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<br/>&bull;&nbsp;<a href="index.html">About Miller</a>
<br/>&bull;&nbsp;<a href="file-formats.html">File formats</a>
<br/>&bull;&nbsp;<a href="feature-comparison.html">Miller features in the context of the Unix toolkit</a>
<br/>&bull;&nbsp;<a href="record-heterogeneity.html">Record-heterogeneity</a>
<br/>&bull;&nbsp;<a href="reference.html"><b>Reference</b></a>
<br/>&bull;&nbsp;<a href="data-examples.html">Data examples</a>
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<br/>&bull;&nbsp;<a href="build.html">Compiling, portability, dependencies, and testing</a>
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<br/>&bull;&nbsp;<a href="whyc.html">Why C?</a>
<br/>&bull;&nbsp;<a href="etymology.html">Why call it Miller?</a>
<br/>&bull;&nbsp;<a href="originality.html">How original is Miller?</a>
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<br/>&bull;&nbsp;<a href="https://github.com/johnkerl/miller">GitHub repo</a>
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<br/> <br/> <br/> <br/> <br/> <br/> <br/> <br/> <br/> <br/> <br/> <br/>
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<center><b>Contents:</b></center>
&bull;&nbsp;<a href="#Command_overview">Command overview</a><br/>
&bull;&nbsp;<a href="#On-line_help">On-line help</a><br/>
&bull;&nbsp;<a href="#Data_types">Data types</a><br/>
&bull;&nbsp;<a href="#Null_data">Null data</a><br/>
&bull;&nbsp;<a href="#I/O_options">I/O options</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#Formats">Formats</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#Record/field/pair_separators">Record/field/pair separators</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#Number_formatting">Number formatting</a><br/>
&bull;&nbsp;<a href="#Data_transformations">Data transformations</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#bar">bar</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#cat">cat</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#check">check</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#count-distinct">count-distinct</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#cut">cut</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#filter">filter</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#grep">grep</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#group-by">group-by</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#group-like">group-like</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#having-fields">having-fields</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#head">head</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#histogram">histogram</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#join">join</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#label">label</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#put">put</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#regularize">regularize</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#rename">rename</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#reorder">reorder</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#sample">sample</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#sec2gmt">sec2gmt</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#sort">sort</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#stats1">stats1</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#stats2">stats2</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#step">step</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#tac">tac</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#tail">tail</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#top">top</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#uniq">uniq</a><br/>
&bull;&nbsp;<a href="#then-chaining">then-chaining</a><br/>
&bull;&nbsp;<a href="#Functions_for_filter_and_put">Functions for filter and put</a><br/>
&bull;&nbsp;<a href="#Operator_precedence">Operator precedence</a><br/>
&bull;&nbsp;<a href="#Operator_and_function_semantics">Operator and function semantics</a><br/>
&bull;&nbsp;<a href="#Arithmetic">Arithmetic</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#Input_scanning">Input scanning</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#Conversion_by_math_routines">Conversion by math routines</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#Conversion_by_arithmetic_operators">Conversion by arithmetic operators</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;&bull;&nbsp;<a href="#Pythonic_division">Pythonic division</a><br/>
&bull;&nbsp;<a href="#Regular_expressions">Regular expressions</a><br/>
</div>
<p/>
<a id="Command_overview"/><h1>Command overview</h1>
<p>
Whereas the Unix toolkit is made of the separate executables <tt>cat</tt>, <tt>tail</tt>, <tt>cut</tt>,
<tt>sort</tt>, etc., Miller has subcommands, invoked as follows:
<p/>
<div class="pokipanel">
<pre>
mlr tac *.dat
mlr cut --complement -f os_version *.dat
mlr sort -f hostname,uptime *.dat
</pre>
</div>
<p/>
<p/>These falls into categories as follows:
<table border=1>
<tr class="mlrbg">
<th>Commands </th>
<th>Description</th>
</tr>
<tr>
<td>
<a href="#cat"><tt>cat</tt></a>,
<a href="#cut"><tt>cut</tt></a>,
<a href="#head"><tt>head</tt></a>,
<a href="#sort"><tt>sort</tt></a>,
<a href="#tac"><tt>tac</tt></a>,
<a href="#tail"><tt>tail</tt></a>,
<a href="#top"><tt>top</tt></a>,
<a href="#uniq"><tt>uniq</tt></a>
</td>
<td> Analogs of their Unix-toolkit namesakes, discussed below as well as in
<a href="feature-comparison.html">Miller features in the context of the Unix toolkit</a> </td>
</tr>
<tr>
<td>
<a href="#filter"><tt>filter</tt></a>,
<a href="#put"><tt>put</tt></a>,
<a href="#step"><tt>step</tt></a>
</td>
<td> <tt>awk</tt>-like functionality </td>
</tr>
<tr>
<td>
<a href="#histogram"><tt>histogram</tt></a>,
<a href="#stats1"><tt>stats1</tt></a>,
<a href="#stats2"><tt>stats2</tt></a>
</td>
<td> Statistically oriented </td>
</tr>
<tr>
<td>
<a href="#group-by"><tt>group-by</tt></a>,
<a href="#group-like"><tt>group-like</tt></a>,
<a href="#having-fields"><tt>having-fields</tt></a>
</td>
<td> Particularly oriented toward <a href="record-heterogeneity.html">Record-heterogeneity</a>, although
all Miller commands can handle heterogeneous records
</tr>
<tr>
<td>
<a href="#count-distinct"><tt>count-distinct</tt></a>,
<a href="#label"><tt>label</tt></a>,
<a href="#regularize"><tt>rename</tt></a>,
<a href="#rename"><tt>rename</tt></a>,
<a href="#reorder"><tt>reorder</tt></a>
</td>
<td> These draw from other sources (see also <a href="originality.html">How original is Miller?</a>):
<a href="#count-distinct"><tt>count-distinct</tt></a> is SQL-ish, and
<a href="#rename"><tt>rename</tt></a> can be done by <tt>sed</tt> (which does it faster:
see <a href="performance.html">Performance</a>).
</td>
</tr>
</table>
<a id="On-line_help"/><h1>On-line help</h1>
<p/>Examples:<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --help
Usage: mlr [I/O options] {verb} [verb-dependent options ...] {zero or more file names}
Command-line-syntax examples:
mlr --csv --rs lf --fs tab cut -f hostname,uptime file1.tsv file2.tsv
mlr --csv cut -f hostname,uptime mydata.csv
mlr --csv filter '$status != "down" &amp;&amp; $upsec &gt;= 10000' *.csv
mlr --nidx put '$sum = $7 + 2.1*$8' *.dat
grep -v '^#' /etc/group | mlr --ifs : --nidx --opprint label group,pass,gid,member then sort -f group
mlr join -j account_id -f accounts.dat then group-by account_name balances.dat
mlr put '$attr = sub($attr, "([0-9]+)_([0-9]+)_.*", "\1:\2")' data/*
mlr stats1 -a min,mean,max,p10,p50,p90 -f flag,u,v data/*
mlr stats2 -a linreg-pca -f u,v -g shape data/*
Data-format examples:
DKVP: delimited key-value pairs (Miller default format)
+---------------------+
| apple=1,bat=2,cog=3 | Record 1: "apple" =&gt; "1", "bat" =&gt; "2", "cog" =&gt; "3"
| dish=7,egg=8,flint | Record 2: "dish" =&gt; "7", "egg" =&gt; "8", "3" =&gt; "flint"
+---------------------+
NIDX: implicitly numerically indexed (Unix-toolkit style)
+---------------------+
| the quick brown | Record 1: "1" =&gt; "the", "2" =&gt; "quick", "3" =&gt; "brown"
| fox jumped | Record 2: "1" =&gt; "fox", "2" =&gt; "jumped"
+---------------------+
CSV/CSV-lite: comma-separated values with separate header line
+---------------------+
| apple,bat,cog |
| 1,2,3 | Record 1: "apple =&gt; "1", "bat" =&gt; "2", "cog" =&gt; "3"
| 4,5,6 | Record 2: "apple" =&gt; "4", "bat" =&gt; "5", "cog" =&gt; "6"
+---------------------+
PPRINT: pretty-printed tabular
+---------------------+
| apple bat cog |
| 1 2 3 | Record 1: "apple =&gt; "1", "bat" =&gt; "2", "cog" =&gt; "3"
| 4 5 6 | Record 2: "apple" =&gt; "4", "bat" =&gt; "5", "cog" =&gt; "6"
+---------------------+
XTAB: pretty-printed transposed tabular
+---------------------+
| apple 1 | Record 1: "apple" =&gt; "1", "bat" =&gt; "2", "cog" =&gt; "3"
| bat 2 |
| cog 3 |
| |
| dish 7 | Record 2: "dish" =&gt; "7", "egg" =&gt; "8"
| egg 8 |
+---------------------+
Help options:
-h or --help Show this message.
--version Show the software version.
{verb name} --help Show verb-specific help.
--list-all-verbs or -l List only verb names.
--help-all-verbs Show help on all verbs.
Verbs:
bar cat check count-distinct cut filter grep group-by group-like
having-fields head histogram join label put regularize rename reorder sample
sec2gmt sort stats1 stats2 step tac tail top uniq
Functions for the filter and put verbs:
+ + - - * / // % ** | ^ &amp; ~ &lt;&lt; &gt;&gt; == != =~ !=~ &gt; &gt;= &lt; &lt;= &amp;&amp; || ^^ ! boolean
float fmtnum hexfmt int string . gsub strlen sub tolower toupper abs acos
acosh asin asinh atan atan2 atanh cbrt ceil cos cosh erf erfc exp expm1
floor invqnorm log log10 log1p logifit madd max mexp min mmul msub pow qnorm
round roundm sgn sin sinh sqrt tan tanh urand urand32 urandint dhms2fsec
dhms2sec fsec2dhms fsec2hms gmt2sec hms2fsec hms2sec sec2dhms sec2gmt
sec2hms strftime strptime systime
Please use "mlr --help-function {function name}" for function-specific help.
Please use "mlr --help-all-functions" or "mlr -f" for help on all functions.
Data-format options, for input, output, or both:
--idkvp --odkvp --dkvp Delimited key-value pairs, e.g "a=1,b=2"
(default)
--inidx --onidx --nidx Implicitly-integer-indexed fields
(Unix-toolkit style)
--icsv --ocsv --csv Comma-separated value (or tab-separated
with --fs tab, etc.)
--ipprint --opprint --pprint --right Pretty-printed tabular (produces no
output until all input is in)
--ixtab --oxtab --xtab --xvright Pretty-printed vertical-tabular
The --right option right-justifies all fields for PPRINT output format.
The --xvright option right-justifies values for XTAB format.
-p is a keystroke-saver for --nidx --fs space --repifs
Examples: --csv for CSV-formatted input and output; --idkvp --opprint for
DKVP-formatted input and pretty-printed output.
Separator options, for input, output, or both:
--rs --irs --ors Record separators, e.g. 'lf' or '\r\n'
--fs --ifs --ofs --repifs Field separators, e.g. comma
--ps --ips --ops Pair separators, e.g. equals sign
Notes:
* IPS/OPS are only used for DKVP and XTAB formats, since only in these formats
do key-value pairs appear juxtaposed.
* IRS/ORS are ignored for XTAB format. Nominally IFS and OFS are newlines;
XTAB records are separated by two or more consecutive IFS/OFS -- i.e.
a blank line.
* OFS must be single-character for PPRINT format. This is because it is used
with repetition for alignment; multi-character separators would make
alignment impossible.
* OPS may be multi-character for XTAB format, in which case alignment is
disabled.
* DKVP, NIDX, CSVLITE, PPRINT, and XTAB formats are intended to handle
platform-native text data. In particular, this means LF line-terminators
by default on Linux/OSX. You can use "--dkvp --rs crlf" for
CRLF-terminated DKVP files, and so on.
* CSV is intended to handle RFC-4180-compliant data. In particular, this means
it uses CRLF line-terminators by default. You can use "--csv --rs lf" for
Linux-native CSV files.
* You can specify separators in any of the following ways, shown by example:
- Type them out, quoting as necessary for shell escapes, e.g.
"--fs '|' --ips :"
- C-style escape sequences, e.g. "--rs '\r\n' --fs '\t'".
- To avoid backslashing, you can use any of the following names:
cr crcr newline lf lflf crlf crlfcrlf tab space comma pipe slash colon semicolon equals
* Default separators by format:
File format RS FS PS
dkvp \n , =
nidx \n space (N/A)
csv \r\n , (N/A)
csvlite \n , (N/A)
pprint \n space (N/A)
xtab (N/A) \n space
Relevant to CSV/CSV-lite input only:
--implicit-csv-header Use 1,2,3,... as field labels, rather than from line 1
of input files. Tip: combine with "label" to recreate
missing headers.
