Miller in 10 minutes

Obtaining Miller

You can install Miller for various platforms as follows:

  • Linux: yum install miller or apt-get install miller depending on your flavor of Linux

  • MacOS: brew install miller or port install miller depending on your preference of Homebrew or MacPorts.

  • Windows: choco install miller using Chocolatey.

  • You can get latest builds for Linux, MacOS, and Windows by visiting https://github.com/johnkerl/miller/actions, selecting the latest build, and clicking _Artifacts_. (These are retained for 5 days after each commit.)

  • See also Building from source if you prefer – in particular, if your platform’s package manager doesn’t have the latest release.

As a first check, you should be able to run mlr --version at your system’s command prompt and see something like the following:

 mlr --version
 Miller v6.0.0-dev

As a second check, given (example.csv) you should be able to do

 mlr --csv cat example.csv
 color,shape,flag,index,quantity,rate
 yellow,triangle,true,11,43.6498,9.8870
 red,square,true,15,79.2778,0.0130
 red,circle,true,16,13.8103,2.9010
 red,square,false,48,77.5542,7.4670
 purple,triangle,false,51,81.2290,8.5910
 red,square,false,64,77.1991,9.5310
 purple,triangle,false,65,80.1405,5.8240
 yellow,circle,true,73,63.9785,4.2370
 yellow,circle,true,87,63.5058,8.3350
 purple,square,false,91,72.3735,8.2430
 mlr --icsv --opprint cat example.csv
 color  shape    flag  index quantity rate
 yellow triangle true  11    43.6498  9.8870
 red    square   true  15    79.2778  0.0130
 red    circle   true  16    13.8103  2.9010
 red    square   false 48    77.5542  7.4670
 purple triangle false 51    81.2290  8.5910
 red    square   false 64    77.1991  9.5310
 purple triangle false 65    80.1405  5.8240
 yellow circle   true  73    63.9785  4.2370
 yellow circle   true  87    63.5058  8.3350
 purple square   false 91    72.3735  8.2430

If you run into issues on these checks, please check out the resources on the Community page for help.

Miller verbs

Let’s take a quick look at some of the most useful Miller verbs – file-format-aware, name-index-empowered equivalents of standard system commands.

mlr cat is like system cat (or type on Windows) – it passes the data through unmodified:

 mlr --csv cat example.csv
 color,shape,flag,index,quantity,rate
 yellow,triangle,true,11,43.6498,9.8870
 red,square,true,15,79.2778,0.0130
 red,circle,true,16,13.8103,2.9010
 red,square,false,48,77.5542,7.4670
 purple,triangle,false,51,81.2290,8.5910
 red,square,false,64,77.1991,9.5310
 purple,triangle,false,65,80.1405,5.8240
 yellow,circle,true,73,63.9785,4.2370
 yellow,circle,true,87,63.5058,8.3350
 purple,square,false,91,72.3735,8.2430

But mlr cat can also do format conversion – for example, you can pretty-print in tabular format:

 mlr --icsv --opprint cat example.csv
 color  shape    flag  index quantity rate
 yellow triangle true  11    43.6498  9.8870
 red    square   true  15    79.2778  0.0130
 red    circle   true  16    13.8103  2.9010
 red    square   false 48    77.5542  7.4670
 purple triangle false 51    81.2290  8.5910
 red    square   false 64    77.1991  9.5310
 purple triangle false 65    80.1405  5.8240
 yellow circle   true  73    63.9785  4.2370
 yellow circle   true  87    63.5058  8.3350
 purple square   false 91    72.3735  8.2430

mlr head and mlr tail count records rather than lines. Whether you’re getting the first few records or the last few, the CSV header is included either way:

