GNU Datamash 1.8

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This manual is for GNU Datamash (version 1.8, 10 July 2022), which provides command-line computations on input files.

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1 Overview

The datamash program ( performs calculation (e.g. sum,, count, min, max, skewness, standard deviation) on input files.

Example: sum up the values in the first column of the input:

$ seq 10 | datamash sum 1

datamash can group input data and perform operations on each group. It can sort the file, and read header lines.

Example: Given a file with three fields (name, subject, score), find the average score in each subject:

$ cat scores.txt
Name        Subject          Score
Bryan       Arts             68
Isaiah      Arts             80
Gabriel     Health-Medicine  100
Tysza       Business         92
Zackery     Engineering      54

$ datamash --sort --headers --group 2 mean 3 sstdev 3 < scores.txt
GroupBy(Subject)   mean(Score)   sstdev(Score)
Arts               68.9474       10.4215
Business           87.3636       5.18214
Engineering        66.5385       19.8814
Health-Medicine    90.6154       9.22441
Life-Sciences      55.3333       20.606
Social-Sciences    60.2667       17.2273

datamash is designed for interactive exploration of textual data and for automating tasks in shell scripts.

datamash has a rich set of statistical functions to quickly assess information in textual input files. An example of calculating basic statistic (mean, 1st quartile, median, 3rd quartile, IQR, sample-standard-deviation, and p-value of Jarque-Bera test for normal distribution:

$ datamash -H mean 1 q1 1 median 1 q3 1 iqr 1 sstdev 1 jarque 1 < FILE
mean(x)   q1(x)  median(x)  q3(x)   iqr(x)  sstdev(x)  jarque(x)
45.32     23     37         61.5    38.5    30.4487    8.0113-09

2 Invoking datamash

The format for running the datamash program is:

datamash [option]… op1 column1  [op2 column2 …]

Where op1 is the operation to perform on the values in column1. datamash reads input from stdin and performs one or more operations on the input data. If --group is used, each operation is performed on every group. If --group is not used, each operation is performed on all the values in the input file.

The LC_NUMERIC locale specifies the decimal-point character and the thousands separator.

datamash supports the following operations:

Primary operations:

groupby, crosstab, transpose, reverse, check

Line-Filtering operations:


Per-Line operations:

base64, debase64, md5, sha1, sha224, sha256, sha384, sha512, bin, strbin, round, floor, ceil, trunc, frac, dirname, basename, extname, barename, getnum, cut, echo

Group-by Numeric operations:

sum, min, max, absmin, absmax, range

Group-by Textual/Numeric operations:

count, first, last, rand, unique, uniq, collapse, countunique

Group-by Statistical operations:

mean, geomean, harmmean, mode, median, q1, q3, iqr, perc, antimode, pstdev, sstdev, pvar, svar, ms, rms, mad, madraw, sskew, pskew, skurt, pkurt, jarque, dpo, scov, pcov, spearson, ppearson

Grouping options:


Skip comment lines (starting with ’#’ or ’;’ and optional whitespace).


Print entire input line before op results (default: print only the grouped keys). While using this option with non-linewise operations was historically permitted, it never produced very sensible output. Such usage has been deprecated, and in a future release it will result in an error.

-g X[,Y,X]

Group input via fields X[,Y,Z]. By default, fields are separated by TABs. Use --field-separator to change the delimiter character. Input file must be sorted by the same fields X[,Y,Z]. Use --sort to automatically sort the input. If --group is not specified, each operation is performed in the entire input file.


Indicates the first input line is column headers, and should not be used for any calculations.


Print column headers as first line. If the column header names are known (i.e. the input file had a header line, and the command was invoked with --header-in, -H or --headers), prints the operation and the name of the field (e.g. ‘mean(X)’). Otherwise, prints the number operation and the field number (e.g. ‘mean(field-3)’).


Same as ‘--header-in --header-out’. A short option indicating the input file has a header line, and the output should contain a header line as well.


Ignore upper/lower case when comparing text for grouping, sorting, and comparing unique values in the ‘countunique’ and ‘unique’ (or ‘uniq’) operations.


Sort the input before grouping. datamash requires sorted input. If the input is not sorted, using --sort will automatically sort the input before processing it further. Sorting will be performed based on the specified --group parameter, and respecting case --ignore-case option (if used). The following commands are equivalent:

$ cat FILE | sort -k1,1 | datamash --group 1 sum 1
$ cat FILE | datamash --sort --group 1 sum 1

Use the given program to sort instead of the system sort

File Operation options:


Allow lines with varying number of fields. By default, transpose and reverse will fail with an error message unless all input lines have the same number of fields.


