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fix URLs and reknit vignettes
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README.md

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[![R-CMD-check](https://github.com/sfirke/janitor/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/sfirke/janitor/actions/workflows/R-CMD-check.yaml)
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[![Coverage
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Status](https://img.shields.io/codecov/c/github/sfirke/janitor/master.svg)](https://codecov.io/github/sfirke/janitor?branch=master)
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[![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://www.tidyverse.org/lifecycle/#stable)
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[![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
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[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version-ago/janitor)](https://cran.r-project.org/package=janitor)
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![!Monthly Downloads](https://cranlogs.r-pkg.org/badges/janitor)
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![!Downloads](https://cranlogs.r-pkg.org/badges/grand-total/janitor)
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A full description of each function, organized by topic, can be found in
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janitor’s [catalog of functions
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vignette](http://sfirke.github.io/janitor/articles/janitor.html). There
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vignette](https://sfirke.github.io/janitor/articles/janitor.html). There
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you will find functions not mentioned in this README, like
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`compare_df_cols()` which provides a summary of differences in column
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names and types when given a set of data.frames.
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``` r
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library(readxl); library(janitor); library(dplyr); library(here)
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roster_raw <- read_excel(here("dirty_data.xlsx")) # available at http://github.com/sfirke/janitor
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roster_raw <- read_excel(here("dirty_data.xlsx")) # available at https://github.com/sfirke/janitor
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glimpse(roster_raw)
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#> Rows: 14
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#> Columns: 11
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These modular adornments can be layered to reduce R’s deficit against
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Excel and SPSS when it comes to quick, informative counts. Learn more
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about `tabyl()` and the `adorn_` functions from the [tabyls
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vignette](http://sfirke.github.io/janitor/articles/tabyls.html).
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vignette](https://sfirke.github.io/janitor/articles/tabyls.html).
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## Contact me
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- let me know what you think on Mastodon:
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[@samfirke@a2mi.social](https://a2mi.social/@samfirke)
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- compose a friendly e-mail to:
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<img src = "http://samfirke.com/wp-content/uploads/2016/07/email_address_whitespace_top.png" alt = "samuel.firke AT gmail" width = "210"/>
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<img src = "https://samfirke.com/wp-content/uploads/2016/07/email_address_whitespace_top.png" alt = "samuel.firke AT gmail" width = "210"/>

index.Rmd

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[![Travis-CI Build Status](https://travis-ci.org/sfirke/janitor.svg?branch=master)](https://travis-ci.org/sfirke/janitor)
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[![Coverage Status](https://img.shields.io/codecov/c/github/sfirke/janitor/master.svg)](https://codecov.io/github/sfirke/janitor?branch=master)
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[![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://www.tidyverse.org/lifecycle/#stable)
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[![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
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[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version-ago/janitor)](https://cran.r-project.org/package=janitor)
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![!Monthly Downloads](https://cranlogs.r-pkg.org/badges/janitor)
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![!Downloads](https://cranlogs.r-pkg.org/badges/grand-total/janitor)