 mlr --csv head -n 4 example.csv
 color,shape,flag,index,quantity,rate
 yellow,triangle,true,11,43.6498,9.8870
 red,square,true,15,79.2778,0.0130
 red,circle,true,16,13.8103,2.9010
 red,square,false,48,77.5542,7.4670
 mlr --csv tail -n 4 example.csv
 color,shape,flag,index,quantity,rate
 purple,triangle,false,65,80.1405,5.8240
 yellow,circle,true,73,63.9785,4.2370
 yellow,circle,true,87,63.5058,8.3350
 purple,square,false,91,72.3735,8.2430
 mlr --icsv --ojson tail -n 2 example.csv
 {
   "color": "yellow",
   "shape": "circle",
   "flag": true,
   "index": 87,
   "quantity": 63.5058,
   "rate": 8.3350
 }
 {
   "color": "purple",
   "shape": "square",
   "flag": false,
   "index": 91,
   "quantity": 72.3735,
   "rate": 8.2430
 }

You can sort on a single field:

 mlr --icsv --opprint sort -f shape example.csv
 color  shape    flag  index quantity rate
 red    circle   true  16    13.8103  2.9010
 yellow circle   true  73    63.9785  4.2370
 yellow circle   true  87    63.5058  8.3350
 red    square   true  15    79.2778  0.0130
 red    square   false 48    77.5542  7.4670
 red    square   false 64    77.1991  9.5310
 purple square   false 91    72.3735  8.2430
 yellow triangle true  11    43.6498  9.8870
 purple triangle false 51    81.2290  8.5910
 purple triangle false 65    80.1405  5.8240

Or, you can sort primarily alphabetically on one field, then secondarily numerically descending on another field, and so on:

 mlr --icsv --opprint sort -f shape -nr index example.csv
 color  shape    flag  index quantity rate
 yellow circle   true  87    63.5058  8.3350
 yellow circle   true  73    63.9785  4.2370
 red    circle   true  16    13.8103  2.9010
 purple square   false 91    72.3735  8.2430
 red    square   false 64    77.1991  9.5310
 red    square   false 48    77.5542  7.4670
 red    square   true  15    79.2778  0.0130
 purple triangle false 65    80.1405  5.8240
 purple triangle false 51    81.2290  8.5910
 yellow triangle true  11    43.6498  9.8870

If there are fields you don’t want to see in your data, you can use cut to keep only the ones you want, in the same order they appeared in the input data:

 mlr --icsv --opprint cut -f flag,shape example.csv
 shape    flag
 triangle true
 square   true
 circle   true
 square   false
 triangle false
 square   false
 triangle false
 circle   true
 circle   true
 square   false

You can also use cut -o to keep specified fields, but in your preferred order:

 mlr --icsv --opprint cut -o -f flag,shape example.csv
 flag  shape
 true  triangle
 true  square
 true  circle
 false square
 false triangle
 false square
 false triangle
 true  circle
 true  circle
 false square

You can use cut -x to omit fields you don’t care about:

 mlr --icsv --opprint cut -x -f flag,shape example.csv
 color  index quantity rate
 yellow 11    43.6498  9.8870
 red    15    79.2778  0.0130
 red    16    13.8103  2.9010
 red    48    77.5542  7.4670
 purple 51    81.2290  8.5910
 red    64    77.1991  9.5310
 purple 65    80.1405  5.8240
 yellow 73    63.9785  4.2370
 yellow 87    63.5058  8.3350
 purple 91    72.3735  8.2430

You can use filter to keep only records you care about:

 mlr --icsv --opprint filter '$color == "red"' example.csv
 color shape  flag  index quantity rate
 red   square true  15    79.2778  0.0130
 red   circle true  16    13.8103  2.9010
 red   square false 48    77.5542  7.4670
 red   square false 64    77.1991  9.5310
 mlr --icsv --opprint filter '$color == "red" && $flag == true' example.csv
 color shape  flag index quantity rate
 red   square true 15    79.2778  0.0130
 red   circle true 16    13.8103  2.9010