When use --no-strict option, missing fields will be filled with this value.

General options:


print numeric values with printf style floating-point FORMAT.

-t x

Use character X instead of TAB as input and output field delimiter. If --output-delimiter is also used, it will override the output field delimiter.


Skip NA or NaN values.


Use character X instead as output field delimiter. This option overrides --field-separator/-t/ --whitespace/-W.

-c x

Use character X instead of comma to delimit items in a ‘collapse’ or ‘unique’ (aka ‘uniq’) list.

-R N

Round numeric output to N decimal places.


Use whitespace (one or more spaces and/or tabs) for field delimiters. Leading whitespace is ignored, trailing whitespace results in an empty field. TAB character will be used as output field separator. If --output-delimiter is also used, it will override the output field delimiter.


End lines with a 0 byte, not newline.


Print an informative help message on standard output and exit successfully.


Print the version number and licensing information of Datamash on standard output and then exit successfully.

3 Available operations in datamash

Primary operations:

alternative syntax for --group


cross-tabulate two fields (also known as ’pivot-tables’)


transpose rows, columns of a text file


reverse fields in each line of a text file


verify tabular structure of input (ensure same number of fields in all lines)

Line-Filtering operation:

remove lines with duplicated key value

Per-Line operations:

encode the field as base64


decode the field as base64. Exit with an error if the field is invalid base64 value which cannot be decoded.


calculates md5 hash of the field


calculates sha1 hash of the field


calculates sha224 hash of the field


calculates sha256 hash of the field


calculates sha384 hash of the field


calculates sha512 hash of the field


extracts the directory name of the field (assuming the field is a file name). Similar to dirname(1).


extracts the base file name of the field (assuming the field is a file name). Similar to basename(1).


extracts the extension of the file name of the field (assuming the field is a file name).


extracts the base file name of the field without the extension (assuming the field is a file name).


extract a number from the field. getnum accepts an optional single letter option ‘n/i/d/p/h/o’ affecting the detected value.


copy input field to output field (similar to cut(1)). When the cut operation is given a list of fields, the fields are copied in the given order (in contrast to cut(1)).


an alias for cut.

Group-by Numeric operations:

sum the of values


minimum value


maximum value


minimum of the absolute values


maximum of the absolute values


range of values (maximum - minimum)

Group-By Textual/Numeric operations:

count number of elements in the group


the first value of the group


the last value of the group


one random value from the group


comma-separated sorted list of unique values


an alias for unique.

--collapse-delimiter can be used to use a different character than comma.


comma-separated list of all input values

--collapse-delimiter can be used to use a different character than comma.


number of unique/distinct values

Group-By Statistical operations:

mean of the values


geometric mean of the values


harmonic mean of the values


trimmed mean of the values


mean square of the values


root mean square of the values


median value


1st quartile value


3rd quartile value


inter-quartile range


percentile value


mode value (most common value)


anti-mode value (least common value)


population standard deviation


sample standard deviation


population variance


sample variance


Median Absolute Deviation, scaled by a constant 1.4826 for normal distributions


Median Absolute Deviation, unscaled


skewness of the (sample) group


skewness of the (population) group


Excess Kurtosis of the (sample) group


Excess Kurtosis of the (population) group


p-value of the Jarque-Beta test for normality


p-value of the D’Agostino-Pearson Omnibus test for normality.

4 Statistical Operations

Equivalent R functions

GNU Datamash is designed to closely follow R project’s ( statistical functions. See the files/operators.R file for the R equivalent code for each of datamash’s operators. When building datamash from source code on your local computer, operators are compared to known results of the equivalent R functions.

