Package: cleaner 1.5.5

cleaner: Fast and Easy Data Cleaning

Data cleaning functions for classes logical, factor, numeric, character, currency and Date to make data cleaning fast and easy. Relying on very few dependencies, it provides smart guessing, but with user options to override anything if needed.

Authors:Matthijs S. Berends [aut, cre]

cleaner_1.5.5.tar.gz
cleaner_1.5.5.zip(r-4.7)cleaner_1.5.5.zip(r-4.6)cleaner_1.5.5.zip(r-4.5)
cleaner_1.5.5.tgz(r-4.6-any)cleaner_1.5.5.tgz(r-4.5-any)
cleaner_1.5.5.tar.gz(r-4.7-any)cleaner_1.5.5.tar.gz(r-4.6-any)
cleaner_1.5.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cleaner/json (API)

# Install 'cleaner' in R:

install.packages('cleaner', repos = c('https://msberends.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/msberends/cleaner/issues

Pkgdown/docs site:https://msberends.github.io

Datasets:

unclean - Example data that is not clean

On CRAN:

6.58 score 34 stars 9 packages 69 scripts 1.2k downloads 1 mentions 28 exports 14 dependencies

Last updated from:7dcfb33a37. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	140
source / vignettes	OK	184
linux-release-x86_64	OK	128
macos-release-arm64	OK	149
macos-oldrel-arm64	OK	114
windows-devel	OK	81
windows-release	OK	77
windows-oldrel	OK	77
wasm-release	OK	112

Exports:as.currency as.percentage clean clean_character clean_currency clean_Date clean_double clean_factor clean_integer clean_logical clean_numeric clean_percentage clean_POSIXct format_datetime format_names format_p_value freq freq.default header is.currency is.freq is.percentage na_replace percentage rdate regex_false regex_true top_freq

Dependencies:backports cli crayon evaluate glue highr knitr lifecycle pillar rlang utf8 vctrs xfun yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Clean column data to a class	clean clean.data.frame clean_character clean_currency clean_Date clean_double clean_factor clean_integer clean_logical clean_numeric clean_percentage clean_POSIXct
Transform to currency	as.currency currency format.currency is.currency print.currency
Readable date format to POSIX	format_datetime
Format names and values	format_names
Format p values (APA guideline)	format_p_value
Frequency table	freq freq.Date freq.default freq.factor freq.hms freq.matrix freq.numeric freq.table header is.freq print.freq top_freq
Replace NA values	na_replace na_replace.data.frame na_replace.Date na_replace.default na_replace.list na_replace.logical na_replace.matrix na_replace.numeric
Transform to percentage	as.percentage format.percentage is.percentage percentage print.percentage
Generate random dates	rdate
Regular expressions for 'TRUE' and 'FALSE'	regex_false regex_true regex_true_false
Example data that is not clean	unclean