correlationfunnel: Speed Up Exploratory Data Analysis (EDA) with the Correlation Funnel

Speeds up exploratory data analysis (EDA) by providing a succinct workflow and interactive visualization tools for understanding which features have relationships to target (response). Uses binary correlation analysis to determine relationship. Default correlation method is the Pearson method. Lian Duan, W Nick Street, Yanchi Liu, Songhua Xu, and Brook Wu (2014) <doi:10.1145/2637484>.

Version: 0.2.0
Depends: R (≥ 3.1)
Imports: ggplot2, rlang, recipes, magrittr, plotly, tibble, dplyr (≥ 1.0.0), tidyr (≥ 1.0.0), stats, utils, ggrepel, stringr, forcats, purrr, cli, crayon, rstudioapi
Suggests: scales, knitr, rmarkdown, covr, lubridate, testthat (≥ 2.1.0)
Published: 2020-06-09
Author: Matt Dancho [aut, cre]
Maintainer: Matt Dancho <mdancho at business-science.io>
BugReports: https://github.com/business-science/correlationfunnel/issues
License: MIT + file LICENSE
URL: https://github.com/business-science/correlationfunnel
NeedsCompilation: no
Materials: README NEWS
CRAN checks: correlationfunnel results

Documentation:

Reference manual: correlationfunnel.pdf
Vignettes: Introducing Correlation Funnel
Methodology, Key Considerations, and FAQs

Downloads:

Package source: correlationfunnel_0.2.0.tar.gz
Windows binaries: r-devel: correlationfunnel_0.2.0.zip, r-release: correlationfunnel_0.2.0.zip, r-oldrel: correlationfunnel_0.2.0.zip
macOS binaries: r-release (arm64): correlationfunnel_0.2.0.tgz, r-oldrel (arm64): correlationfunnel_0.2.0.tgz, r-release (x86_64): correlationfunnel_0.2.0.tgz
Old sources: correlationfunnel archive

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