Double-quoting for CSV output:
--quote-all Wrap all fields in double quotes
--quote-none Do not wrap any fields in double quotes, even if they have
OFS or ORS in them
--quote-minimal Wrap fields in double quotes only if they have OFS or ORS
in them (default)
--quote-numeric Wrap fields in double quotes only if they have numbers
in them
Numerical formatting:
--ofmt {format} E.g. %.18lf, %.0lf. Please use sprintf-style codes for
double-precision. Applies to verbs which compute new
values, e.g. put, stats1, stats2. See also the fmtnum
function within mlr put (mlr --help-all-functions).
Defaults to %lf.
Other options:
--seed {n} with n of the form 12345678 or 0xcafefeed. For put/filter
urand()/urandint()/urand32().
Then-chaining:
Output of one verb may be chained as input to another using "then", e.g.
mlr stats1 -a min,mean,max -f flag,u,v -g color then sort -f color
For more information please see http://johnkerl.org/miller/doc and/or
http://github.com/johnkerl/miller. This is Miller version v3.0.0-almost.
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr sort --help
Usage: mlr sort {flags}
Flags:
-f {comma-separated field names} Lexical ascending
-n {comma-separated field names} Numerical ascending; nulls sort last
-nf {comma-separated field names} Numerical ascending; nulls sort last
-r {comma-separated field names} Lexical descending
-nr {comma-separated field names} Numerical descending; nulls sort first
Sorts records primarily by the first specified field, secondarily by the second
field, and so on. Any records not having all specified sort keys will appear
at the end of the output, in the order they were encountered, regardless of the
specified sort order.
Example:
mlr sort -f a,b -nr x,y,z
which is the same as:
mlr sort -f a -f b -nr x -nr y -nr z
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="Data_types"/><h1>Data types</h1>
<p/> Miller&rsquo;s input and output are all string-oriented: there is (as of
August 2015 anyway) no support for binary record packing. In this sense,
everything is a string in and out of Miller. During processing, field names
are always strings, even if they have names like "3"; field values are usually
strings. Field values&rsquo; ability to be interpreted as a non-string type
only has meaning when comparison or function operations are done on them. And
it is an error condition if Miller encounters non-numeric (or otherwise
mistyped) data in a field in which it has been asked to do numeric (or
otherwise type-specific) operations.
<p/> Field values are treated as numeric for the following:
<ul>
<li/> Numeric sort: <tt>mlr sort -n</tt>, <tt>mlr sort -nr</tt>.
<li/> Statistics: <tt>mlr histogram</tt>, <tt>mlr stats1</tt>, <tt>mlr stats2</tt>.
<li/> Cross-record arithmetic: <tt>mlr step</tt>.
</ul>
<p/>For <tt>mlr put</tt> and <tt>mlr filter</tt>:
<ul>
<li/> Miller&rsquo;s types for function processing are <b>null</b> (empty
string), <b>error</b>, <b>string</b>, <b>float</b> (double-precision),
<b>int</b> (64-bit signed), and <b>boolean</b>.
<li/> On input, string values representable as numbers, e.g. "3" or "3.1", are
treated as int or float, respectively. If a record has <tt>x=1,y=2</tt> then
<tt>mlr put '$z=$x+$y'</tt> will produce <tt>x=1,y=2,z=3</tt>, and <tt>mlr put
'$z=$x.$y'</tt> gives an error. To coerce back to string for processing, use
the <tt>string</tt> function: <tt>mlr put '$z=string($x).string($y)'</tt> will
produce <tt>x=1,y=2,z=12</tt>.
<li/> On input, string values representable as boolean (e.g. <tt>"true"</tt>,
<tt>"false"</tt>) are <i>not</i> automatically treated as boolean. (This is
because <tt>"true"</tt> and <tt>"false"</tt> are ordinary words, and auto
string-to-boolean on a column consisting of words would result in some strings
mixed with some booleans.) Use the <tt>boolean</tt> function to coerce: e.g.
giving the record <tt>x=1,y=2,w=false</tt> to <tt>mlr put '$z=($x&lt;$y) ||
boolean($w)'</tt>.
<li/> Functions take types as described in <tt>mlr --help-all-functions</tt>:
for example, <tt>log10</tt> takes float input and produces float output,
<tt>gmt2sec</tt> maps string to int, and <tt>sec2gmt</tt> maps int to string.
<li/> All math functions described in <tt>mlr --help-all-functions</tt> take
integer as well as float input.
</ul>
<!-- ================================================================ -->
<a id="Null_data"/><h1>Null data</h1>
<p/> One of Miller&rsquo;s key features is its support for <b>heterogeneous</b> data.
Accordingly, if you try to sort on field <tt>hostname</tt> when not all records in the data
stream <i>have</i> a field named <tt>hostname</tt>, it is not an error (although you could
pre-filter the data stream using <tt>mlr having-fields --at-least hostname then sort ...</tt>).
Rather, records lacking one or more sort keys are simply output contiguously by <tt>mlr sort</tt>.
<p/> Field values may also be null by being
specified with present key but empty value: e.g. sending <tt>x=,y=2</tt> to <tt>mlr put '$z=$x+$y'</tt>.
<p/>
Rules for null-handling:
<ul>
<li> Records with one or more null sort-field values sort after records with all sort-field values present:
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint cat data/sort-null.dat
a b
3 2
1 8
- 4
5 7
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint sort -n a data/sort-null.dat
a b
1 8
3 2
5 7
- 4
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint sort -nr a data/sort-null.dat
a b
- 4
5 7
3 2
1 8
</pre>
</div>
<p/>
<li> Functions which have one or more null arguments produce null output: e.g.
<p/>
<div class="pokipanel">
<pre>
$ echo 'x=2,y=3' | mlr put '$a=$x+$y'
x=2,y=3,a=5
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ echo 'x=,y=3' | mlr put '$a=$x+$y'
x=,y=3,a=
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ echo 'x=,y=3' | mlr put '$a=log($x);$b=log($y)'
x=,y=3,a=,b=1.098612
</pre>
</div>
<p/>
<li> The <tt>min</tt> and <tt>max</tt> functions are special: if one argument is non-null, it wins:
<p/>
<div class="pokipanel">
<pre>
$ echo 'x=,y=3' | mlr put '$a=min($x,$y);$b=max($x,$y)'
x=,y=3,a=3,b=3
</pre>
</div>
<p/>
</ul>
<!-- ================================================================ -->
<a id="I/O_options"/><h1>I/O options</h1>
<!-- ================================================================ -->
<a id="Formats"/><h2>Formats</h2>
<p/> Options:
<pre>
--dkvp --idkvp --odkvp
--nidx --inidx --onidx
--csv --icsv --ocsv
--csvlite --icsvlite --ocsvlite
--pprint --ipprint --ppprint --right
--xtab --ixtab --oxtab
</pre>
<p/> These are as discussed in <a href="file-formats.html">File formats</a>, with the exception of <tt>--right</tt>
which makes pretty-printed output right-aligned:
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint cat data/small
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint --right cat data/small
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td></tr></table>
<p/>Additional notes:
<ul>
<li/> Use <tt>--csv</tt>, <tt>--pprint</tt>, etc. when the input and output formats are the same.
<li/> Use <tt>--icsv --opprint</tt>, etc. when you want format conversion as part of what Miller does to your data.
<li/> DKVP (key-value-pair) format is the default for input and output. So,
<tt>--oxtab</tt> is the same as <tt>--idkvp --oxtab</tt>.
</ul>
<!-- ================================================================ -->
<a id="Record/field/pair_separators"/><h2>Record/field/pair separators</h2>
<p/> Miller has record separators <tt>IRS</tt> and <tt>ORS</tt>, field
separators <tt>IFS</tt> and <tt>OFS</tt>, and pair separators <tt>IPS</tt> and
<tt>OPS</tt>. For example, in the DKVP line <tt>a=1,b=2,c=3</tt>, the record
separator is newline, field separator is comma, and pair separator is the
equals sign. These are the default values.
<p/> Options:
<pre>
--rs --irs --ors
--fs --ifs --ofs --repifs
--ps --ips --ops
</pre>
<ul>
<li/> You can change a separator from input to output via e.g. <tt>--ifs =
--ofs :</tt>. Or, you can specify that the same separator is to be used for
input and output via e.g. <tt>--fs :</tt>.
<li/> The pair separator is only relevant to DKVP format.
<li/> Pretty-print and xtab formats ignore the separator arguments altogether.
<li/> The <tt>--repifs</tt> means that multiple successive occurrences of the
field separator count as one. For example, in CSV data we often signify nulls
by empty strings, e.g. <tt>2,9,,,,,6,5,4</tt>. On the other hand, if the field
separator is a space, it might be more natural to parse <tt>2 4 5</tt> the
same as <tt>2 4 5</tt>: <tt>--repifs --ifs ' '</tt> lets this happen. In fact,
the <tt>--ipprint</tt> option above is internally implemented in terms of
<tt>--repifs</tt>.
<li/> Just write out the desired separator, e.g. <tt>--ofs '|'</tt>. But you
may use the symbolic names <tt>newline</tt>, <tt>space</tt>, <tt>tab</tt>,
<tt>pipe</tt>, or <tt>semicolon</tt> if you like.
</ul>
<!-- ================================================================ -->
<a id="Number_formatting"/><h2>Number formatting</h2>
<p/> The command-line option <tt>--ofmt {format string}</tt> is the global
number format for commands which generate numeric output, e.g.
<tt>stats1</tt>, <tt>stats2</tt>, <tt>histogram</tt>, and <tt>step</tt>, as
well as <tt>mlr put</tt>. Examples:
<p/>
<div class="pokipanel">
<pre>
--ofmt %.9le --ofmt %.6lf --ofmt %.0lf
</pre>
</div>
<p/>
<p/> These are just C <tt>printf</tt> formats applied to double-precision
numbers. Please don&rsquo;t use <tt>%s</tt> or <tt>%d</tt>. Additionally, if
you use leading width (e.g. <tt>%18.12lf</tt>) then the output will contain
embedded whitespace, which may not be what you want if you pipe the output to
something else, particularly CSV. I use Miller&rsquo;s pretty-print format
(<tt>mlr --opprint</tt>) to column-align numerical data.
<p/> To apply formatting to a single field, overriding the global
<tt>ofmt</tt>, use <tt>fmtnum</tt> function within <tt>mlr put</tt>. For example:
<p/>
<div class="pokipanel">
<pre>
$ echo 'x=3.1,y=4.3' | mlr put '$z=fmtnum($x*$y,"%08lf")'
x=3.1,y=4.3,z=13.330000
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ echo 'x=0xffff,y=0xff' | mlr put '$z=fmtnum(int($x*$y),"%08llx")'
x=0xffff,y=0xff,z=00feff01
</pre>
</div>
<p/>
<p/>Input conversion from hexadecimal is done automatically on fields handled
by <tt>mlr put</tt> and <tt>mlr filter</tt> as long as the field value begins
with "0x". To apply output conversion to hexadecimal on a single column, you
may use <tt>fmtnum</tt>, or the keystroke-saving <tt>hexfmt</tt> function.
Example:
<p/>
<div class="pokipanel">
<pre>
$ echo 'x=0xffff,y=0xff' | mlr put '$z=hexfmt($x*$y)'
x=0xffff,y=0xff,z=0xfeff01
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="Data_transformations"/><h1>Data transformations</h1>
<!-- ================================================================ -->
<a id="bar"/><h2>bar</h2>
<p/> Cheesy bar-charting.
<p/>
<div class="pokipanel">
<pre>
$ mlr bar -h
Usage: mlr bar [options]
Replaces a numeric field with a number of asterisks, allowing for cheesy bar plots.
These align best with --opprint or --oxtab output format.
Options:
-f {a,b,c} Field names to convert to bars.
-c {character} Fill character: default '*'.
-x {character} Out-of-bounds character: default '#'.
-b {character} Blank character: default '.'.
--lo {lo} Lower-limit value for min-width bar: default '0.000000'.
--hi {hi} Upper-limit value for max-width bar: default '100.000000'.
-w {n} Bar-field width: default '40'.
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint cat data/small
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint bar --lo 0 --hi 1 -f x,y data/small
a b i x y
pan pan 1 *************........................... *****************************...........
eks pan 2 ******************************.......... ********************....................
wye wye 3 ********................................ *************...........................
eks wye 4 ***************......................... *****...................................
wye pan 5 **********************.................. **********************************......
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint bar --lo 0.4 --hi 0.6 -f x,y data/small
a b i x y
pan pan 1 #....................................... ***************************************#
eks pan 2 ***************************************# ************************................
wye wye 3 #....................................... #.......................................
eks wye 4 #....................................... #.......................................
wye pan 5 **********************************...... ***************************************#
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="cat"/><h2>cat</h2>
<p/> Most useful for format conversions (see
<a href="file-formats.html">File formats</a>), and concatenating multiple
same-schema CSV files to have the same header:
<p/>
<div class="pokipanel">
<pre>
$ mlr cat -h
Usage: mlr cat [options]
Passes input records directly to output. Most useful for format conversion.