5 Usage Examples

5.1 Summary Statistics

The following are examples of using datamash to quickly calculate summary statistics. The examples will use a file with three fields (name, subject, score) representing grades of students:

$ cat scores.txt
Shawn     Arts  65
Marques   Arts  58
Fernando  Arts  78
Paul      Arts  63
Walter    Arts  75

Counting how many students study each subject (subject is the second field in the input file, thus groupby 2):

$ datamash --sort groupby 2 count 2 < scores.txt
Arts            19
Business        11
Engineering     13
Health-Medicine 13
Life-Sciences   12
Social-Sciences 15

Similarly, find the minimum and maximum score in each subject:

$ datamash --sort groupby 2 min 3 max 3 < scores.txt
Arts             46      88
Business         79      94
Engineering      39      99
Health-Medicine  72     100
Life-Sciences    14      91
Social-Sciences  27      90

find the mean and (population) standard deviation in each subject:

$ datamash --sort groupby 2 mean 3 pstdev 3 < scores.txt
Arts              68.947  10.143
Business          87.363   4.940
Engineering       66.538  19.101
Health-Medicine   90.615   8.862
Life-Sciences     55.333  19.728
Social-Sciences   60.266  16.643

Find the median, first, third quartiles and the inter-quartile range in each subject:

$ datamash --sort groupby 2 median 3 q1 3 q3  3 iqr 3  < scores.txt
Arts              71      61.5      75.5     14
Business          87      83        92        9
Engineering       56      51        83       32
Health-Medicine   91      84       100       16
Life-Sciences     58.5    44.25     67.75    23.5
Social-Sciences   62      55        70.5     15.5

See Header Lines and Column Names for examples of dealing with header lines.

5.2 Header Lines and Column Names

Output Header Lines

If the input does not have a header line, use --header-out to add a header in the first line of the output, indicating which operation was performed:

$ datamash --sort --header-out groupby 2 min  3 max 3 < scores.txt
GroupBy(field-2)  min(field-3)  max(field-3)
Arts              46            88
Business          79            94
Engineering       39            99
Health-Medicine   72           100
Life-Sciences     14            91
Social-Sciences   27            90

Skipping Input Header Lines

If the input has a header line (first line containing column names), use --header-in to skip the line:

$ cat scores_h.txt
Name      Major   Score
Shawn     Arts    65
Marques   Arts    58
Fernando  Arts    78
Paul      Arts    63

$ datamash --sort --header-in groupby 2 mean 3 < scores_h.txt
Arts             68.947
Business         87.363
Engineering      66.538
Health-Medicine  90.615
Life-Sciences    55.333
Social-Sciences  60.266

If the header line is not skipped, datamash will show an error (due to strict input validation):

$ datamash groupby 2 mean 3 < scores_h.txt
datamash: invalid numeric value in line 1 field 3: 'Score'

Using Header Lines

Column names in the input header lines can be printed in the output header lines by using --headers (or -H, both are equivalent to --header-in --header-out):

$ datamash --sort --headers groupby 2 mean 3 < scores_h.txt
GroupBy(Major)    mean(Score)
Arts              68.947
Business          87.363
Engineering       66.538
Health-Medicine   90.615
Life-Sciences     55.333
Social-Sciences   60.266

Or in short form (-sH instead of --sort --headers), equivalent to the above command:

$ datamash -sH groupby 2 mean 3

Column Names

When the input file has a header line, column names can be used instead of column numbers. In the example below, Major is used instead of the value 2, and Score is used instead of the value 3:

$ datamash --sort --headers groupby Major mean Score < scores_h.txt
GroupBy(Major)    mean(Score)
Arts              68.947
Business          87.363
Engineering       66.538
Health-Medicine   90.615
Life-Sciences     55.333
Social-Sciences   60.266

datamash will read the first line of the input, and deduce the correct column number based on the given name. If the column name is not found, an error will be printed:

$ datamash --sort --headers groupby 2 mean Foo  < scores_h.txt
datamash: column name 'Foo' not found in input file

Field names must be escaped with a backslash if they start with a digit or contain special characters (dash/minus, colons, commas). Note the interplay between escaping with backslash and shell quoting. The following equivalent command sum the values of a field named ‘FOO-BAR’:

$ datamash -H sum FOO\\-BAR < input.txt
$ datamash -H sum 'FOO\-BAR' < input.txt
$ datamash -H sum "FOO\\-BAR" < input.txt

5.3 Field Delimiters

datamash uses tabs (ASCII character 0x09) as default field delimiters. Use -W to treat one or more consecutive whitespace characters as field delimiters. Use -t, --field-separator to set a custom field delimiter.

The following examples illustrate the various options.

By default, fields are separated by a single tab. Multiple tabs denotes multiple fields (this is consistent with GNU coreutils’ cut):

$ printf '1\t\t2\n' | datamash sum 3
$ printf '1\t\t2\n' | cut -f3

Every tab separates two fields. A line starting with a tab thus starts with an empty field, and a line ending with a tab ends with an empty field.