You can use put to create new fields which are computed from other fields:

 mlr --icsv --opprint put '
   $ratio = $quantity / $rate;
   $color_shape = $color . "_" . $shape
 ' example.csv
 color  shape    flag  index quantity rate   ratio              color_shape
 yellow triangle true  11    43.6498  9.8870 4.414868008496004  yellow_triangle
 red    square   true  15    79.2778  0.0130 6098.292307692308  red_square
 red    circle   true  16    13.8103  2.9010 4.760530851430541  red_circle
 red    square   false 48    77.5542  7.4670 10.386259541984733 red_square
 purple triangle false 51    81.2290  8.5910 9.455127458968688  purple_triangle
 red    square   false 64    77.1991  9.5310 8.099790158430384  red_square
 purple triangle false 65    80.1405  5.8240 13.760388049450551 purple_triangle
 yellow circle   true  73    63.9785  4.2370 15.09995279679018  yellow_circle
 yellow circle   true  87    63.5058  8.3350 7.619172165566886  yellow_circle
 purple square   false 91    72.3735  8.2430 8.779995147397793  purple_square

Even though Miller’s main selling point is name-indexing, sometimes you really want to refer to a field name by its positional index. Use $[[3]] to access the name of field 3 or $[[[3]]] to access the value of field 3:

 mlr --icsv --opprint put '$[[3]] = "NEW"' example.csv
 color  shape    NEW   index quantity rate
 yellow triangle true  11    43.6498  9.8870
 red    square   true  15    79.2778  0.0130
 red    circle   true  16    13.8103  2.9010
 red    square   false 48    77.5542  7.4670
 purple triangle false 51    81.2290  8.5910
 red    square   false 64    77.1991  9.5310
 purple triangle false 65    80.1405  5.8240
 yellow circle   true  73    63.9785  4.2370
 yellow circle   true  87    63.5058  8.3350
 purple square   false 91    72.3735  8.2430
 mlr --icsv --opprint put '$[[[3]]] = "NEW"' example.csv
 color  shape    flag index quantity rate
 yellow triangle NEW  11    43.6498  9.8870
 red    square   NEW  15    79.2778  0.0130
 red    circle   NEW  16    13.8103  2.9010
 red    square   NEW  48    77.5542  7.4670
 purple triangle NEW  51    81.2290  8.5910
 red    square   NEW  64    77.1991  9.5310
 purple triangle NEW  65    80.1405  5.8240
 yellow circle   NEW  73    63.9785  4.2370
 yellow circle   NEW  87    63.5058  8.3350
 purple square   NEW  91    72.3735  8.2430

You can find the full list of verbs at the Reference: list of verbs page.

Multiple input files

Miller takes all the files from the command line as an input stream. But it’s format-aware, so it doesn’t repeat CSV header lines. For example, with input files (data/a.csv) and (data/b.csv), the system cat command will repeat header lines:

 cat data/a.csv
 a,b,c
 1,2,3
 4,5,6
 cat data/b.csv
 a,b,c
 7,8,9
 cat data/a.csv data/b.csv
 a,b,c
 1,2,3
 4,5,6
 a,b,c
 7,8,9

However, mlr cat will not:

 mlr --csv cat data/a.csv data/b.csv
 a,b,c
 1,2,3
 4,5,6
 7,8,9

Chaining verbs together

Often we want to chain queries together – for example, sorting by a field and taking the top few values. We can do this using pipes:

 mlr --csv sort -nr index example.csv | mlr --icsv --opprint head -n 3
 color  shape  flag  index quantity rate
 purple square false 91    72.3735  8.2430
 yellow circle true  87    63.5058  8.3350
 yellow circle true  73    63.9785  4.2370

This works fine – but Miller also lets you chain verbs together using the word then. Think of this as a Miller-internal pipe that lets you use fewer keystrokes:

 mlr --icsv --opprint sort -nr index then head -n 3 example.csv
 color  shape  flag  index quantity rate
 purple square false 91    72.3735  8.2430
 yellow circle true  87    63.5058  8.3350
 yellow circle true  73    63.9785  4.2370