Options:
-n Prepend field "n" to each record with record-counter starting at 1
-N {name} Prepend field {name} to each record with record-counter starting at 1
</pre>
</div>
<p/>
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ cat a.csv
a,b,c
1,2,3
4,5,6
</pre>
</div>
<p/>
</td> <td>
<p/>
<div class="pokipanel">
<pre>
$ cat b.csv
a,b,c
7,8,9
</pre>
</div>
<p/>
</td> <td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --csv cat a.csv b.csv
a,b,c
1,2,3
4,5,6
7,8,9
</pre>
</div>
<p/>
</td> <td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsv --oxtab cat a.csv b.csv
a 1
b 2
c 3
a 4
b 5
c 6
a 7
b 8
c 9
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="check"/><h2>check</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr check --help
Usage: mlr check
Consumes records without printing any output.
Useful for doing a well-formatted check on input data.
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="count-distinct"/><h2>count-distinct</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr count-distinct --help
Usage: mlr count-distinct [options]
-f {a,b,c} Field names for distinct count.
Prints number of records having distinct values for specified field names.
Same as uniq -c.
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr count-distinct -f a,b then sort -nr count data/medium
a=zee,b=wye,count=455
a=pan,b=eks,count=429
a=pan,b=pan,count=427
a=wye,b=hat,count=426
a=hat,b=wye,count=423
a=pan,b=hat,count=417
a=eks,b=hat,count=417
a=eks,b=eks,count=413
a=pan,b=zee,count=413
a=zee,b=hat,count=409
a=eks,b=wye,count=407
a=zee,b=zee,count=403
a=pan,b=wye,count=395
a=wye,b=pan,count=392
a=zee,b=eks,count=391
a=zee,b=pan,count=389
a=hat,b=eks,count=389
a=wye,b=eks,count=386
a=hat,b=zee,count=385
a=wye,b=zee,count=385
a=hat,b=hat,count=381
a=wye,b=wye,count=377
a=eks,b=pan,count=371
a=hat,b=pan,count=363
a=eks,b=zee,count=357
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="cut"/><h2>cut</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr cut --help
Usage: mlr cut [options]
Passes through input records with specified fields included/excluded.
-f {a,b,c} Field names to include for cut.
-o Retain fields in the order specified here in the argument list.
Default is to retain them in the order found in the input data.
-x|--complement Exclude, rather than include, field names specified by -f.
-r Treat field names as regular expressions. "ab", "a.*b" will
match any field name containing the substring "ab" or matching
"a.*b", respectively; anchors of the form "^ab$", "^a.*b$" may
be used. The -o flag is ignored when -r is present.
Examples:
mlr cut -f hostname,status
mlr cut -x -f hostname,status
mlr cut -r -f '^status$,sda[0-9]'
mlr cut -r -f '^status$,"sda[0-9]"'
mlr cut -r -f '^status$,"sda[0-9]"i' (this is case-insensitive)
</pre>
</div>
<p/>
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint cat data/small
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint cut -f y,x,i data/small
i x y
1 0.3467901443380824 0.7268028627434533
2 0.7586799647899636 0.5221511083334797
3 0.20460330576630303 0.33831852551664776
4 0.38139939387114097 0.13418874328430463
5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ echo 'a=1,b=2,c=3' | mlr cut -f b,c,a
a=1,b=2,c=3
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ echo 'a=1,b=2,c=3' | mlr cut -o -f b,c,a
b=2,c=3,a=1
</pre>
</div>
<p/>
</td></tr></table>
<p/>
<!-- ================================================================ -->
<a id="filter"/><h2>filter</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr filter --help
Usage: mlr filter [-v] [-x] [-s|-f] {expression}
Prints records for which {expression} evaluates to true.
-x: Prints records for which {expression} evaluates to false.
-v: First prints the AST (abstract syntax tree) for the expression, which gives
full transparency on the precedence and associativity rules of Miller's
grammar.
-s: Keeps field values, or literals in the expression, as strings with no type
inference to int or float.
-f: Keeps field values, or literals in the expression, as strings or floats
with no inference to int.
Please use a dollar sign for field names and double-quotes for string
literals. Miller built-in variables are NF NR FNR FILENUM FILENAME PI E.
Examples:
mlr filter 'log10($count) &gt; 4.0'
mlr filter 'FNR == 2 (second record in each file)'
mlr filter 'urand() &lt; 0.001' (subsampling)
mlr filter '$color != "blue" &amp;&amp; $value &gt; 4.2'
mlr filter '($x&lt;.5 &amp;&amp; $y&lt;.5) || ($x&gt;.5 &amp;&amp; $y&gt;.5)'
mlr filter '($name =~ "^sys.*east$") || ($name =~ "^dev.[0-9]+"i)'
Please see http://johnkerl.org/miller/doc/reference.html for more information
including function list. Or "mlr -f". Please also also "mlr grep" which is
useful when you don't yet know which field name(s) you're looking for.
</pre>
</div>
<p/>
<p/>Field names must be specified using a <tt>$</tt> in <tt>filter</tt> and
<a href="#put"><tt>put</tt></a> expressions, even though they don&rsquo;t appear in the data
stream. For integer-indexed data, this looks like <tt>awk</tt>&rsquo;s
<tt>$1,$2,$3</tt>. Likewise, enclose string literals in double quotes in
<tt>filter</tt> expressions even though they don&rsquo;t appear in file data.
In particular, <tt>mlr filter '$x=="abc"'</tt> passes through the record
<tt>x=abc</tt>.
<p/>The <tt>filter</tt> command supports the same built-in variables as for
<a href="#put"><tt>put</tt></a>, all <tt>awk</tt>-inspired: <tt>NF</tt>,
<tt>NR</tt>, <tt>FNR</tt>, <tt>FILENUM</tt>, and <tt>FILENAME</tt>. This
selects the 2nd record from each matching file:
<p/>
<div class="pokipanel">
<pre>
$ mlr filter 'FNR == 2' data/small*
a=eks,b=pan,i=2,x=0.7586799647899636,y=0.5221511083334797
1=pan,2=pan,3=1,4=0.3467901443380824,5=0.7268028627434533
a=wye,b=eks,i=10000,x=0.734806020620654365,y=0.884788571337605134
</pre>
</div>
<p/>
<p/>Expressions may be arbitrarily complex:
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint filter '$a == "pan" || $b == "wye"' data/small
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
</pre>
</div>
<p/>
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint filter '($x &gt; 0.5 &amp;&amp; $y &gt; 0.5) || ($x &lt; 0.5 &amp;&amp; $y &lt; 0.5)' then stats2 -a corr -f x,y data/medium
x_y_corr
0.756439
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint filter '($x &gt; 0.5 &amp;&amp; $y &lt; 0.5) || ($x &lt; 0.5 &amp;&amp; $y &gt; 0.5)' then stats2 -a corr -f x,y data/medium
x_y_corr
-0.747994
</pre>
</div>
<p/>
</td></tr></table>
Newlines within the expression are ignored, which can help increase legibility of complex expressions:
<p/>
<div class="pokipanel">
<pre>
mlr --opprint filter '
($x &gt; 0.5 &amp;&amp; $y &lt; 0.5)
||
($x &lt; 0.5 &amp;&amp; $y &gt; 0.5)' \
then stats2 -a corr -f x,y data/medium
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="grep"/><h2>grep</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr grep -h
Usage: mlr grep [options] {regular expression}
Passes through records which match {regex}.
Options:
-i Use case-insensitive search.
-v Invert: pass through records which do not match the regex.
Note that "mlr filter" is more powerful, but requires you to know field names.
By contrast, "mlr grep" allows you to regex-match the entire record. It does
this by formatting each record in memory as DKVP, using command-line-specified
ORS/OFS/OPS, and matching the resulting line against the regex specified
here. In particular, the regex is not applied to the input stream: if you
have CSV with header line "x,y,z" and data line "1,2,3" then the regex will
be matched, not against either of these lines, but against the DKVP line
"x=1,y=2,z=3". Furthermore, not all the options to system grep are supported,
and this command is intended to be merely a keystroke-saver. To get all the
features of system grep, you can do
"mlr --odkvp ... | grep ... | mlr --idkvp ..."
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="group-by"/><h2>group-by</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr group-by --help
Usage: mlr group-by {comma-separated field names}
Outputs records in batches having identical values at specified field names.
</pre>
</div>
<p/>
<p/>This is similar to <tt>sort</tt> but with less work. Namely, Miller&rsquo;s
sort has three steps: read through the data and append linked lists of records,
one for each unique combination of the key-field values; after all records
are read, sort the key-field values; then print each record-list. The group-by
operation simply omits the middle sort. An example should make this more
clear.
<table><tr> <td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint group-by a data/small
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
eks wye 4 0.38139939387114097 0.13418874328430463
wye wye 3 0.20460330576630303 0.33831852551664776
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td> <td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint sort -f a data/small
a b i x y
eks pan 2 0.7586799647899636 0.5221511083334797
eks wye 4 0.38139939387114097 0.13418874328430463
pan pan 1 0.3467901443380824 0.7268028627434533
wye wye 3 0.20460330576630303 0.33831852551664776
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td> </tr></table>
<p/>In this example, since the sort is on field <tt>a</tt>, the first step is
to group together all records having the same value for field <tt>a</tt>; the
second step is to sort the distinct <tt>a</tt>-field values <tt>pan</tt>,
<tt>eks</tt>, and <tt>wye</tt> into <tt>eks</tt>, <tt>pan</tt>, and
<tt>wye</tt>; the third step is to print out the record-list for
<tt>a=eks</tt>, then the record-list for <tt>a=pan</tt>, then the record-list
for <tt>a=wye</tt>. The group-by operation omits the middle sort and just puts
like records together, for those times when a sort isn&rsquo;t desired. In
particular, the ordering of group-by fields for group-by is the order in which
they were encountered in the data stream, which in some cases may be more interesting
to you.
<!-- ================================================================ -->
<a id="group-like"/><h2>group-like</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr group-like --help
Usage: mlr group-like
Outputs records in batches having identical field names.
</pre>
</div>
<p/>
<p/> This groups together records having the same schema (i.e. same ordered list of field names)
which is useful for making sense of time-ordered output as described in
<a href="record-heterogeneity.html">Record-heterogeneity</a> &mdash; in particular, in
preparation for CSV or pretty-print output.
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr cat data/het.dkvp
resource=/path/to/file,loadsec=0.45,ok=true
record_count=100,resource=/path/to/file
resource=/path/to/second/file,loadsec=0.32,ok=true
record_count=150,resource=/path/to/second/file
resource=/some/other/path,loadsec=0.97,ok=false
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint group-like data/het.dkvp
resource loadsec ok
/path/to/file 0.45 true
/path/to/second/file 0.32 true
/some/other/path 0.97 false
record_count resource
100 /path/to/file
150 /path/to/second/file
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="having-fields"/><h2>having-fields</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr having-fields --help
Usage: mlr having-fields [options]
Conditionally passes through records depending on each record's field names.
Options:
--at-least {comma-separated names}
--which-are {comma-separated names}
--at-most {comma-separated names}
--all-matching {regular expression}
--any-matching {regular expression}
--none-matching {regular expression}
Examples:
mlr having-fields --which-are amount,status,owner
mlr having-fields --any-matching 'sda[0-9]'
mlr having-fields --any-matching '"sda[0-9]"'
mlr having-fields --any-matching '"sda[0-9]"i' (this is case-insensitive)
</pre>
</div>
<p/>
<p/> Similar to <a href="#group-like"><tt>group-like</tt></a>, this retains records with specified schema.
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr cat data/het.dkvp
resource=/path/to/file,loadsec=0.45,ok=true
record_count=100,resource=/path/to/file
resource=/path/to/second/file,loadsec=0.32,ok=true
record_count=150,resource=/path/to/second/file
resource=/some/other/path,loadsec=0.97,ok=false
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr having-fields --at-least resource data/het.dkvp
resource=/path/to/file,loadsec=0.45,ok=true
record_count=100,resource=/path/to/file
resource=/path/to/second/file,loadsec=0.32,ok=true
record_count=150,resource=/path/to/second/file
resource=/some/other/path,loadsec=0.97,ok=false
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr having-fields --which-are resource,ok,loadsec data/het.dkvp
resource=/path/to/file,loadsec=0.45,ok=true
resource=/path/to/second/file,loadsec=0.32,ok=true
resource=/some/other/path,loadsec=0.97,ok=false
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="head"/><h2>head</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr head --help
Usage: mlr head [options]
-n {count} Head count to print; default 10
-g {a,b,c} Optional group-by-field names for head counts
Passes through the first n records, optionally by category.