Using -W, one or more consecutive whitespace characters are treated as a single field delimiter:

$ printf '1  \t  2\n' | datamash -W sum 2
$ printf '1  \t  2\n' | datamash -W sum 3
datamash: invalid input: field 3 requested, line 1 has only 2 fields

With -W, leading whitespace is ignored, but trailing whitespace is significant. A line starting with one or more consecutive whitespace characters followed by a non-whitespace character starts with a non-empty field. A line ending with one or more consecutive whitespace characters ends with an empty field.

Using -t, a custom field delimiter character can be specified. Multiple consecutive delimiters are treated as multiple fields:

$ printf '1,10,,100\n' | datamash -t, sum 4

5.4 Column Ranges

datamash accepts column ranges such as 1,2,3 and 1-3.

Simulating input with multiple columns:

$ seq 100 | paste - - - -
1    2    3    4
5    6    7    8
9   10   11   12
13  14   15   16
17  18   19   20

The following are equivalent:

$ seq 100 | paste - - - - | datamash sum 1 sum 2 sum 3 sum 4
1225  1250   1275   1300

$ seq 100 | paste - - - - | datamash sum 1,2,3,4
1225  1250   1275   1300

$ seq 100 | paste - - - - | datamash sum 1-4
1225  1250   1275   1300

$ seq 100 | paste - - - - | datamash sum 1-3,4
1225  1250   1275   1300

Ranges can be used with multiple operations:

$ seq 100 | paste - - - - | datamash sum 1-4 mean 1-4
1225  1250   1275   1300   49   50   51   52

5.5 Reverse and Transpose


Use transpose to swap rows and columns in a file:

$ cat input.txt
Sample   Year   Count
A        2014   1002
B        2013    990
C        2014   2030
D        2014    599

$ datamash transpose < input.txt
Sample  A       B       C       D
Year    2014    2013    2014    2014
Count   1002    990     2030    599

By default, transpose verifies the input has the same number of fields in each line, and fails with an error otherwise:

$ cat input.txt
Sample   Year   Count
A        2014   1002
B        2013
C        2014   2030
D        2014    599

$ datamash transpose < input1.txt
datamash: transpose input error: line 3 has 2 fields (previous lines had 3);
see --help to disable strict mode

Use --no-strict to allow missing values:

$ datamash --no-strict transpose < input1.txt
Sample  A       B        C        D
Year    2014    2013     2014     2014
Count   1002    N/A      2030     599

Use --filler to set the missing-field filler value:

$ datamash --no-strict --filler XYZ transpose < input1.txt
Sample  A       B        C        D
Year    2014    2013     2014     2014
Count   1002    XYZ      2030     599


Use reverse to reverse the fields order in a file:

$ cat input.txt
Sample   Year   Count
A        2014   1002
B        2013    990
C        2014   2030
D        2014    599

$ datamash reverse < input.txt
Count   Year    Sample
1002    2014    A
990     2013    B
2030    2014    C
599     2014    D

By default, reverse verifies the input has the same number of fields in each line, and fails with an error otherwise. Use --no-strict to disable this behavior (see section above for an example).

Combining Reverse and Transpose

Reverse and Transpose can be combined to achieve various manipulations. (reminder: tac can be used to reverse lines in a file):

$ cat input.txt
A       1       xx
B       2       yy
C       3       zz

$ tac input.txt
C       3       zz
B       2       yy
A       1       xx

$ tac input.txt | datamash reverse
zz      3       C
yy      2       B
xx      1       A

$ cat input.txt | datamash reverse | datamash transpose
xx      yy      zz
1       2       3
A       B       C

$ tac input.txt | datamash reverse | datamash transpose
zz      yy      xx
3       2       1
C       B       A

5.6 Groupby on /etc/passwd

datamash with the groupby operation mode can be used to aggregate information.

Using this simulated /etc/passwd file as input:

$ cat passwd
list:x:38:38:Mailing List Manager:/var/list:/usr/sbin/nologin
mysql:x:115:124:MySQL Server,,,:/var/lib/mysql:/bin/false
gordon:x:1004:1000:Assaf Gordon,,,,:/home/gordon:/bin/bash
postgres:x:119:126:PostgreSQL administrator,,,:/var/lib/postgresql:/bin/bash
rabbitmq:x:125:138:RabbitMQ messaging server,,,:/var/lib/rabbitmq:/bin/false
redis:x:126:140:redis server,,,:/var/lib/redis:/bin/false

Parameter -t is used to indicate the field separator : (instead of the default tab).

