tidyr v0.8.1

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Easily Tidy Data with 'spread()' and 'gather()' Functions

An evolution of 'reshape2'. It's designed specifically for data tidying (not general reshaping or aggregating) and works well with 'dplyr' data pipelines.

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tidyr

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Overview

The goal of tidyr is to help you create tidy data. Tidy data is data where:

  1. Each variable is in a column.
  2. Each observation is a row.
  3. Each value is a cell.

Tidy data describes a standard way of storing data that is used wherever possible throughout the tidyverse. If you ensure that your data is tidy, you’ll spend less timing fighting with the tools and more time working on your analysis.

Installation

# The easiest way to get tidyr is to install the whole tidyverse:
install.packages("tidyverse")

# Alternatively, install just tidyr:
install.packages("tidyr")

# Or the the development version from GitHub:
# install.packages("devtools")
devtools::install_github("tidyverse/tidyr")

Getting started

library(tidyr)

There are two fundamental verbs of data tidying:

  • gather() takes multiple columns, and gathers them into key-value pairs: it makes “wide” data longer.

  • spread(). takes two columns (key & value) and spreads in to multiple columns, it makes “long” data wider.

tidyr also provides separate() and extract() functions which makes it easier to pull apart a column that represents multiple variables. The complement to separate() is unite().

To get started, read the tidy data vignette (vignette("tidy-data")) and check out the demos, demo(package = "tidyr")).

tidyr replaces reshape2 (2010-2014) and reshape (2005-2010). Somewhat counterintuitively each iteration of the package has done less. tidyr is designed specifically for tidying data, not general reshaping (reshape2), or the general aggregation (reshape).

If you’d like to read more about data reshaping from a CS perspective, I’d recommend the following three papers:

To guide your reading, here’s translation between the terminology used in different places:

tidyr gather spread
reshape(2) melt cast
spreadsheets unpivot pivot
databases fold unfold

Functions in tidyr

Name Description
spread Spread a key-value pair across multiple columns.
%>% Pipe operator
replace_na Replace missing values
extract Extract one column into multiple columns.
deprecated-se Deprecated SE versions of main verbs
complete Complete a data frame with missing combinations of data.
drop_na Drop rows containing missing values
nest Nest repeated values in a list-variable.
gather Gather columns into key-value pairs.
table1 Example tabular representations
fill Fill in missing values.
expand Expand data frame to include all combinations of values
full_seq Create the full sequence of values in a vector.
extract_numeric Extract numeric component of variable.
smiths Some data about the Smith family.
tidyr-package tidyr: Easily Tidy Data with 'spread()' and 'gather()' Functions
separate Separate one column into multiple columns.
separate_rows Separate a collapsed column into multiple rows.
unite Unite multiple columns into one.
uncount "Uncount" a data frame
unnest Unnest a list column.
who World Health Organization TB data
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Vignettes of tidyr

Name
billboard.csv
pew.csv
preg.csv
preg2.csv
tb.csv
tidy-data.Rmd
weather.csv
No Results!

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Details

License MIT + file LICENSE
URL http://tidyr.tidyverse.org, https://github.com/tidyverse/tidyr
BugReports https://github.com/tidyverse/tidyr/issues
LinkingTo Rcpp
VignetteBuilder knitr
LazyData true
RoxygenNote 6.0.1
NeedsCompilation yes
Packaged 2018-05-09 14:59:50 UTC; hadley
Repository CRAN
Date/Publication 2018-05-18 11:17:55 UTC

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