</pre>
</div>
<p/>
Note that <tt>head</tt> is distinct from <a href="#top"><tt>top</tt></a>
&mdash; <tt>head</tt> shows fields which appear first in the data stream;
<tt>top</tt> shows fields which are numerically largest (or smallest).
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint head -n 4 data/medium
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint head -n 1 -g b data/medium
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
wye wye 3 0.20460330576630303 0.33831852551664776
eks zee 7 0.6117840605678454 0.1878849191181694
zee eks 17 0.29081949506712723 0.054478717073354166
wye hat 24 0.7286126830627567 0.19441962592638418
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="histogram"/><h2>histogram</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr histogram --help
Usage: mlr histogram [options]
-f {a,b,c} Value-field names for histogram counts
--lo {lo} Histogram low value
--hi {hi} Histogram high value
--nbins {n} Number of histogram bins
Just a histogram. Input values &lt; lo or &gt; hi are not counted.
</pre>
</div>
<p/>
This is just a histogram; there&rsquo;s not too much to say here. A note about
binning, by example: Suppose you use <tt>--lo 0.0 --hi 1.0 --nbins 10 -f
x</tt>. The input numbers less than 0 or greater than 1 aren&rsquo;t counted
in any bin. Input numbers equal to 1 are counted in the last bin. That is, bin
0 has <tt>0.0 &le; x &lt; 0.1</tt>, bin 1 has <tt>0.1 &le; x &lt; 0.2</tt>,
etc., but bin 9 has <tt>0.9 &le; x &le; 1.0</tt>.
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint put '$x2=$x**2;$x3=$x2*$x' then histogram -f x,x2,x3 --lo 0 --hi 1 --nbins 10 data/medium
bin_lo bin_hi x_count x2_count x3_count
0.000000 0.100000 1072 3231 4661
0.100000 0.200000 938 1254 1184
0.200000 0.300000 1037 988 845
0.300000 0.400000 988 832 676
0.400000 0.500000 950 774 576
0.500000 0.600000 1002 692 476
0.600000 0.700000 1007 591 438
0.700000 0.800000 1007 560 420
0.800000 0.900000 986 571 383
0.900000 1.000000 1013 507 341
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="join"/><h2>join</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr join --help
Usage: mlr join [options]
Joins records from specified left file name with records from all file names
at the end of the Miller argument list.
Functionality is essentially the same as the system "join" command, but for
record streams.
Options:
-f {left file name}
-j {a,b,c} Comma-separated join-field names for output
-l {a,b,c} Comma-separated join-field names for left input file;
defaults to -j values if omitted.
-r {a,b,c} Comma-separated join-field names for right input file(s);
defaults to -j values if omitted.
--lp {text} Additional prefix for non-join output field names from
the left file
--rp {text} Additional prefix for non-join output field names from
the right file(s)
--np Do not emit paired records
--ul Emit unpaired records from the left file
--ur Emit unpaired records from the right file(s)
-u Enable unsorted input. In this case, the entire left file will
be loaded into memory. Without -u, records must be sorted
lexically by their join-field names, else not all records will
be paired.
File-format options default to those for the right file names on the Miller
argument list, but may be overridden for the left file as follows. Please see
the main "mlr --help" for more information on syntax for these arguments.
-i {one of csv,dkvp,nidx,pprint,xtab}
--irs {record-separator character}
--ifs {field-separator character}
--ips {pair-separator character}
--repifs
--repips
--use-mmap
--no-mmap
Please see http://johnkerl.org/miller/doc/reference.html for more information
including examples.
</pre>
</div>
<p/>
Examples:
<p/>Join larger table with IDs with smaller ID-to-name lookup table, showing only paired records:
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsvlite --opprint cat data/join-left-example.csv
id name
100 alice
200 bob
300 carol
400 david
500 edgar
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsvlite --opprint cat data/join-right-example.csv
status idcode
present 400
present 100
missing 200
present 100
present 200
missing 100
missing 200
present 300
missing 600
present 400
present 400
present 300
present 100
missing 400
present 200
present 200
present 200
present 200
present 400
present 300
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsvlite --opprint join -u -j id -r idcode -f data/join-left-example.csv data/join-right-example.csv
id name status
400 david present
100 alice present
200 bob missing
100 alice present
200 bob present
100 alice missing
200 bob missing
300 carol present
400 david present
400 david present
300 carol present
100 alice present
400 david missing
200 bob present
200 bob present
200 bob present
200 bob present
400 david present
300 carol present
</pre>
</div>
<p/>
</td></tr></table>
<p/>Same, but with sorting the input first:
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsvlite --opprint sort -f idcode then join -j id -r idcode -f data/join-left-example.csv data/join-right-example.csv
id name status
100 alice present
100 alice present
100 alice missing
100 alice present
200 bob missing
200 bob present
200 bob missing
200 bob present
200 bob present
200 bob present
200 bob present
300 carol present
300 carol present
300 carol present
400 david present
400 david present
400 david present
400 david missing
400 david present
</pre>
</div>
<p/>
</td></tr></table>
<p/>Same, but showing only unpaired records:
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsvlite --opprint join --np --ul --ur -u -j id -r idcode -f data/join-left-example.csv data/join-right-example.csv
status idcode
missing 600
id name
500 edgar
</pre>
</div>
<p/>
</td></tr></table>
<p/>Use prefixing options to disambiguate between otherwise identical non-join field names:
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --csvlite --opprint cat data/self-join.csv data/self-join.csv
a b c
1 2 3
1 4 5
1 2 3
1 4 5
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --csvlite --opprint join -j a --lp left_ --rp right_ -f data/self-join.csv data/self-join.csv
a left_b left_c right_b right_c
1 2 3 2 3
1 4 5 2 3
1 2 3 4 5
1 4 5 4 5
</pre>
</div>
<p/>
</td></tr></table>
<p/>Use zero join columns:
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --csvlite --opprint join -j "" --lp left_ --rp right_ -f data/self-join.csv data/self-join.csv
left_a left_b left_c right_a right_b right_c
1 2 3 1 2 3
1 4 5 1 2 3
1 2 3 1 4 5
1 4 5 1 4 5
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="label"/><h2>label</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr label --help
Usage: mlr label {new1,new2,new3,...}
Given n comma-separated names, renames the first n fields of each record to
have the respective name. (Fields past the nth are left with their original
names.) Particularly useful with --inidx or --implicit-csv-header, to give
useful names to otherwise integer-indexed fields.
Examples:
"echo 'a b c d' | mlr --inidx --odkvp cat" gives "1=a,2=b,3=c,4=d"
"echo 'a b c d' | mlr --inidx --odkvp label s,t" gives "s=a,t=b,3=c,4=d"
</pre>
</div>
<p/>
See also <a href="#rename"><tt>rename</tt></a>.
<p/>Example: Files such as <tt>/etc/passwd</tt>, <tt>/etc/group</tt>, and so on
have implicit field names which are found in section-5 manpages. These field names may be made explicit as follows:
<p/>
<div class="pokipanel">
<pre>
% grep -v '^#' /etc/passwd | mlr --nidx --fs : --opprint label name,password,uid,gid,gecos,home_dir,shell | head
name password uid gid gecos home_dir shell
nobody * -2 -2 Unprivileged User /var/empty /usr/bin/false
root * 0 0 System Administrator /var/root /bin/sh
daemon * 1 1 System Services /var/root /usr/bin/false
_uucp * 4 4 Unix to Unix Copy Protocol /var/spool/uucp /usr/sbin/uucico
_taskgated * 13 13 Task Gate Daemon /var/empty /usr/bin/false
_networkd * 24 24 Network Services /var/networkd /usr/bin/false
_installassistant * 25 25 Install Assistant /var/empty /usr/bin/false
_lp * 26 26 Printing Services /var/spool/cups /usr/bin/false
_postfix * 27 27 Postfix Mail Server /var/spool/postfix /usr/bin/false
</pre>
</div>
<p/>
<p/>Likewise, if you have CSV/CSV-lite input data which has somehow been bereft of its header line, you can re-add a header line using <tt>--implicit-csv-header</tt> and <tt>label</tt>:
<p/>
<div class="pokipanel">
<pre>
$ cat data/headerless.csv
John,23,present
Fred,34,present
Alice,56,missing
Carol,45,present
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --csv --rs lf --implicit-csv-header cat data/headerless.csv
1,2,3
John,23,present
Fred,34,present
Alice,56,missing
Carol,45,present
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --csv --rs lf --implicit-csv-header label name,age,status data/headerless.csv
name,age,status
John,23,present
Fred,34,present
Alice,56,missing
Carol,45,present
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsv --rs lf --implicit-csv-header --opprint label name,age,status data/headerless.csv
name age status
John 23 present
Fred 34 present
Alice 56 missing
Carol 45 present
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="put"/><h2>put</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr put --help
Usage: mlr put [-v] [-s|-f] {expression}
Adds/updates specified field(s).
-v: First prints the AST (abstract syntax tree) for the expression, which gives
full transparency on the precedence and associativity rules of Miller's
grammar.
-s: Keeps field values, or literals in the expression, as strings with no type
inference to int or float.
-f: Keeps field values, or literals in the expression, as strings or floats
with no inference to int.
Please use a dollar sign for field names and double-quotes for string
literals. Miller built-in variables are NF NR FNR FILENUM FILENAME PI E.
Multiple assignments may be separated with a semicolon.
Examples:
mlr put '$y = log10($x); $z = sqrt($y)'
mlr put '$filename = FILENAME'
mlr put '$colored_shape = $color . "_" . $shape'
mlr put '$y = cos($theta); $z = atan2($y, $x)'
mlr put '$name = sub($name, "http.*com"i, "")'
Please see http://johnkerl.org/miller/doc/reference.html for more information
including function list.
</pre>
</div>
<p/>
<p/>Field names must be specified using a <tt>$</tt> in <a href="#filter"><tt>filter</tt></a> and <tt>put</tt>
expressions, even though they don&rsquo;t appear in the data stream. For
integer-indexed data, this looks like <tt>awk</tt>&rsquo;s <tt>$1,$2,$3</tt>.
Likewise, enclose string literals in double quotes in <tt>put</tt>
expressions even though they don&rsquo;t appear in file data. In particular,
<tt>mlr put '$x=="abc"'</tt> creates the field <tt>x=abc</tt>.
<p/>Multiple expressions may be given, separated by semicolons, and each may refer to the ones before:
<p/>
<div class="pokipanel">
<pre>
$ ruby -e '10.times{|i|puts "i=#{i}"}' | mlr --opprint put '$j=$i+1;$k=$i+$j'
i j k
0 1 1
1 2 3
2 3 5
3 4 7
4 5 9
5 6 11
6 7 13
7 8 15
8 9 17
9 10 19
</pre>
</div>
<p/>
<p/>Miller supports the following five built-in variables for <a href="#filter"><tt>filter</tt></a>
and <tt>put</tt>, all <tt>awk</tt>-inspired: <tt>NF</tt>, <tt>NR</tt>,
<tt>FNR</tt>, <tt>FILENUM</tt>, and <tt>FILENAME</tt>.
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint put '$nf=NF; $nr=NR; $fnr=FNR; $filenum=FILENUM; $filename=FILENAME' data/small data/small2
a b i x y nf nr fnr filenum filename
pan pan 1 0.3467901443380824 0.7268028627434533 5 1 1 1 data/small
eks pan 2 0.7586799647899636 0.5221511083334797 5 2 2 1 data/small
wye wye 3 0.20460330576630303 0.33831852551664776 5 3 3 1 data/small
eks wye 4 0.38139939387114097 0.13418874328430463 5 4 4 1 data/small
wye pan 5 0.5732889198020006 0.8636244699032729 5 5 5 1 data/small
pan eks 9999 0.267481232652199086 0.557077185510228001 5 6 1 2 data/small2
wye eks 10000 0.734806020620654365 0.884788571337605134 5 7 2 2 data/small2
pan wye 10001 0.870530722602517626 0.009854780514656930 5 8 3 2 data/small2
hat wye 10002 0.321507044286237609 0.568893318795083758 5 9 4 2 data/small2
pan zee 10003 0.272054845593895200 0.425789896597056627 5 10 5 2 data/small2
</pre>
</div>
<p/>
Newlines within the expression are ignored, which can help increase legibility of complex expressions:
<p/>
<div class="pokipanel">
<pre>
mlr --opprint put '
$nf = NF;
$nr = NR;
$fnr = FNR;
$filenum = FILENUM;
$filename = FILENAME' \
data/small data/small2
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="regularize"/><h2>regularize</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr regularize --help
Usage: mlr regularize
For records seen earlier in the data stream with same field names in
a different order, outputs them with field names in the previously
encountered order.