Aggregate (groupby) login shells (column 7) and count how many users use each:

$ datamash -t: --sort groupby 7 count 7 < passwd

Aggregate (groupby) login shells (column 7) and print comma-separated list of users (column 1) for each shell (collapse):

$ cat passwd | datamash -t: --sort groupby 7 collapse 1
/usr/sbin/nologin:daemon,bin,sys,games,man,lp,mail,news,uucp,proxy ,www-data,backup,list,sshd

Aggregate unix-groups (column 4) and print comma-separated list of users (column 1) for in each group:

$ datamash -t: --sort groupby 4 collapse 1 < /etc/passwd

5.7 Check - checking tabular structure

datamash check validates the tabular structure of a file, ensuring all lines have the same number of fields. check is meant to be used in scripting and automation pipelines, as it will terminate with non-zero exit code if the file is not well structured, while also printing detailed context information about the offending lines:

$ cat good.txt
A    1    ww
B    2    xx
C    3    yy
D    4    zz

$ cat bad.txt
A    1    ww
B    2    xx
C    3
D    4    zz

$ datamash check < good.txt && echo ok || echo fail
4 lines, 3 fields

$ datamash check < bad.txt && echo ok || echo fail
line 2 (3 fields):
  B  2 xx
line 3 (2 fields):
  C  3
datamash: check failed: line 3 has 2 fields (previous line had 3)

5.7.1 Expected number of lines/fields

check accepts optional lines and fields and will return failure if the input does not have the requested number of lines/fields.

The syntax is:

datamash check [N lines] [N fields]

Usage examples:

$ cat file.txt
A    1    ww
B    2    xx
C    3    yy
D    4    zz

$ datamash check 4 lines < file.txt && echo ok
4 lines, 3 fields

$ datamash check 3 fields < file.txt && echo ok
4 lines, 3 fields

$ datamash check 4 lines 3 fields < file.txt && echo ok
4 lines, 3 fields

$ datamash check 7 fields < file.txt && echo ok
line 1 (3 fields):
  A    1    ww
datamash: check failed: line 1 has 3 fields (expecting 22)

$ datamash check 10 lines < file.txt && echo ok
datamash: check failed: input had 4 lines (expecting 10)

For convenience, line,row,rows can be used instead of lines; field,columns,column,col can be used instead of fields. The following are all equivalent:

datamash check 4 lines 10 fields < file.txt
datamash check 4 rows  10 columns < file.txt
datamash check 10 col 4 row < file.txt

5.7.2 checks in automation scripts

In pipeline/automation context, it is often beneficial to validate files as early as possible (immediately after file is created, as in fail-fast methodology). A typical usage in a shell script would be:


    base=$(basename "$0")
    echo "$base: error: $@" >&2
    exit 1

custom pipeline-or-program > output.txt \
    || die "program failed"

datamash check < output.txt \
    || die "'output.txt' has invalid structure (missing fields)"

If the generated output.txt file has invalid structure (i.e. missing fields), datamash will print the stderr enough details to help in troubleshooting (line numbers and offending line’s content).

5.8 Crosstab - Cross-Tabulation (pivot-tables)

Cross-tabulation compares the relationship between two fields. Given the following input file:

$ cat input.txt
a    x    3
a    y    7
b    x    21
a    x    40

Show cross-tabulation between the first field (a/b) and the second field (x/y) - counting how many times each pair appears (note: sorting is required):

$ datamash -s crosstab 1,2 < input.txt
     x    y
a    2    1
b    1    N/A

The default operation is count - in the above example, a and x appear twice in the input file, while b and y never appear together.

An optional grouping operation can be used instead of counting.

For each pair, sum the values in the third column:

$ datamash -s crosstab 1,2 sum 3 < input.txt
     x    y
a    43   7
b    21   N/A

For each pair, list all unique values in the third column:

$ datamash -s crosstab 1,2 unique 3 < input.txt
     x    y
a    3,40 7
b    21   N/A

Note that using --header-out with crosstab prints a line showing how to interpret the rows and columns, and what operation was used.

