Package: janitor 2.2.0.9000

janitor: Simple Tools for Examining and Cleaning Dirty Data

The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and explore duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness.

Authors:Sam Firke [aut, cre], Bill Denney [ctb], Chris Haid [ctb], Ryan Knight [ctb], Malte Grosser [ctb], Jonathan Zadra [ctb], Olivier Roy [ctb]

janitor_2.2.0.9000.tar.gz
janitor_2.2.0.9000.zip(r-4.5)janitor_2.2.0.9000.zip(r-4.4)janitor_2.2.0.9000.zip(r-4.3)
janitor_2.2.0.9000.tgz(r-4.4-any)janitor_2.2.0.9000.tgz(r-4.3-any)
janitor_2.2.0.9000.tar.gz(r-4.5-noble)janitor_2.2.0.9000.tar.gz(r-4.4-noble)
janitor_2.2.0.9000.tgz(r-4.4-emscripten)janitor_2.2.0.9000.tgz(r-4.3-emscripten)
janitor.pdf |janitor.html
janitor/json (API)
NEWS

# Install 'janitor' in R:
install.packages('janitor', repos = c('https://sfirke.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/sfirke/janitor/issues

On CRAN:

data-analysisdata-cleaningdata-sciencedirty-dataexcelpivot-tablesspsstabulationstidyverse

19.29 score 1.4k stars 215 packages 31k scripts 325k downloads 11 mentions 42 exports 25 dependencies

Last updated 2 days agofrom:74345dad8a. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-winNOTENov 19 2024
R-4.5-linuxNOTENov 19 2024
R-4.4-winNOTENov 19 2024
R-4.4-macNOTENov 19 2024
R-4.3-winOKNov 19 2024
R-4.3-macOKNov 19 2024

Exports:%>%add_totals_coladd_totals_rowadorn_crosstabadorn_nsadorn_pct_formattingadorn_percentagesadorn_roundingadorn_titleadorn_totalsas_tabylchisq.testclean_namescompare_df_colscompare_df_cols_sameconvert_to_dateconvert_to_datetimeconvert_to_NAcrosstabdescribe_classexcel_numeric_to_dateexcel_time_to_numericfind_headerfisher.testget_dupesget_one_to_onemake_clean_namespaste_skip_naremove_constantremove_emptyremove_empty_colsremove_empty_rowsround_half_upround_to_fractionrow_to_namessas_numeric_to_datesignif_half_upsingle_valuetabyltop_levelsuntabyluse_first_valid_of

Dependencies:clicpp11dplyrfansigenericsgluehmslifecyclelubridatemagrittrpillarpkgconfigpurrrR6rlangsnakecasestringistringrtibbletidyrtidyselecttimechangeutf8vctrswithr

Overview of janitor functions

Rendered fromjanitor.Rmdusingknitr::rmarkdownon Nov 19 2024.

Last update: 2023-06-14
Started: 2018-01-07

tabyls: a tidy, fully-featured approach to counting things

Rendered fromtabyls.Rmdusingknitr::rmarkdownon Nov 19 2024.

Last update: 2023-07-11
Started: 2017-10-11

Readme and manuals

Help Manual

Help pageTopics
Add underlying Ns to a tabyl displaying percentages.adorn_ns
Format a 'data.frame' of decimals as percentages.adorn_pct_formatting
Convert a data.frame of counts to percentages.adorn_percentages
Round the numeric columns in a data.frame.adorn_rounding
Add column name to the top of a two-way tabyl.adorn_title
Append a totals row and/or column to a data.frameadorn_totals
Add 'tabyl' attributes to a data.frameas_tabyl
Apply 'stats::chisq.test()' to a two-way tabylchisq.test chisq.test.default chisq.test.tabyl
Cleans names of an object (usually a data.frame).clean_names clean_names.default clean_names.sf clean_names.tbl_graph clean_names.tbl_lazy
Compare data frames columns before mergingcompare_df_cols
Do the the data.frames have the same columns & types?compare_df_cols_same
Parse dates from many formatsconvert_to_date convert_to_datetime
Describe the class(es) of an objectdescribe_class describe_class.default describe_class.factor
Convert dates encoded as serial numbers to Date class.excel_numeric_to_date
Convert a time that may be inconsistently or inconveniently formatted from Microsoft Excel to a numeric number of seconds between 0 and 86400.excel_time_to_numeric
Find the header row in a data.framefind_header
Apply 'stats::fisher.test()' to a two-way tabylfisher.test fisher.test.default fisher.test.tabyl
Get rows of a 'data.frame' with identical values for the specified variables.get_dupes
Find the list of columns that have a 1:1 mapping to each otherget_one_to_one
Cleans a vector of text, typically containing the names of an object.make_clean_names
Constant to help map from mu to umu_to_u
Like 'paste()', but missing values are omittedpaste_skip_na
Remove constant columns from a data.frame or matrix.remove_constant
Remove empty rows and/or columns from a data.frame or matrix.remove_empty
Round a numeric vector; halves will be rounded up, ala Microsoft Excel.round_half_up
Round to the nearest fraction of a specified denominator.round_to_fraction
Elevate a row to be the column names of a data.frame.row_to_names
Convert a SAS date, time or date/time to an R objectsas_numeric_to_date
Round a numeric vector to the specified number of significant digits; halves will be rounded up.signif_half_up
Ensure that a vector has only a single value throughout.single_value
Generate a frequency table (1-, 2-, or 3-way).tabyl tabyl.data.frame tabyl.default
Generate a frequency table of a factor grouped into top-n, bottom-n, and all other levels.top_levels
Remove 'tabyl' attributes from a data.frame.untabyl