Example: input records a=1,c=2,b=3, then e=4,d=5, then c=7,a=6,b=8
output as a=1,c=2,b=3, then e=4,d=5, then a=6,c=7,b=8
</pre>
</div>
<p/>
<p/>This exists since hash-map software in various languages and tools
encountered in the wild does not always print similar rows with fields in the
same order: <tt>mlr regularize</tt> helps clean that up.
<p/>See also <a href="#reorder"><tt>reorder</tt></a>.
<!-- ================================================================ -->
<a id="rename"/><h2>rename</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr rename --help
Usage: mlr rename [options] {old1,new1,old2,new2,...}
Renames specified fields.
Options:
-r Treat old field names as regular expressions. "ab", "a.*b"
will match any field name containing the substring "ab" or
matching "a.*b", respectively; anchors of the form "^ab$",
"^a.*b$" may be used. New field names may be plain strings,
or may contain capture groups of the form "\1" through
"\9". Wrapping the regex in double quotes is optional, but
is required if you wish to follow it with 'i' to indicate
case-insensitivity.
-g Do global replacement within each field name rather than
first-match replacement.
Examples:
mlr rename -r 'Date_[0-9]+,Date,' Rename all such fields to be "Date"
mlr rename -r '"Date_[0-9]+",Date' Same
mlr rename -r 'Date_([0-9]+).*,\1' Rename all such fields to be of the form 20151015
mlr rename -r '"name"i,Name' Rename "name", "Name", "NAME", etc. to "Name"
</pre>
</div>
<p/>
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint cat data/small
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint rename i,INDEX,b,COLUMN2 data/small
a COLUMN2 INDEX x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td></tr></table>
<p/>As discussed in <a href="performance.html">Performance</a>, <tt>sed</tt>
is significantly faster than Miller at doing this. However, Miller is
format-aware, so it knows to do renames only within specified field keys and
not any others, nor in field values which may happen to contain the same
pattern. Example:
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ sed 's/y/COLUMN5/g' data/small
a=pan,b=pan,i=1,x=0.3467901443380824,COLUMN5=0.7268028627434533
a=eks,b=pan,i=2,x=0.7586799647899636,COLUMN5=0.5221511083334797
a=wCOLUMN5e,b=wCOLUMN5e,i=3,x=0.20460330576630303,COLUMN5=0.33831852551664776
a=eks,b=wCOLUMN5e,i=4,x=0.38139939387114097,COLUMN5=0.13418874328430463
a=wCOLUMN5e,b=pan,i=5,x=0.5732889198020006,COLUMN5=0.8636244699032729
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr rename y,COLUMN5 data/small
a=pan,b=pan,i=1,x=0.3467901443380824,COLUMN5=0.7268028627434533
a=eks,b=pan,i=2,x=0.7586799647899636,COLUMN5=0.5221511083334797
a=wye,b=wye,i=3,x=0.20460330576630303,COLUMN5=0.33831852551664776
a=eks,b=wye,i=4,x=0.38139939387114097,COLUMN5=0.13418874328430463
a=wye,b=pan,i=5,x=0.5732889198020006,COLUMN5=0.8636244699032729
</pre>
</div>
<p/>
</td></tr></table>
See also <a href="#label"><tt>label</tt></a>.
<!-- ================================================================ -->
<a id="reorder"/><h2>reorder</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr reorder --help
Usage: mlr reorder [options]
-f {a,b,c} Field names to reorder.
-e Put specified field names at record end: default is to put
them at record start.
Examples:
mlr reorder -f a,b sends input record "d=4,b=2,a=1,c=3" to "a=1,b=2,d=4,c=3".
mlr reorder -e -f a,b sends input record "d=4,b=2,a=1,c=3" to "d=4,c=3,a=1,b=2".
</pre>
</div>
<p/>
This pivots specified field names to the start or end of the record &mdash; for
example when you have highly multi-column data and you want to bring a field or
two to the front of line where you can give a quick visual scan.
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint cat data/small
a b i x y
pan pan 1 0.3467901443380824 0.7268028627434533
eks pan 2 0.7586799647899636 0.5221511083334797
wye wye 3 0.20460330576630303 0.33831852551664776
eks wye 4 0.38139939387114097 0.13418874328430463
wye pan 5 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint reorder -f i,b data/small
i b a x y
1 pan pan 0.3467901443380824 0.7268028627434533
2 pan eks 0.7586799647899636 0.5221511083334797
3 wye wye 0.20460330576630303 0.33831852551664776
4 wye eks 0.38139939387114097 0.13418874328430463
5 pan wye 0.5732889198020006 0.8636244699032729
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint reorder -e -f i,b data/small
a x y i b
pan 0.3467901443380824 0.7268028627434533 1 pan
eks 0.7586799647899636 0.5221511083334797 2 pan
wye 0.20460330576630303 0.33831852551664776 3 wye
eks 0.38139939387114097 0.13418874328430463 4 wye
wye 0.5732889198020006 0.8636244699032729 5 pan
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="sample"/><h2>sample</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr sample --help
Usage: mlr sample [options]
Reservoir sampling, optionally by category.
-k {count} Required: number of records to output, total, or by group if using -g.
-g {a,b,c} Optional: group-by-field names for samples.
</pre>
</div>
<p/>
<p/>This is reservoir-sampling: select <i>k</i> items from <i>n</i> with
uniform probability and no repeats in the sample. (If <i>n</i> is less than
<i>k</i>, then of course only <i>n</i> samples are produced.) With <tt>-g
{field names}</tt>, produce a <i>k</i>-sample for each distinct value of the
specified field names.
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint sample -k 4 data/colored-shapes.dkvp
color shape flag i u v w x
purple triangle 0 90122 0.9986871176198068 0.3037738877233719 0.5154934457238382 5.365962021016529
red circle 0 3139 0.04835898233323954 -0.03964684310055758 0.5263660881848111 5.3758779366493625
orange triangle 0 67847 0.36746306902109926 0.5161574810505635 0.5176199566173642 3.1748088656576567
yellow square 1 33576 0.3098376725521097 0.8525628505287842 0.49774122460981685 4.494754378604669
$ mlr --opprint sample -k 4 data/colored-shapes.dkvp
color shape flag i u v w x
blue square 1 16783 0.09974385090654347 0.7243899920872646 0.5353718443278438 4.431057737383438
orange square 1 93291 0.5944176543007182 0.17744449786454086 0.49262281749172077 3.1548117990710653
yellow square 1 54436 0.5268161165014636 0.8785588662666121 0.5058773791931063 7.019185838783636
yellow square 1 55491 0.0025440267883102274 0.05474106287787284 0.5102729153751984 3.526301273728043
$ mlr --opprint sample -k 2 -g color data/colored-shapes.dkvp
color shape flag i u v w x
yellow triangle 1 11 0.6321695890307647 0.9887207810889004 0.4364983936735774 5.7981881667050565
yellow square 1 917 0.8547010348386344 0.7356782810796262 0.4531511689924275 5.774541777078352
red circle 1 4000 0.05490416175132373 0.07392337815122155 0.49416101516594396 5.355725080701707
red square 0 87506 0.6357719216821314 0.6970867759393995 0.4940826462055272 6.351579417310387
purple triangle 0 14898 0.7800986870203719 0.23998073813992293 0.5014775988383656 3.141006771777843
purple triangle 0 151 0.032614487569017414 0.7346633365041219 0.7812143304483805 2.6831992610568047
green triangle 1 126 0.1513010528347546 0.40346767294704544 0.051213231883952326 5.955109300797182
green circle 0 17635 0.029856606049114442 0.4724542934246524 0.49529606749929744 5.239153910272168
blue circle 1 1020 0.414263129226617 0.8304946402876182 0.13151094520189244 4.397873687920433
blue triangle 0 220 0.441773289968473 0.44597731903759075 0.6329360666849821 4.3064608776550894
orange square 0 1885 0.8079311983747106 0.8685956833908394 0.3116410800256374 4.390864584500387
orange triangle 0 1533 0.32904497195507487 0.23168161807490417 0.8722623057355134 5.164071635714438
$ mlr --opprint sample -k 2 -g color then sort -f color data/colored-shapes.dkvp
color shape flag i u v w x
blue circle 0 215 0.7803586969333292 0.33146680638888126 0.04289047852629113 5.725365736377487
blue circle 1 3616 0.8548431579124808 0.4989623130006362 0.3339426415875795 3.696785877560498
green square 0 356 0.7674272008085286 0.341578843118008 0.4570224877870851 4.830320062215299
green square 0 152 0.6684429446914862 0.016056003736548696 0.4656148241291592 5.434588759225423
orange triangle 0 587 0.5175826237797857 0.08989091493635304 0.9011709461770973 4.265854207755811
orange triangle 0 1533 0.32904497195507487 0.23168161807490417 0.8722623057355134 5.164071635714438
purple triangle 0 14192 0.5196327866973567 0.7860928603468063 0.4964368415453642 4.899167143824484
purple triangle 0 65 0.6842806710360729 0.5823723856331258 0.8014053396013747 5.805148213865135
red square 1 2431 0.38378504852300466 0.11445015005595527 0.49355539228753786 5.146756570128739
red triangle 0 57097 0.43763430414406546 0.3355450325004481 0.5322349637512487 4.144267240289442
yellow triangle 1 11 0.6321695890307647 0.9887207810889004 0.4364983936735774 5.7981881667050565
yellow square 1 158 0.41527900739142165 0.7118027080775757 0.4200799665161291 5.33279067554884
</pre>
</div>
<p/>
<p/>Note that no output is produced until all inputs are in. Another way to do
sampling, which works in the streaming case, is <tt>mlr filter 'urand() &amp;
0.001'</tt> where you tune the 0.001 to meet your needs.
<!-- ================================================================ -->
<a id="sec2gmt"/><h2>sec2gmt</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr sec2gmt -h
Usage: mlr sec2gmt {comma-separated list of field names}
Replaces a numeric field representing seconds since the epoch with the
corresponding GMT timestamp. This is nothing more than a keystroke-saver for
the sec2gmt function:
mlr sec2gmt time1,time2
is the same as
mlr put '$time1=sec2gmt($time1);$time2=sec2gmt($time2)'
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="sort"/><h2>sort</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr sort --help
Usage: mlr sort {flags}
Flags:
-f {comma-separated field names} Lexical ascending
-n {comma-separated field names} Numerical ascending; nulls sort last
-nf {comma-separated field names} Numerical ascending; nulls sort last
-r {comma-separated field names} Lexical descending
-nr {comma-separated field names} Numerical descending; nulls sort first
Sorts records primarily by the first specified field, secondarily by the second
field, and so on. Any records not having all specified sort keys will appear
at the end of the output, in the order they were encountered, regardless of the
specified sort order.
Example:
mlr sort -f a,b -nr x,y,z
which is the same as:
mlr sort -f a -f b -nr x -nr y -nr z
</pre>
</div>
<p/>
<p/>Example:
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint sort -f a -nr x data/small
a b i x y
eks pan 2 0.7586799647899636 0.5221511083334797
eks wye 4 0.38139939387114097 0.13418874328430463
pan pan 1 0.3467901443380824 0.7268028627434533
wye pan 5 0.5732889198020006 0.8636244699032729
wye wye 3 0.20460330576630303 0.33831852551664776
</pre>
</div>
<p/>
<p/>Here&rsquo;s an example filtering log data: suppose multiple threads (labeled here by color) are all logging progress counts to a single log file. The log file is (by nature) chronological, so the progress of various threads is interleaved:
<p/>
<div class="pokipanel">
<pre>
$ head -n 10 data/multicountdown.dat
upsec=0.002,color=green,count=1203
upsec=0.083,color=red,count=3817
upsec=0.188,color=red,count=3801
upsec=0.395,color=blue,count=2697
upsec=0.526,color=purple,count=953
upsec=0.671,color=blue,count=2684
upsec=0.899,color=purple,count=926
upsec=0.912,color=red,count=3798
upsec=1.093,color=blue,count=2662
upsec=1.327,color=purple,count=917
</pre>
</div>
<p/>
<p/> We can group these by thread by sorting on the thread ID (here,
<tt>color</tt>). Since Miller&rsquo;s sort is stable, this means that
timestamps within each thread&rsquo;s log data are still chronological:
<p/>
<div class="pokipanel">
<pre>
$ head -n 20 data/multicountdown.dat | mlr --opprint sort -f color
upsec color count
0.395 blue 2697
0.671 blue 2684
1.093 blue 2662
2.064 blue 2659
2.2880000000000003 blue 2647
0.002 green 1203
1.407 green 1187
1.448 green 1177
2.313 green 1161
0.526 purple 953
0.899 purple 926
1.327 purple 917
1.703 purple 908
0.083 red 3817
0.188 red 3801
0.912 red 3798
1.416 red 3788
1.587 red 3782
1.601 red 3755
1.832 red 3717
</pre>
</div>
<p/>
<p/>Any records not having all specified sort keys will appear at the end of the output, in the order they
were encountered, regardless of the specified sort order:
<p/>
<div class="pokipanel">
<pre>
$ mlr sort -n x data/sort-missing.dkvp
x=1
x=2
x=4
a=3
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr sort -nr x data/sort-missing.dkvp
x=4
x=2
x=1
a=3
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="stats1"/><h2>stats1</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr stats1 --help
Usage: mlr stats1 [options]
Options:
-a {sum,count,...} Names of accumulators: p10 p25.2 p50 p98 p100 etc. and/or
one or more of:
count Count instances of fields
mode Find most-frequently-occurring values for fields; first-found wins tie
sum Compute sums of specified fields
mean Compute averages (sample means) of specified fields
stddev Compute sample standard deviation of specified fields
var Compute sample variance of specified fields
meaneb Estimate error bars for averages (assuming no sample autocorrelation)
skewness Compute sample skewness of specified fields
kurtosis Compute sample kurtosis of specified fields
min Compute minimum values of specified fields
max Compute maximum values of specified fields
-f {a,b,c} Value-field names on which to compute statistics
-g {d,e,f} Optional group-by-field names
-s Print iterative stats. Useful in tail -f contexts (in which
case please avoid pprint-format output since end of input
stream will never be seen).