As another convenience, you can put the filename first using --from. When you’re interacting with your data at the command line, this makes it easier to up-arrow and append to the previous command:

 mlr --icsv --opprint --from example.csv sort -nr index then head -n 3
 color  shape  flag  index quantity rate
 purple square false 91    72.3735  8.2430
 yellow circle true  87    63.5058  8.3350
 yellow circle true  73    63.9785  4.2370
 mlr --icsv --opprint --from example.csv \
   sort -nr index \
   then head -n 3 \
   then cut -f shape,quantity
 shape  quantity
 square 72.3735
 circle 63.5058
 circle 63.9785

Sorts and stats

Now suppose you want to sort the data on a given column, and then take the top few in that ordering. You can use Miller’s then feature to pipe commands together.

Here are the records with the top three index values:

 mlr --icsv --opprint sort -nr index then head -n 3 example.csv
 color  shape  flag  index quantity rate
 purple square false 91    72.3735  8.2430
 yellow circle true  87    63.5058  8.3350
 yellow circle true  73    63.9785  4.2370

Lots of Miller commands take a -g option for group-by: here, head -n 1 -g shape outputs the first record for each distinct value of the shape field. This means we’re finding the record with highest index field for each distinct shape field:

 mlr --icsv --opprint sort -f shape -nr index then head -n 1 -g shape example.csv
 color  shape    flag  index quantity rate
 yellow circle   true  87    63.5058  8.3350
 purple square   false 91    72.3735  8.2430
 purple triangle false 65    80.1405  5.8240

Statistics can be computed with or without group-by field(s):

 mlr --icsv --opprint --from example.csv \
   stats1 -a count,min,mean,max -f quantity -g shape
 shape    quantity_count quantity_min quantity_mean     quantity_max
 triangle 3              43.6498      68.33976666666666 81.229
 square   4              72.3735      76.60114999999999 79.2778
 circle   3              13.8103      47.0982           63.9785
 mlr --icsv --opprint --from example.csv \
   stats1 -a count,min,mean,max -f quantity -g shape,color
 shape    color  quantity_count quantity_min quantity_mean      quantity_max
 triangle yellow 1              43.6498      43.6498            43.6498
 square   red    3              77.1991      78.01036666666666  79.2778
 circle   red    1              13.8103      13.8103            13.8103
 triangle purple 2              80.1405      80.68475000000001  81.229
 circle   yellow 2              63.5058      63.742149999999995 63.9785
 square   purple 1              72.3735      72.3735            72.3735

If your output has a lot of columns, you can use XTAB format to line things up vertically for you instead:

 mlr --icsv --oxtab --from example.csv \
   stats1 -a p0,p10,p25,p50,p75,p90,p99,p100 -f rate
 rate_p0   0.0130
 rate_p10  2.9010
 rate_p25  4.2370
 rate_p50  8.2430
 rate_p75  8.5910
 rate_p90  9.8870
 rate_p99  9.8870
 rate_p100 9.8870

File formats and format conversion

Miller supports the following formats:

  • CSV (comma-separared values)

  • TSV (tab-separated values)

  • JSON (JavaScript Object Notation)

  • PPRINT (pretty-printed tabular)

  • XTAB (vertical-tabular or sideways-tabular)

  • NIDX (numerically indexed, label-free, with implicit labels "1", "2", etc.)

  • DKVP (delimited key-value pairs).

What’s a CSV file, really? It’s an array of rows, or records, each being a list of key-value pairs, or fields: for CSV it so happens that all the keys are shared in the header line and the values vary from one data line to another.

For example, if you have:

shape,flag,index
circle,1,24
square,0,36

then that’s a way of saying:

shape=circle,flag=1,index=24
shape=square,flag=0,index=36

Other ways to write the same data:

CSV                   PPRINT
shape,flag,index      shape  flag index
circle,1,24           circle 1    24
square,0,36           square 0    36

JSON                  XTAB
{                     shape circle
  "shape": "circle",  flag  1
  "flag": 1,          index 24
  "index": 24         .
}                     shape square
{                     flag  0
  "shape": "square",  index 36
  "flag": 0,
  "index": 36
}

   DKVP
   shape=circle,flag=1,index=24
   shape=square,flag=0,index=36

Anything we can do with CSV input data, we can do with any other format input data. And you can read from one format, do any record-processing, and output to the same format as the input, or to a different output format.

