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plyr

plyr is a set of tools for a common set of problems: you need to split up a big data structure into homogeneous pieces, apply a function to each piece and then combine all the results back together. For example, you might want to:

fit the same model each patient subsets of a data frame
quickly calculate summary statistics for each group
perform group-wise transformations like scaling or standardising

It's already possible to do this with base R functions (like split and the apply family of functions), but plyr makes it all a bit easier with:

totally consistent names, arguments and outputs
convenient parallelisation through the foreach package
input from and output to data.frames, matrices and lists
progress bars to keep track of long running operations
built-in error recovery, and informative error messages
labels that are maintained across all transformations

Considerable effort has been put into making plyr fast and memory efficient, and in many cases plyr is as fast as, or faster than, the built-in equivalents.

A detailed introduction to plyr has been published in JSS: "The Split-Apply-Combine Strategy for Data Analysis", http://www.jstatsoft.org/v40/i01/. You can find out more at https://had.co.nz/plyr/, or track development at https://github.com/hadley/plyr. You can ask questions about plyr (and data manipulation in general) on the plyr mailing list. Sign up at https://groups.google.com/group/manipulatr.

Status

plyr is retired: this means only changes necessary to keep it on CRAN will be made. We recommend using dplyr (for data frames) or purrr (for lists) instead.

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Version

Install

install.packages('plyr')

Monthly Downloads

456,912

Version

1.8.9

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Repository

https://github.com/hadley/plyr

Homepage

http://had.co.nz/plyr

Maintainer

Last Published

October 2nd, 2023

Functions in plyr (1.8.9)

Split data frame, apply function, and return results in an array.

Column-wise function.

Descending order.

Yearly batting records for all major league baseball players

create_progress_bar

Create progress bar.

Split data frame, apply function, and return results in a data frame.

Count the number of occurences.

Capture current evaluation context.

Aggregate multiple functions into a single function.

Evaluate a quoted list of variables.

Split list, apply function, and discard results.

Check if a data frame is empty.

Compute a unique numeric id for each unique row in a data frame.

Split data frame, apply function, and discard results.

Number of dimensions.

Recursively join a list of data frames.

Determine if a vector is discrete.

Join keys. Given two data frames, create a unique key for each row.

Numeric id for a vector.

An indexed data frame.

Fail with specified value.

Split list, apply function, and return results in a list.

Split data frame, apply function, and return results in a list.

Join two data frames together.

Construct an immutable data frame.

Split iterator that returns values, not indices.

Experimental iterator based version of llply.

Call function with arguments in array or data frame, returning an array.

Is a formula? Checks if argument is a formula

Call function with arguments in array or data frame, discarding results.

An indexed array.

List to vector.

list_to_dataframe

List to data frame.

Split list, apply function, and return results in a data frame.

Split list, apply function, and return results in an array.

plyr-deprecated

Deprecated Functions in Package plyr

Monthly ozone measurements over Central America.

Call function with arguments in array or data frame, returning a data frame.

Call function with arguments in array or data frame, returning a list.

Graphical progress bar, powered by Tk.

Graphical progress bar, powered by Windows.

Compute names of quoted variables.

Print quoted variables.

plyr: the split-apply-combine paradigm for R.

Number of unique values.

Text progress bar.

Text progress bar with time.

Replace specified values with new values, in a vector or factor.

Extract matching rows of a data frame.

Mutate a data frame by adding new or replacing existing columns.

Toggle row names between explicit and implicit.

Quick data frame.

Replicate expression and return results in a list.

Round to multiple of any number.

Combine data.frames by row, filling in missing columns.

Null progress bar

Generate labels for split data frame.

Replicate expression and return results in a data frame.

Replicate expression and return results in a array.

rbind.fill.matrix

Bind matrices by row, and fill missing columns with NA.

Reduce dimensions.

Replicate expression and discard results.

Split an array by .margins.

Modify names by name, not position.

Quote variables to create a list of unevaluated expressions for later evaluation.

Replace specified values with new values, in a factor or character vector.

`Splat' arguments to a function.

Function that always returns true.

Vector aggregate.

Summarise a data frame.

Try, with default in case of error.

Take a subset along an arbitrary dimension

Split a data frame by variables.

Remove splitting variables from a data frame.

Apply with built in try. Uses compact, lapply and tryNULL

Convert input to quoted variables.

Split array, apply function, and return results in a data frame.

Split array, apply function, and return results in a list.

Dimension names.

Split array, apply function, and return results in an array.

Split array, apply function, and discard results.

as.data.frame.function

Make a function return a data frame.

Order a data frame by its colums.

Convert split list to regular list.