$ datamash -s --header-in --header-out crosstab 1,2 < input.txt
GroupBy(a) GroupBy(x) count(a)
     x    y
a    1    1
b    1    N/A

5.9 Rounding numbers

The following demonstrate the different rounding operations:

$ ( echo X ; seq -1.25 0.25 1.25 ) \
      | datamash --full -H round 1 ceil 1 floor 1 trunc 1 frac 1

  X     round(X)  ceil(X)  floor(X)  trunc(X)   frac(X)
-1.25   -1        -1       -2        -1         -0.25
-1.00   -1        -1       -1        -1          0
-0.75   -1         0       -1         0         -0.75
-0.50   -1         0       -1         0         -0.5
-0.25    0         0       -1         0         -0.25
 0.00    0         0        0         0          0
 0.25    0         1        0         0          0.25
 0.50    1         1        0         0          0.5
 0.75    1         1        0         0          0.75
 1.00    1         1        1         1          0
 1.25    1         2        1         1          0.25

5.10 Binning numbers

Bin input values into buckets of size 5:

$ ( echo X ; seq -10 2.5 10 ) \
      | datamash -H --full bin:5 1
    X  bin(X)
-10.0    -10
 -7.5    -10
 -5.0     -5
 -2.5     -5
  0.0      0
  2.5      0
  5.0      5
  7.5      5
 10.0     10

5.11 Binning strings

Hash any string input value into a numeric integer. A typical usage would be to split an input file into N chunks, ensuring that all values of a certain key will be stored in the same chunk:

$ cat input.txt
PatientA   10
PatientB   11
PatientC   12
PatientA   14
PatientC   15

Each patient ID is hashed into a bin between 0 and 9 and printed in the last field:

$ datamash --full strbin 1 < input.txt
PatientA   10    5
PatientB   11    6
PatientC   12    7
PatientA   14    5
PatientC   15    7

Splitting the input into chunks can be done with awk:

$ cat input.txt | datamash --full strbin 1 \
    | awk '{print > $NF ".txt"}'

5.12 Extracting numeric values - using getnum

The getnum operation extracts a numeric value from the field:

$ echo zoom-123.45xyz | datamash getnum 1

getnum accepts an optional single-letter TYPE option:


natural numbers (positive integers, including zero)




decimal point numbers


positive decimal point numbers (this is the default)


hex numbers


octal numbers


$ echo zoom-123.45xyz | datamash getnum 1

$ echo zoom-123.45xyz | datamash getnum:n 1

$ echo zoom-123.45xyz | datamash getnum:i 1

$ echo zoom-123.45xyz | datamash getnum:d 1

$ echo zoom-123.45xyz | datamash getnum:p 1

# Hex 0x123 = 291 Decimal
$ echo zoom-123.45xyz | datamash getnum:h 1

# Octal 0123 = 83 Decimal
$ echo zoom-123.45xyz | datamash getnum:o 1

6 Reporting bugs

To report bugs, suggest enhancements or otherwise discuss GNU Datamash, please send electronic mail to

For bug reports, please include enough information for the maintainers to reproduce the problem. Generally speaking, that means:

When in doubt whether something is needed or not, include it. It’s better to include too much than to leave out something important.

Patches are welcome; if possible, please make them with ‘diff -u’ (see Overview in Comparing and Merging Files) and include ChangeLog entries (see Change Log in The GNU Emacs Manual). Please follow the existing coding style.

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Appendix A GNU Free Documentation License

Version 1.3, 3 November 2008
Copyright © 2000, 2001, 2002, 2007, 2008 Free Software Foundation, Inc.

Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.

    The purpose of this License is to make a manual, textbook, or other functional and useful document free in the sense of freedom: to assure everyone the effective freedom to copy and redistribute it, with or without modifying it, either commercially or noncommercially. Secondarily, this License preserves for the author and publisher a way to get credit for their work, while not being considered responsible for modifications made by others.

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    You may make a collection consisting of the Document and other documents released under this License, and replace the individual copies of this License in the various documents with a single copy that is included in the collection, provided that you follow the rules of this License for verbatim copying of each of the documents in all other respects.

    You may extract a single document from such a collection, and distribute it individually under this License, provided you insert a copy of this License into the extracted document, and follow this License in all other respects regarding verbatim copying of that document.


    A compilation of the Document or its derivatives with other separate and independent documents or works, in or on a volume of a storage or distribution medium, is called an “aggregate” if the copyright resulting from the compilation is not used to limit the legal rights of the compilation’s users beyond what the individual works permit. When the Document is included in an aggregate, this License does not apply to the other works in the aggregate which are not themselves derivative works of the Document.