How to specify these to Miller:

  • If you use --csv or --json or --pprint, etc., then Miller will use that format for input and output.

  • If you use --icsv and --ojson (note the extra i and o) then Miller will use CSV for input and JSON for output, etc. See also Keystroke-savers for even shorter options like --c2j.

You can read more about this at the File formats page.

Choices for printing to files

Often we want to print output to the screen. Miller does this by default, as we’ve seen in the previous examples.

Sometimes, though, we want to print output to another file. Just use > outputfilenamegoeshere at the end of your command:

 mlr --icsv --opprint cat example.csv > newfile.csv
 # Output goes to the new file;
 # nothing is printed to the screen.
 cat newfile.csv
 color  shape    flag     index quantity rate
 yellow triangle true     11    43.6498  9.8870
 red    square   true     15    79.2778  0.0130
 red    circle   true     16    13.8103  2.9010
 red    square   false    48    77.5542  7.4670
 purple triangle false    51    81.2290  8.5910
 red    square   false    64    77.1991  9.5310
 purple triangle false    65    80.1405  5.8240
 yellow circle   true     73    63.9785  4.2370
 yellow circle   true     87    63.5058  8.3350
 purple square   false    91    72.3735  8.2430

Other times we just want our files to be changed in-place: just use mlr -I:

 cp example.csv newfile.txt
 cat newfile.txt
 color,shape,flag,index,quantity,rate
 yellow,triangle,true,11,43.6498,9.8870
 red,square,true,15,79.2778,0.0130
 red,circle,true,16,13.8103,2.9010
 red,square,false,48,77.5542,7.4670
 purple,triangle,false,51,81.2290,8.5910
 red,square,false,64,77.1991,9.5310
 purple,triangle,false,65,80.1405,5.8240
 yellow,circle,true,73,63.9785,4.2370
 yellow,circle,true,87,63.5058,8.3350
 purple,square,false,91,72.3735,8.2430
 mlr -I --csv sort -f shape newfile.txt
 cat newfile.txt
 color,shape,flag,index,quantity,rate
 red,circle,true,16,13.8103,2.9010
 yellow,circle,true,73,63.9785,4.2370
 yellow,circle,true,87,63.5058,8.3350
 red,square,true,15,79.2778,0.0130
 red,square,false,48,77.5542,7.4670
 red,square,false,64,77.1991,9.5310
 purple,square,false,91,72.3735,8.2430
 yellow,triangle,true,11,43.6498,9.8870
 purple,triangle,false,51,81.2290,8.5910
 purple,triangle,false,65,80.1405,5.8240

Also using mlr -I you can bulk-operate on lots of files: e.g.:

 mlr -I --csv cut -x -f unwanted_column_name *.csv

If you like, you can first copy off your original data somewhere else, before doing in-place operations.

Lastly, using tee within put, you can split your input data into separate files per one or more field names:

 mlr --csv --from example.csv put -q 'tee > $shape.".csv", $*'
 cat circle.csv
 color,shape,flag,index,quantity,rate
 red,circle,true,16,13.8103,2.9010
 yellow,circle,true,73,63.9785,4.2370
 yellow,circle,true,87,63.5058,8.3350
 cat square.csv
 color,shape,flag,index,quantity,rate
 red,square,true,15,79.2778,0.0130
 red,square,false,48,77.5542,7.4670
 red,square,false,64,77.1991,9.5310
 purple,square,false,91,72.3735,8.2430
 cat triangle.csv
 color,shape,flag,index,quantity,rate
 yellow,triangle,true,11,43.6498,9.8870
 purple,triangle,false,51,81.2290,8.5910
 purple,triangle,false,65,80.1405,5.8240