Example: mlr stats1 -a min,p10,p50,p90,max -f value -g size,shape
Example: mlr stats1 -a count,mode -f size
Example: mlr stats1 -a count,mode -f size -g shape
Notes:
* p50 is a synonym for median.
* min and max output the same results as p0 and p100, respectively, but use
less memory.
* count and mode allow text input; the rest require numeric input.
In particular, 1 and 1.0 are distinct text for count and mode.
* When there are mode ties, the first-encountered datum wins.
</pre>
</div>
<p/>
These are simple univariate statistics on one or more number-valued fields
(<tt>count</tt> and <tt>mode</tt> apply to non-numeric fields as well),
optionally categorized by one or more other fields.
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --oxtab stats1 -a count,sum,min,p10,p50,mean,p90,max -f x,y data/medium
x_count 10000
x_sum 4986.019682
x_min 0.000045
x_p10 0.093322
x_p50 0.501159
x_mean 0.498602
x_p90 0.900794
x_max 0.999953
y_count 10000
y_sum 5062.057445
y_min 0.000088
y_p10 0.102132
y_p50 0.506021
y_mean 0.506206
y_p90 0.905366
y_max 0.999965
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint stats1 -a mean -f x,y -g b then sort -f b data/medium
b x_mean y_mean
eks 0.506361 0.510293
hat 0.487899 0.513118
pan 0.497304 0.499599
wye 0.497593 0.504596
zee 0.504242 0.502997
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint stats1 -a p50,p99 -f u,v -g color then put '$ur=$u_p99/$u_p50;$vr=$v_p99/$v_p50' data/colored-shapes.dkvp
color u_p50 u_p99 v_p50 v_p99 ur vr
yellow 0.501019 0.989046 0.520630 0.987034 1.974069 1.895845
red 0.485038 0.990054 0.492586 0.994444 2.041189 2.018823
purple 0.501319 0.988893 0.504571 0.988287 1.972582 1.958668
green 0.502015 0.990764 0.505359 0.990175 1.973574 1.959350
blue 0.525226 0.992655 0.485170 0.993873 1.889958 2.048505
orange 0.483548 0.993635 0.480913 0.989102 2.054884 2.056717
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint count-distinct -f shape then sort -nr count data/colored-shapes.dkvp
shape count
square 4115
triangle 3372
circle 2591
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint stats1 -a mode -f color -g shape data/colored-shapes.dkvp
shape color_mode
triangle red
square red
circle red
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="stats2"/><h2>stats2</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr stats2 --help
Usage: mlr stats2 [options]
-a {linreg-ols,corr,...} Names of accumulators: one or more of:
linreg-pca Linear regression using principal component analysis
linreg-ols Linear regression using ordinary least squares
r2 Quality metric for linreg-ols (linreg-pca emits its own)
logireg Logistic regression
corr Sample correlation
cov Sample covariance
covx Sample-covariance matrix
-f {a,b,c,d} Value-field name-pairs on which to compute statistics.
There must be an even number of names.
-g {e,f,g} Optional group-by-field names.
-v Print additional output for linreg-pca.
-s Print iterative stats. Useful in tail -f contexts (in which
case please avoid pprint-format output since end of input
stream will never be seen).
--fit Rather than printing regression parameters, applies them to
the input data to compute new fit fields. All input records are
held in memory until end of input stream. Has effect only for
linreg-ols, linreg-pca, and logireg.
Only one of -s or --fit may be used.
Example: mlr stats2 -a linreg-pca -f x,y
Example: mlr stats2 -a linreg-ols,r2 -f x,y -g size,shape
Example: mlr stats2 -a corr -f x,y
</pre>
</div>
<p/>
These are simple bivariate statistics on one or more pairs of number-valued
fields, optionally categorized by one or more fields.
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --oxtab put '$x2=$x*$x; $xy=$x*$y; $y2=$y**2' then stats2 -a cov,corr -f x,y,y,y,x2,xy,x2,y2 data/medium
x_y_cov 0.000043
x_y_corr 0.000504
y_y_cov 0.084611
y_y_corr 1.000000
x2_xy_cov 0.041884
x2_xy_corr 0.630174
x2_y2_cov -0.000310
x2_y2_corr -0.003425
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint put '$x2=$x*$x; $xy=$x*$y; $y2=$y**2' then stats2 -a linreg-ols,r2 -f x,y,y,y,xy,y2 -g a data/medium
a x_y_ols_m x_y_ols_b x_y_ols_n x_y_r2 y_y_ols_m y_y_ols_b y_y_ols_n y_y_r2 xy_y2_ols_m xy_y2_ols_b xy_y2_ols_n xy_y2_r2
pan 0.017026 0.500403 2081 0.000287 1.000000 0.000000 2081 1.000000 0.878132 0.119082 2081 0.417498
eks 0.040780 0.481402 1965 0.001646 1.000000 0.000000 1965 1.000000 0.897873 0.107341 1965 0.455632
wye -0.039153 0.525510 1966 0.001505 1.000000 0.000000 1966 1.000000 0.853832 0.126745 1966 0.389917
zee 0.002781 0.504307 2047 0.000008 1.000000 0.000000 2047 1.000000 0.852444 0.124017 2047 0.393566
hat -0.018621 0.517901 1941 0.000352 1.000000 0.000000 1941 1.000000 0.841230 0.135573 1941 0.368794
</pre>
</div>
<p/>
</td></tr></table>
<p/>Here&rsquo;s an example simple line-fit. The <tt>x</tt> and <tt>y</tt>
fields of the <tt>data/medium</tt> dataset are just independent uniformly
distributed on the unit interval. Here we remove half the data and fit a line to it.
<p/>
<div class="pokipanel">
<pre>
# Prepare input data:
mlr filter '($x&lt;.5 &amp;&amp; $y&lt;.5) || ($x&gt;.5 &amp;&amp; $y&gt;.5)' data/medium &gt; data/medium-squares
# Do a linear regression and examine coefficients:
mlr --ofs newline stats2 -a linreg-pca -f x,y data/medium-squares
x_y_pca_m=1.014419
x_y_pca_b=0.000308
x_y_pca_quality=0.861354
# Option 1 to apply the regression coefficients and produce a linear fit:
# Set x_y_pca_m and x_y_pca_b as shell variables:
eval $(mlr --ofs newline stats2 -a linreg-pca -f x,y data/medium-squares)
# In addition to x and y, make a new yfit which is the line fit, then plot
# using your favorite tool:
mlr --onidx put '$yfit='$x_y_pca_m'*$x+'$x_y_pca_b then cut -x -f a,b,i data/medium-squares \
| pgr -p -title 'linreg-pca example' -xmin 0 -xmax 1 -ymin 0 -ymax 1
# Option 2 to apply the regression coefficients and produce a linear fit: use --fit option
mlr --onidx stats2 -a linreg-pca --fit -f x,y then cut -f a,b,i data/medium-squares \
| pgr -p -title 'linreg-pca example' -xmin 0 -xmax 1 -ymin 0 -ymax 1
</pre>
</div>
<p/>
<p/>I use <a href="https://github.com/johnkerl/pgr"><tt>pgr</tt></a> for
plotting; here&rsquo;s a screenshot.
<center>
<img src="data/linreg-example.jpg"/>
</center>
<p/> (Thanks Drew Kunas for a good conversation about PCA!)
<p/> Here&rsquo;s an example estimating time-to-completion for a set of jobs.
Input data comes from a log file, with number of work units left to do in the
<tt>count</tt> field and accumulated seconds in the <tt>upsec</tt> field,
labeled by the <tt>color</tt> field:
<p/>
<div class="pokipanel">
<pre>
$ head -n 10 data/multicountdown.dat
upsec=0.002,color=green,count=1203
upsec=0.083,color=red,count=3817
upsec=0.188,color=red,count=3801
upsec=0.395,color=blue,count=2697
upsec=0.526,color=purple,count=953
upsec=0.671,color=blue,count=2684
upsec=0.899,color=purple,count=926
upsec=0.912,color=red,count=3798
upsec=1.093,color=blue,count=2662
upsec=1.327,color=purple,count=917
</pre>
</div>
<p/>
We can do a linear regression on count remaining as a function of time: with <tt>c = m*u+b</tt> we want to find the
time when the count goes to zero, i.e. <tt>u=-b/m</tt>.
<p/>
<div class="pokipanel">
<pre>
$ mlr --oxtab stats2 -a linreg-pca -f upsec,count -g color then put '$donesec = -$upsec_count_pca_b/$upsec_count_pca_m' data/multicountdown.dat
color green
upsec_count_pca_m -32.756917
upsec_count_pca_b 1213.722730
upsec_count_pca_n 24
upsec_count_pca_quality 0.999984
donesec 37.052410
color red
upsec_count_pca_m -37.367646
upsec_count_pca_b 3810.133400
upsec_count_pca_n 30
upsec_count_pca_quality 0.999989
donesec 101.963431
color blue
upsec_count_pca_m -29.231212
upsec_count_pca_b 2698.932820
upsec_count_pca_n 25
upsec_count_pca_quality 0.999959
donesec 92.330514
color purple
upsec_count_pca_m -39.030097
upsec_count_pca_b 979.988341
upsec_count_pca_n 21
upsec_count_pca_quality 0.999991
donesec 25.108529
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="step"/><h2>step</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr step --help
Usage: mlr step [options]
-a {delta,rsum,...} Names of steppers: comma-separated, one or more of:
delta Compute differences in field(s) between successive records
ratio Compute ratios in field(s) between successive records
rsum Compute running sums of field(s) between successive records
counter Count instances of field(s) between successive records
-f {a,b,c} Value-field names on which to compute statistics
-g {d,e,f} Optional group-by-field names
Computes values dependent on the previous record, optionally grouped
by category.
</pre>
</div>
<p/>
Most Miller commands are record-at-a-time, with the exception of <tt>stats1</tt>,
<tt>stats2</tt>, and <tt>histogram</tt> which compute aggregate output. The
<tt>step</tt> command is intermediate: it allows the option of adding fields
which are functions of fields from previous records. Rsum is short for <i>running sum</i>.