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    Translation is considered a kind of modification, so you may distribute translations of the Document under the terms of section 4. Replacing Invariant Sections with translations requires special permission from their copyright holders, but you may include translations of some or all Invariant Sections in addition to the original versions of these Invariant Sections. You may include a translation of this License, and all the license notices in the Document, and any Warranty Disclaimers, provided that you also include the original English version of this License and the original versions of those notices and disclaimers. In case of a disagreement between the translation and the original version of this License or a notice or disclaimer, the original version will prevail.

    If a section in the Document is Entitled “Acknowledgements”, “Dedications”, or “History”, the requirement (section 4) to Preserve its Title (section 1) will typically require changing the actual title.


    You may not copy, modify, sublicense, or distribute the Document except as expressly provided under this License. Any attempt otherwise to copy, modify, sublicense, or distribute it is void, and will automatically terminate your rights under this License.

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    Termination of your rights under this section does not terminate the licenses of parties who have received copies or rights from you under this License. If your rights have been terminated and not permanently reinstated, receipt of a copy of some or all of the same material does not give you any rights to use it.


    The Free Software Foundation may publish new, revised versions of the GNU Free Documentation License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns. See

    Each version of the License is given a distinguishing version number. If the Document specifies that a particular numbered version of this License “or any later version” applies to it, you have the option of following the terms and conditions either of that specified version or of any later version that has been published (not as a draft) by the Free Software Foundation. If the Document does not specify a version number of this License, you may choose any version ever published (not as a draft) by the Free Software Foundation. If the Document specifies that a proxy can decide which future versions of this License can be used, that proxy’s public statement of acceptance of a version permanently authorizes you to choose that version for the Document.


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    An MMC is “eligible for relicensing” if it is licensed under this License, and if all works that were first published under this License somewhere other than this MMC, and subsequently incorporated in whole or in part into the MMC, (1) had no cover texts or invariant sections, and (2) were thus incorporated prior to November 1, 2008.

    The operator of an MMC Site may republish an MMC contained in the site under CC-BY-SA on the same site at any time before August 1, 2009, provided the MMC is eligible for relicensing.

ADDENDUM: How to use this License for your documents

To use this License in a document you have written, include a copy of the License in the document and put the following copyright and license notices just after the title page:

  Copyright (C)  year  your name.
  Permission is granted to copy, distribute and/or modify this document
  under the terms of the GNU Free Documentation License, Version 1.3
  or any later version published by the Free Software Foundation;
  with no Invariant Sections, no Front-Cover Texts, and no Back-Cover
  Texts.  A copy of the license is included in the section entitled ``GNU
  Free Documentation License''.

If you have Invariant Sections, Front-Cover Texts and Back-Cover Texts, replace the “with…Texts.” line with this:

    with the Invariant Sections being list their titles, with
    the Front-Cover Texts being list, and with the Back-Cover Texts
    being list.

If you have Invariant Sections without Cover Texts, or some other combination of the three, merge those two alternatives to suit the situation.

If your document contains nontrivial examples of program code, we recommend releasing these examples in parallel under your choice of free software license, such as the GNU General Public License, to permit their use in free software.

Concept index

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Index Entry  Section

--collapse-delimiter: Invoking datamash
--field-separator: Invoking datamash
--field-separator: Groupby on /etc/passwd
--filler: Invoking datamash
--filler: Reverse and Transpose
--format: Invoking datamash
--full: Invoking datamash
--group: Invoking datamash
--header-in: Invoking datamash
--header-in: Header Lines and Column Names
--header-out: Invoking datamash
--header-out: Header Lines and Column Names
--header-out: Crosstab
--headers: Invoking datamash
--headers: Header Lines and Column Names
--help: Invoking datamash
--ignore-case: Invoking datamash
--narm: Invoking datamash
--no-strict: Invoking datamash
--no-strict: Reverse and Transpose
--output-delimiter: Invoking datamash
--round: Invoking datamash
--skip-comments: Invoking datamash
--sort: Invoking datamash
--sort-cmd: Invoking datamash
--version: Invoking datamash
--whitespace: Invoking datamash
--zero-terminated: Invoking datamash
-C: Invoking datamash
-c: Invoking datamash
-f: Invoking datamash
-g: Invoking datamash
-H: Invoking datamash
-H: Header Lines and Column Names
–header-out, crosstab and: Crosstab
-i: Invoking datamash
-R: Invoking datamash
-s: Invoking datamash
-t: Invoking datamash
-t: Invoking datamash
-t: Groupby on /etc/passwd
-W: Invoking datamash
-z: Invoking datamash