index.md

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Status](https://travis-ci.org/sfirke/janitor.svg?branch=master)](https://travis-ci.org/sfirke/janitor)
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[![Coverage
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Status](https://img.shields.io/codecov/c/github/sfirke/janitor/master.svg)](https://codecov.io/github/sfirke/janitor?branch=master)
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[![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://www.tidyverse.org/lifecycle/#stable)
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[![lifecycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
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[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version-ago/janitor)](https://cran.r-project.org/package=janitor)
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![!Monthly Downloads](https://cranlogs.r-pkg.org/badges/janitor)
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![!Downloads](https://cranlogs.r-pkg.org/badges/grand-total/janitor)
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The main janitor functions:
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- perfectly format data.frame column names;
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- create and format frequency tables of one, two, or three variables -
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think an improved `table()`; and
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- provide other tools for cleaning and examining data.frames.
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- perfectly format data.frame column names;
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- create and format frequency tables of one, two, or three variables -
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think an improved `table()`; and
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- provide other tools for cleaning and examining data.frames.
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The tabulate-and-report functions approximate popular features of SPSS
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and Microsoft Excel.
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You can install:
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- the most recent officially-released version from CRAN with
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- the most recent officially-released version from CRAN with
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``` r
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install.packages("janitor")
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```
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``` r
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install.packages("janitor")
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```
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- the latest development version from GitHub with
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- the latest development version from GitHub with
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``` r
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install.packages("devtools")
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devtools::install_github("sfirke/janitor")
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```
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``` r
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install.packages("devtools")
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devtools::install_github("sfirke/janitor")
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```
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## Using janitor
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A full description of each function, organized by topic, can be found in
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janitor’s [catalog of functions
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vignette](http://sfirke.github.io/janitor/articles/janitor.html). There
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vignette](https://sfirke.github.io/janitor/articles/janitor.html). There
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you will find functions not mentioned in this README, like
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`compare_df_cols()` which provides a summary of differences in column
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names and types when given a set of data.frames.
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Dirtiness includes:
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- A header at the top
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- Dreadful column names
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- Rows and columns containing Excel formatting but no data
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- Dates in two different formats in a single column (MM/DD/YYYY and
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numbers)
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- Values spread inconsistently over theCertificationcolumns
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- A header at the top
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- Dreadful column names
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- Rows and columns containing Excel formatting but no data
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- Dates in two different formats in a single column (MM/DD/YYYY and
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numbers)
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- Values spread inconsistently over the “Certification” columns
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Here’s that data after being read in to R:
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``` r
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library(readxl); library(janitor); library(dplyr); library(here)
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roster_raw <- read_excel(here("dirty_data.xlsx")) # available at http://github.com/sfirke/janitor
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roster_raw <- read_excel(here("dirty_data.xlsx")) # available at https://github.com/sfirke/janitor
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glimpse(roster_raw)
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#> Rows: 14
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#> Columns: 11
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`tabyl` can be called two ways:
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- On a vector, when tabulating a single variable:
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`tabyl(roster$subject)`
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- On a data.frame, specifying 1, 2, or 3 variable names to tabulate:
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`roster %>% tabyl(subject, employee_status)`.
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- Here the data.frame is passed in with the `%>%` pipe; this
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allows `tabyl` to be used in an analysis pipeline
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- On a vector, when tabulating a single variable:
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`tabyl(roster$subject)`
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- On a data.frame, specifying 1, 2, or 3 variable names to tabulate:
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`roster %>% tabyl(subject, employee_status)`.
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- Here the data.frame is passed in with the `%>%` pipe; this allows
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`tabyl` to be used in an analysis pipeline
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One variable:
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These modular adornments can be layered to reduce R’s deficit against
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Excel and SPSS when it comes to quick, informative counts. Learn more
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about `tabyl()` and the `adorn_` functions from the [tabyls
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vignette](http://sfirke.github.io/janitor/articles/tabyls.html).
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vignette](https://sfirke.github.io/janitor/articles/tabyls.html).
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## <i class="fa fa-bullhorn" aria-hidden="true"></i> Contact Me
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You are welcome to:
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- submit suggestions and report bugs:
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<https://github.com/sfirke/janitor/issues>
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- let me know what you think on Mastodon:
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[@samfirke@a2mi.social](https://a2mi.social/@samfirke)
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- compose a friendly e-mail to:
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<img src = "http://samfirke.com/wp-content/uploads/2016/07/email_address_whitespace_top.png" alt = "samuel.firke AT gmail" width = "210"/>
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- submit suggestions and report bugs:
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<https://github.com/sfirke/janitor/issues>
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- let me know what you think on Mastodon:
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[@samfirke@a2mi.social](https://a2mi.social/@samfirke)
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- compose a friendly e-mail to:
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<img src = "https://samfirke.com/wp-content/uploads/2016/07/email_address_whitespace_top.png" alt = "samuel.firke AT gmail" width = "210"/>

vignettes/janitor.Rmd

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title: "Overview of janitor functions"
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date: "`r Sys.Date()`"
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output:
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github_document:
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rmarkdown::github_document:
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toc: true
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toc_depth: 3
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vignette: >

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