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint step -a delta,rsum,counter -f x data/medium | head -15
a b i x y x_delta x_rsum x_counter
pan pan 1 0.3467901443380824 0.7268028627434533 0.000000 0.346790 1
eks pan 2 0.7586799647899636 0.5221511083334797 0.411890 1.105470 2
wye wye 3 0.20460330576630303 0.33831852551664776 -0.554077 1.310073 3
eks wye 4 0.38139939387114097 0.13418874328430463 0.176796 1.691473 4
wye pan 5 0.5732889198020006 0.8636244699032729 0.191890 2.264762 5
zee pan 6 0.5271261600918548 0.49322128674835697 -0.046163 2.791888 6
eks zee 7 0.6117840605678454 0.1878849191181694 0.084658 3.403672 7
zee wye 8 0.5985540091064224 0.976181385699006 -0.013230 4.002226 8
hat wye 9 0.03144187646093577 0.7495507603507059 -0.567112 4.033668 9
pan wye 10 0.5026260055412137 0.9526183602969864 0.471184 4.536294 10
pan pan 11 0.7930488423451967 0.6505816637259333 0.290423 5.329343 11
zee pan 12 0.3676141320555616 0.23614420670296965 -0.425435 5.696957 12
eks pan 13 0.4915175580479536 0.7709126592971468 0.123903 6.188474 13
eks zee 14 0.5207382318405251 0.34141681118811673 0.029221 6.709213 14
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint step -a delta,rsum,counter -f x -g a data/medium | head -15
a b i x y x_delta x_rsum x_counter
pan pan 1 0.3467901443380824 0.7268028627434533 0.000000 0.346790 1
eks pan 2 0.7586799647899636 0.5221511083334797 0.000000 0.758680 1
wye wye 3 0.20460330576630303 0.33831852551664776 0.000000 0.204603 1
eks wye 4 0.38139939387114097 0.13418874328430463 -0.377281 1.140079 2
wye pan 5 0.5732889198020006 0.8636244699032729 0.368686 0.777892 2
zee pan 6 0.5271261600918548 0.49322128674835697 0.000000 0.527126 1
eks zee 7 0.6117840605678454 0.1878849191181694 0.230385 1.751863 3
zee wye 8 0.5985540091064224 0.976181385699006 0.071428 1.125680 2
hat wye 9 0.03144187646093577 0.7495507603507059 0.000000 0.031442 1
pan wye 10 0.5026260055412137 0.9526183602969864 0.155836 0.849416 2
pan pan 11 0.7930488423451967 0.6505816637259333 0.290423 1.642465 3
zee pan 12 0.3676141320555616 0.23614420670296965 -0.230940 1.493294 3
eks pan 13 0.4915175580479536 0.7709126592971468 -0.120267 2.243381 4
eks zee 14 0.5207382318405251 0.34141681118811673 0.029221 2.764119 5
</pre>
</div>
<p/>
</td></tr></table>
Example deriving uptime-delta from system uptime:
<p/>
<div class="pokipanel">
<pre>
$ each 10 uptime | mlr -p step -a delta -f 11
...
20:08 up 36 days, 10:38, 5 users, load averages: 1.42 1.62 1.73 0.000000
20:08 up 36 days, 10:38, 5 users, load averages: 1.55 1.64 1.74 0.020000
20:08 up 36 days, 10:38, 7 users, load averages: 1.58 1.65 1.74 0.010000
20:08 up 36 days, 10:38, 9 users, load averages: 1.78 1.69 1.76 0.040000
20:08 up 36 days, 10:39, 9 users, load averages: 2.12 1.76 1.78 0.070000
20:08 up 36 days, 10:39, 9 users, load averages: 2.51 1.85 1.81 0.090000
20:08 up 36 days, 10:39, 8 users, load averages: 2.79 1.92 1.83 0.070000
20:08 up 36 days, 10:39, 4 users, load averages: 2.64 1.90 1.83 -0.020000
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="tac"/><h2>tac</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr tac --help
Usage: mlr tac
Prints records in reverse order from the order in which they were encountered.
</pre>
</div>
<p/>
<p/>Prints the records in the input stream in reverse order. Note: this
requires Miller to retain all input records in memory before any output records
are produced.
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsv --opprint cat a.csv
a b c
1 2 3
4 5 6
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsv --opprint cat b.csv
a b c
7 8 9
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsv --opprint tac a.csv b.csv
a b c
7 8 9
4 5 6
1 2 3
</pre>
</div>
<p/>
</td></tr></table>
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --icsv --opprint put '$filename=FILENAME' then tac a.csv b.csv
a b c filename
7 8 9 b.csv
4 5 6 a.csv
1 2 3 a.csv
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="tail"/><h2>tail</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr tail --help
Usage: mlr tail [options]
-n {count} Tail count to print; default 10
-g {a,b,c} Optional group-by-field names for tail counts
Passes through the last n records, optionally by category.
</pre>
</div>
<p/>
<p/> Prints the last <i>n</i> records in the input stream, optionally by category.
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint tail -n 4 data/colored-shapes.dkvp
color shape flag i u v w x
blue square 1 99974 0.6189062525431605 0.2637962404841453 0.5311465405784674 6.210738209085753
blue triangle 0 99976 0.008110504040268474 0.8267274952432482 0.4732962944898885 6.146956761817328
yellow triangle 0 99990 0.3839424618160777 0.55952913620132 0.5113763011485609 4.307973891915119
yellow circle 1 99994 0.764950884927175 0.25284227383991364 0.49969878539567425 5.013809741826425
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint tail -n 1 -g shape data/colored-shapes.dkvp
color shape flag i u v w x
yellow triangle 0 99990 0.3839424618160777 0.55952913620132 0.5113763011485609 4.307973891915119
blue square 1 99974 0.6189062525431605 0.2637962404841453 0.5311465405784674 6.210738209085753
yellow circle 1 99994 0.764950884927175 0.25284227383991364 0.49969878539567425 5.013809741826425
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="top"/><h2>top</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr top --help
Usage: mlr top [options]
-f {a,b,c} Value-field names for top counts.
-g {d,e,f} Optional group-by-field names for top counts.
-n {count} How many records to print per category; default 1.
-a Print all fields for top-value records; default is
to print only value and group-by fields. Requires a single
value-field name only.
--min Print top smallest values; default is top largest values.
Prints the n records with smallest/largest values at specified fields,
optionally by category.
</pre>
</div>
<p/>
Note that <tt>top</tt> is distinct from <a href="#head"><tt>head</tt></a>
&mdash; <tt>head</tt> shows fields which appear first in the data stream;
<tt>top</tt> shows fields which are numerically largest (or smallest).
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint top -n 4 -f x data/medium
top_idx x_top
1 0.999953
2 0.999823
3 0.999733
4 0.999563
</pre>
</div>
<p/>
</td><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint top -n 2 -f x -g a then sort -f a data/medium
a top_idx x_top
eks 1 0.998811
eks 2 0.998534
hat 1 0.999953
hat 2 0.999733
pan 1 0.999403
pan 2 0.999044
wye 1 0.999823
wye 2 0.999264
zee 1 0.999490
zee 2 0.999438
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="uniq"/><h2>uniq</h2>
<p/>
<div class="pokipanel">
<pre>
$ mlr uniq --help
Usage: mlr uniq [options]
-g {d,e,f} Group-by-field names for uniq counts
-c Show repeat counts in addition to unique values
Prints distinct values for specified field names. With -c, same as
count-distinct.
</pre>
</div>
<p/>
<table><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ wc -l data/colored-shapes.dkvp
10078 data/colored-shapes.dkvp
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr uniq -g color,shape data/colored-shapes.dkvp
color=yellow,shape=triangle
color=red,shape=square
color=red,shape=circle
color=purple,shape=triangle
color=yellow,shape=circle
color=purple,shape=square
color=yellow,shape=square
color=red,shape=triangle
color=green,shape=triangle
color=green,shape=square
color=blue,shape=circle
color=blue,shape=triangle
color=purple,shape=circle
color=blue,shape=square
color=green,shape=circle
color=orange,shape=triangle
color=orange,shape=square
color=orange,shape=circle
</pre>
</div>
<p/>
</td></tr><tr><td>
<p/>
<div class="pokipanel">
<pre>
$ mlr --opprint uniq -g color,shape -c then sort -f color,shape data/colored-shapes.dkvp
color shape count
blue circle 384
blue square 589
blue triangle 497
green circle 287
green square 454
green triangle 368
orange circle 68
orange square 128
orange triangle 107
purple circle 289
purple square 481
purple triangle 372
red circle 1207
red square 1874
red triangle 1560
yellow circle 356
yellow square 589
yellow triangle 468
</pre>
</div>
<p/>
</td></tr></table>
<!-- ================================================================ -->
<a id="then-chaining"/><h1>then-chaining</h1>
<p/>
In accord with the
<a href="http://en.wikipedia.org/wiki/Unix_philosophy">Unix philosophy</a>, you can pipe data into or out of
Miller. For example:
<p/>
<div class="pokipanel">
<pre>
mlr cut --complement -f os_version *.dat | mlr sort -f hostname,uptime
</pre>
</div>
<p/>
<p/>
You can, if you like, instead simply chain commands together using the
<tt>then</tt> keyword:
<p/>
<div class="pokipanel">
<pre>
mlr cut --complement -f os_version then sort -f hostname,uptime *.dat
</pre>
</div>
<p/>
Here&rsquo;s a performance comparison:
<p/>
<div class="pokipanel">
<pre>
% cat piped.sh
mlr cut -x -f i,y data/big | mlr sort -n y &gt; /dev/null
% time sh piped.sh
real 0m2.828s
user 0m3.183s
sys 0m0.137s
% cat chained.sh
mlr cut -x -f i,y then sort -n y data/big &gt; /dev/null
% time sh chained.sh
real 0m2.082s
user 0m1.933s
sys 0m0.137s
</pre>
</div>
<p/>
There are two reasons to use then-chaining: one is for performance, although I
don&rsquo;t expect this to be a win in all cases. Using then-chaining avoids
redundant string-parsing and string-formatting at each pipeline step: instead
input records are parsed once, they are fed through each pipeline stage in
memory, and then output records are formatted once. On the other hand, Miller
is single-threaded, while modern systems are usually multi-processor, and when
streaming-data programs operate through pipes, each one can use a CPU. Rest
assured you get the same results either way.
<p/>The other reason to use then-chaining is for simplicity: you don&rsquo;t
have re-type formatting flags (e.g. <tt>--csv --rs lf --fs tab</tt>) at every
pipeline stage.
<!-- ================================================================ -->
<a id="Functions_for_filter_and_put"/><h1>Functions for filter and put</h1>
<p/>
<div class="pokipanel">
<pre>
$ mlr --help-all-functions
+ (class=arithmetic #args=2): Addition.
+ (class=arithmetic #args=1): Unary plus.
- (class=arithmetic #args=2): Subtraction.
- (class=arithmetic #args=1): Unary minus.
* (class=arithmetic #args=2): Multiplication.
/ (class=arithmetic #args=2): Division.
// (class=arithmetic #args=2): Integer division: rounds to negative (pythonic).
% (class=arithmetic #args=2): Remainder; never negative-valued (pythonic).
** (class=arithmetic #args=2): Exponentiation; same as pow, but as an infix
operator.
| (class=arithmetic #args=2): Bitwise OR.
^ (class=arithmetic #args=2): Bitwise XOR.
&amp; (class=arithmetic #args=2): Bitwise AND.
~ (class=arithmetic #args=1): Bitwise NOT. Beware '$y=~$x' since =~ is the
regex-match operator: try '$y = ~$x'.
&lt;&lt; (class=arithmetic #args=2): Bitwise left-shift.
&gt;&gt; (class=arithmetic #args=2): Bitwise right-shift.
== (class=boolean #args=2): String/numeric equality. Mixing number and string
results in string compare.
!= (class=boolean #args=2): String/numeric inequality. Mixing number and string
results in string compare.
=~ (class=boolean #args=2): String (left-hand side) matches regex (right-hand
side), e.g. '$name =~ "^a.*b$"'.
!=~ (class=boolean #args=2): String (left-hand side) does not match regex
(right-hand side), e.g. '$name !=~ "^a.*b$"'.
&gt; (class=boolean #args=2): String/numeric greater-than. Mixing number and string
results in string compare.
&gt;= (class=boolean #args=2): String/numeric greater-than-or-equals. Mixing number
and string results in string compare.
&lt; (class=boolean #args=2): String/numeric less-than. Mixing number and string
results in string compare.
&lt;= (class=boolean #args=2): String/numeric less-than-or-equals. Mixing number
and string results in string compare.
&amp;&amp; (class=boolean #args=2): Logical AND.
|| (class=boolean #args=2): Logical OR.
^^ (class=boolean #args=2): Logical XOR.
! (class=boolean #args=1): Logical negation.
boolean (class=conversion #args=1): Convert int/float/bool/string to boolean.
float (class=conversion #args=1): Convert int/float/bool/string to float.
fmtnum (class=conversion #args=2): Convert int/float/bool to string using
printf-style format string, e.g. "%06lld".
hexfmt (class=conversion #args=1): Convert int to string, e.g. 255 to "0xff".
int (class=conversion #args=1): Convert int/float/bool/string to int.
string (class=conversion #args=1): Convert int/float/bool/string to string.