/etc/passwd, examples: Groupby on /etc/passwd

bin: Binning numbers
binning numbers: Binning numbers
binning strings: Binning strings
buckets, binning numbers: Binning numbers
buckets, binning strings: Binning strings
bug reporting: Reporting bugs

ceil: Rounding numbers
check: Check
check, in automation and shell scripts: Check
checking tabular structure: Check
checklist for bug reports: Reporting bugs
collapse: Groupby on /etc/passwd
column names: Header Lines and Column Names
column ranges: Column Ranges
columns, reverse: Reverse and Transpose
count: Crosstab
count: Groupby on /etc/passwd
count, crosstab and: Crosstab
cross tabulation: Crosstab
crosstab: Crosstab
crosstab and –header-out: Crosstab
crosstab and sum: Crosstab
crosstab and unique: Crosstab

delimiters, tabs: Field Delimiters
delimiters, whitespace: Field Delimiters

example, grouping: Overview
example, sorting: Overview
example, statistics: Overview
example, sum: Overview
examples, /etc/passwd: Groupby on /etc/passwd
examples, header: Header Lines and Column Names
examples, header: Header Lines and Column Names
examples, header-in: Header Lines and Column Names
examples, header-out: Header Lines and Column Names
examples, headers: Header Lines and Column Names
examples, max: Summary Statistics
examples, mean: Summary Statistics
examples, median: Summary Statistics
examples, min: Summary Statistics
examples, quartiles: Summary Statistics
examples, standard deviation: Summary Statistics
examples, summary statistics: Summary Statistics
examples, usage: Usage Examples

fail fast: Check
field delimiters: Field Delimiters
field names: Header Lines and Column Names
floor: Rounding numbers
frac: Rounding numbers

getnum: Extracting numeric values
groupby: Groupby on /etc/passwd
groupby, and collapse: Groupby on /etc/passwd
groupby, and count: Groupby on /etc/passwd
grouping: Overview
grouping: Invoking datamash

header, examples: Header Lines and Column Names
header-in, examples: Header Lines and Column Names
header-out, examples: Header Lines and Column Names
headers, examples: Header Lines and Column Names
help: Invoking datamash

input validation, transpose: Reverse and Transpose
invoking: Invoking datamash

LC_NUMERIC: Invoking datamash
line filtering operation: Available Operations
login shell, examples: Groupby on /etc/passwd

max, examples: Summary Statistics
mean, examples: Summary Statistics
median, examples: Summary Statistics
min, examples: Summary Statistics
missing values, transpose: Reverse and Transpose
multiple columns: Column Ranges

numbers, extracting from a field: Extracting numeric values
numeric operations: Available Operations

operations, line filtering: Available Operations
operations, numeric: Available Operations
operations, per-line: Available Operations
operations, primary: Available Operations
operations, statistical: Available Operations
operations, statistical: Statistical Operations
operations, textual: Available Operations
options: Invoking datamash
overview: Overview

patches, contributing: Reporting bugs
Per-Line operations: Available Operations
pivot tables: Crosstab
primary operations: Available Operations
problems: Reporting bugs

quartiles, examples: Summary Statistics

ranges, columns: Column Ranges
reporting bugs: Reporting bugs
reverse columns: Reverse and Transpose
reverse, and transpose: Reverse and Transpose
reverse, strict: Reverse and Transpose
reversing lines: Reverse and Transpose
round: Rounding numbers
rounding numbers: Rounding numbers

shell scripts, check: Check
sorting: Overview
sorting: Invoking datamash
sorting: Invoking datamash
standard deviation, examples: Summary Statistics
Statistical operations: Available Operations
statistical operations: Statistical Operations
statistics: Statistical Operations
strbin: Binning strings
strict mode: Reverse and Transpose
strict, reverse: Reverse and Transpose
strict, transpose: Reverse and Transpose
sum: Crosstab
sum, crosstab and: Crosstab
summary statistics example: Summary Statistics
swap rows, columns: Reverse and Transpose

tab delimiters: Field Delimiters
tac: Reverse and Transpose
Textual operations: Available Operations
transpose: Reverse and Transpose
transpose, and reverse: Reverse and Transpose
transpose, filler value: Reverse and Transpose
transpose, input validation: Reverse and Transpose
transpose, missing values: Reverse and Transpose
transpose, strict: Reverse and Transpose
trunc: Rounding numbers

unique: Crosstab
unique, crosstab and: Crosstab
usage: Invoking datamash
usage examples: Usage Examples

whitespace delimiters: Field Delimiters

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