN checks: dlookr results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=dlookr to link to this page.
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