. (class=string #args=2): String concatenation.
gsub (class=string #args=3): Example: '$name=gsub($name, "old", "new")'
(replace all).
strlen (class=string #args=1): String length.
sub (class=string #args=3): Example: '$name=sub($name, "old", "new")'
(replace once).
tolower (class=string #args=1): Convert string to lowercase.
toupper (class=string #args=1): Convert string to uppercase.
abs (class=math #args=1): Absolute value.
acos (class=math #args=1): Inverse trigonometric cosine.
acosh (class=math #args=1): Inverse hyperbolic cosine.
asin (class=math #args=1): Inverse trigonometric sine.
asinh (class=math #args=1): Inverse hyperbolic sine.
atan (class=math #args=1): One-argument arctangent.
atan2 (class=math #args=2): Two-argument arctangent.
atanh (class=math #args=1): Inverse hyperbolic tangent.
cbrt (class=math #args=1): Cube root.
ceil (class=math #args=1): Ceiling: nearest integer at or above.
cos (class=math #args=1): Trigonometric cosine.
cosh (class=math #args=1): Hyperbolic cosine.
erf (class=math #args=1): Error function.
erfc (class=math #args=1): Complementary error function.
exp (class=math #args=1): Exponential function e**x.
expm1 (class=math #args=1): e**x - 1.
floor (class=math #args=1): Floor: nearest integer at or below.
invqnorm (class=math #args=1): Inverse of normal cumulative distribution
function. Note that invqorm(urand()) is normally distributed.
log (class=math #args=1): Natural (base-e) logarithm.
log10 (class=math #args=1): Base-10 logarithm.
log1p (class=math #args=1): log(1-x).
logifit (class=math #args=3): Given m and b from logistic regression, compute
fit: $yhat=logifit($x,$m,$b).
madd (class=math #args=3): a + b mod m (integers)
max (class=math #args=2): max of two numbers; null loses
mexp (class=math #args=3): a ** b mod m (integers)
min (class=math #args=2): min of two numbers; null loses
mmul (class=math #args=3): a * b mod m (integers)
msub (class=math #args=3): a - b mod m (integers)
pow (class=math #args=2): Exponentiation; same as **.
qnorm (class=math #args=1): Normal cumulative distribution function.
round (class=math #args=1): Round to nearest integer.
roundm (class=math #args=2): Round to nearest multiple of m: roundm($x,$m) is
the same as round($x/$m)*$m
sgn (class=math #args=1): +1 for positive input, 0 for zero input, -1 for
negative input.
sin (class=math #args=1): Trigonometric sine.
sinh (class=math #args=1): Hyperbolic sine.
sqrt (class=math #args=1): Square root.
tan (class=math #args=1): Trigonometric tangent.
tanh (class=math #args=1): Hyperbolic tangent.
urand (class=math #args=0): Floating-point numbers on the unit interval.
Int-valued example: '$n=floor(20+urand()*11)'.
urand32 (class=math #args=0): Integer uniformly distributed 0 and 2**32-1
inclusive.
urandint (class=math #args=2): Integer uniformly distributed between inclusive
integer endpoints.
dhms2fsec (class=time #args=1): Recovers floating-point seconds as in
dhms2fsec("5d18h53m20.250000s") = 500000.250000
dhms2sec (class=time #args=1): Recovers integer seconds as in
dhms2sec("5d18h53m20s") = 500000
fsec2dhms (class=time #args=1): Formats floating-point seconds as in
fsec2dhms(500000.25) = "5d18h53m20.250000s"
fsec2hms (class=time #args=1): Formats floating-point seconds as in
fsec2hms(5000.25) = "01:23:20.250000"
gmt2sec (class=time #args=1): Parses GMT timestamp as integer seconds since
the epoch.
hms2fsec (class=time #args=1): Recovers floating-point seconds as in
hms2fsec("01:23:20.250000") = 5000.250000
hms2sec (class=time #args=1): Recovers integer seconds as in
hms2sec("01:23:20") = 5000
sec2dhms (class=time #args=1): Formats integer seconds as in sec2dhms(500000)
= "5d18h53m20s"
sec2gmt (class=time #args=1): Formats seconds since epoch (integer part)
as GMT timestamp, e.g. sec2gmt(1440768801.7) = "2015-08-28T13:33:21Z".
sec2hms (class=time #args=1): Formats integer seconds as in
sec2hms(5000) = "01:23:20"
strftime (class=time #args=2): Formats seconds since epoch (integer part)
as timestamp, e.g.
strftime(1440768801.7,"%Y-%m-%dT%H:%M:%SZ") = "2015-08-28T13:33:21Z".
strptime (class=time #args=2): Parses timestamp as integer seconds since epoch,
e.g. strptime("2015-08-28T13:33:21Z","%Y-%m-%dT%H:%M:%SZ") = 1440768801.
systime (class=time #args=0): Floating-point seconds since the epoch,
e.g. 1440768801.748936.
To set the seed for urand, you may specify decimal or hexadecimal 32-bit
numbers of the form "mlr --seed 123456789" or "mlr --seed 0xcafefeed".
Miller's built-in variables are NF, NR, FNR, FILENUM, and FILENAME (awk-like)
along with the mathematical constants PI and E.
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="Operator_precedence"/><h1>Operator precedence</h1>
<p/>Operators are listed in order of decreasing precedence, highest first.
<p/>
<div class="pokipanel">
<pre>
Operators Associativity
--------- -------------
() left to right
** right to left
! ~ unary+ unary- &amp; right to left
binary* / // % left to right
binary+ binary- . left to right
&lt;&lt; &gt;&gt; left to right
&amp; left to right
^ left to right
| left to right
&lt; &lt;= &gt; &gt;= left to right
== != =~ !=~ left to right
&amp;&amp; left to right
^^ left to right
|| left to right
= N/A for Miller (there is no $a=$b=$c)
</pre>
</div>
<p/>
<!-- ================================================================ -->
<a id="Operator_and_function_semantics"/><h1>Operator and function semantics</h1>
<ul>
<li/> Functions are in general pass-throughs straight to the system-standard C
library.
<li/> The <tt>min</tt> and <tt>max</tt> functions are different from other
multi-argument functions which return null if any of their inputs are null: for
<tt>min</tt> and <tt>max</tt>, by contrast, if one argument is null, the other
is returned.
<li/> Symmetrically with respect to the bitwise OR, XOR, and AND operators
<tt>|</tt>, <tt>^</tt>, <tt>&amp;</tt>, Miller has logical operators
<tt>||</tt>, <tt>^^</tt>, <tt>&amp;&amp;</tt>: the logical XOR not existing in
C.
<li/> The exponentiation operator <tt>**</tt> is familiar from many languages.
<li/> The regex-match and regex-not-match operators <tt>=~</tt> and
<tt>!=~</tt> are similar to those in Ruby and Perl.
</ul>
<!-- ================================================================ -->
<a id="Arithmetic"/><h1>Arithmetic</h1>
<a id="Input_scanning"/><h2>Input scanning</h2>
<p/>Numbers in Miller are double-precision float or 64-bit signed integers.
Anything scannable as int, e.g <tt>123</tt> or <tt>0xabcd</tt>, is treated as
an integer; otherwise, input scannable as float (<tt>4.56</tt> or <tt>8e9</tt>)
is treated as float; everything else is a string.
<p/>If you want all numbers to be treated as floats, then you may use
<tt>float()</tt> in your filter/put expressions (e.g. replacing <tt>$c = $a *
$b</tt> with <tt>$c = float($a) * float($b)</tt>) &mdash; or, more simply, use
<tt>mlr filter -f</tt> and <tt>mlr put -f</tt> which forces all numeric input,
whether from expression literals or field values, to float.
<a id="Conversion_by_math_routines"/><h2>Conversion by math routines</h2>
<p/>For most math functions, integers are cast to float on input, and produce
float output: e.g. <tt>exp(0) = 1.0</tt> rather than <tt>1</tt>. The
following, however, produce integer output if their inputs are integers:
<tt>+</tt> <tt>-</tt> <tt>*</tt> <tt>/</tt> <tt>//</tt> <tt>%</tt> <tt>abs</tt>
<tt>ceil</tt> <tt>floor</tt> <tt>max</tt> <tt>min</tt> <tt>round</tt>
<tt>roundm</tt> <tt>sgn</tt>.
<a id="Conversion_by_arithmetic_operators"/><h2>Conversion by arithmetic operators</h2>
<p/>The sum, difference, and product of integers is again integer, except for
when that would overflow a 64-bit integer at which point Miller converts the
result to float.
<p/>The short of it is that Miller does this transparently for you so you
needn&rsquo;t think about it.
<p/>Implementation details of this, for the interested: integer adds and
subtracts overflow by at most one bit so it suffices to check sign-changes.
Thus, Miller allows you to add and subtract arbitrary 64-bit signed integers,
converting only to float precisely when the result is less than -2<sup>63</sup>
or greater than 2<sup>63</sup>-1. Multiplies, on the other hand, can overflow
by a word size and a sign-change technique does not suffice to detect overflow.
Instead Miller tests whether the floating-point product exceeds the
representable integer range. Now, 64-bit integers have 64-bit precision while
IEEE-doubles have only 52-bit mantissas &mdash; so, there are 53 bits including
implicit leading one. The following experiment explicitly demonstrates the
resolution at this range:
<div class=pokipanel>
<pre>
64-bit integer 64-bit integer Casted to double Back to 64-bit
in hex in decimal integer
0x7ffffffffffff9ff 9223372036854774271 9223372036854773760.000000 0x7ffffffffffff800
0x7ffffffffffffa00 9223372036854774272 9223372036854773760.000000 0x7ffffffffffff800
0x7ffffffffffffbff 9223372036854774783 9223372036854774784.000000 0x7ffffffffffffc00
0x7ffffffffffffc00 9223372036854774784 9223372036854774784.000000 0x7ffffffffffffc00
0x7ffffffffffffdff 9223372036854775295 9223372036854774784.000000 0x7ffffffffffffc00
0x7ffffffffffffe00 9223372036854775296 9223372036854775808.000000 0x8000000000000000
0x7ffffffffffffffe 9223372036854775806 9223372036854775808.000000 0x8000000000000000
0x7fffffffffffffff 9223372036854775807 9223372036854775808.000000 0x8000000000000000
</pre>
</div>
<p/>That is, one cannot check an integer product to see if it is precisely
greater than 2<sup>63</sup>-1 or less than -2<sup>63</sup> using either integer
arithmetic (it may have already overflowed) or using double-precision (due to
granularity). Instead Miller checks for overflow in 64-bit integer
multiplication by seeing whether the absolute value of the double-precision
product exceeds the largest representable IEEE double less than 2<sup>63</sup>,
which we see from the listing above is 9223372036854774784. (An alternative
would be to do all integer multiplies using handcrafted multi-word 128-bit
arithmetic. This approach is not taken.)
<a id="Pythonic_division"/><h2>Pythonic division</h2>
<p/>Division and remainder are
<a href="http://python-history.blogspot.com/2010/08/why-pythons-integer-division-floors.html">
pythonic</a>:
<ul>
<li/> Quotient of integers is floating-point: <tt>7/2</tt> is <tt>3.5</tt>.
<li/> Integer division is done with <tt>//</tt>: <tt>7/2</tt> is <tt>3</tt>.
This rounds toward the negative.
<li/> Remainders are non-negative.
</ul>
<!-- ================================================================ -->
<a id="Regular_expressions"/><h1>Regular expressions</h1>
<p/>Miller lets you use regular expressions (of type POSIX.2) in the following contexts:
<ul>
<li/> In <tt>mlr filter</tt> with <tt>=~</tt> or <tt>!=~</tt>, e.g. <tt>mlr
filter '$url =~ "http.*com"'</tt>
<li/> In <tt>mlr put</tt> with <tt>sub</tt> or <tt>gsub</tt>, e.g. <tt>mlr put
'$url = sub($url, "http.*com", "")'</tt>
<li/> In <tt>mlr having-fields</tt>, e.g. <tt>mlr having-fields
--any-matching '^sda[0-9]'</tt>
<li/> In <tt>mlr cut</tt>, e.g. <tt>mlr cut -r -f '^status$,^sda[0-9]'</tt>
<li/> In <tt>mlr rename</tt>, e.g. <tt>mlr rename -r '^(sda[0-9]).*$,dev/\1'</tt>
<li/> In <tt>mlr grep</tt>, e.g. <tt>mlr --csv grep 00188555487 myfiles*.csv</tt>
</ul>
<p/>The <tt>i</tt> after the double-quoted regular-expression string is used to
signify case-insensitive match.
<p/>For <tt>filter</tt> and <tt>put</tt>, if the regular expression is a string
literal (the normal case), it is precompiled at process start and reused
thereafter, which is efficient. If the regular expression is a more complex
expression, including string concatenation using <tt>.</tt>, or a column name
(in which case you can take regular expressions from input data!), then regexes
are compiled on each record which works but is less efficient. As well, in this
case there is no way to specify case-insensitive matching.
<p/>Example:
<p/>
<div class="pokipanel">
<pre>
$ cat data/regex-in-data.dat
name=jane,regex=^j.*e$
name=bill,regex=^b[ou]ll$
name=bull,regex=^b[ou]ll$
</pre>
</div>
<p/>
<p/>
<div class="pokipanel">
<pre>
$ mlr filter '$name =~ $regex' data/regex-in-data.dat
name=jane,regex=^j.*e$
name=bull,regex=^b[ou]ll$
</pre>
</div>
<p/>
</div>
</td>
</table>
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