join_all

Recursively join a list of data frames.

A set of tools that solves a common set of problems: you need
to break a big problem down into manageable pieces, operate on each
piece and then put all the pieces back together.  For example, you
might want to fit a model to each spatial location or time point in
your study, summarise data by panels or collapse high-dimensional
arrays to simpler summary statistics. The development of 'plyr' has
been generously supported by 'Becton Dickinson'.

Hadley Wickham

plyr

Tools for Splitting, Applying and Combining Data

join_all function

<dl><dt>dfs</dt>
<dd>A list of data frames.</dd>
<dt>by</dt>
<dd>character vector of variable names to join by. If omitted, will
match on all common variables.</dd>
<dt>type</dt>
<dd>type of join: left (default), right, inner or full. See
details for more information.</dd>
<dt>match</dt>
<dd>how should duplicate ids be matched? Either match just the
<code>"first"</code> matching row, or match <code>"all"</code> matching rows. Defaults
to <code>"all"</code> for compatibility with merge, but <code>"first"</code> is
significantly faster.</dd></dl>

Arguments

Recursively join a list of data frames. — join_all

<dl>

<dt>dfs</dt>
<dd>A list of data frames.</dd>


<dt>by</dt>
<dd>character vector of variable names to join by. If omitted, will
match on all common variables.</dd>


<dt>type</dt>
<dd>type of join: left (default), right, inner or full. See
details for more information.</dd>


<dt>match</dt>
<dd>how should duplicate ids be matched? Either match just the
<code>"first"</code> matching row, or match <code>"all"</code> matching rows. Defaults
to <code>"all"</code> for compatibility with merge, but <code>"first"</code> is
significantly faster.</dd>

</dl>

join_all: Recursively join a list of data frames.

Description

Usage

Arguments

Examples