DATAMASH(1) User Commands DATAMASH(1)

datamash - command-line calculations

datamash [OPTION] op [fld] [op fld ...]

Performs numeric/string operations on input from stdin.

'op' is the operation to perform. If a primary operation is used, it must be listed first, optionally followed by other operations. 'fld' is the input field to use. 'fld' can be a number (1=first field), or a field name when using the -H or --header-in options. Multiple fields can be listed with a comma (e.g. 1,6,8). A range of fields can be listed with a dash (e.g. 2-8). Use colons for operations which require a pair of fields (e.g. 'pcov 2:6').

groupby, crosstab, transpose, reverse, check

rmdup

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

sum, min, max, absmin, absmax, range

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

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

skip comment lines (starting with '#' or ';' and optional whitespace)
print entire input line before op results (default: print only the grouped keys)
This option is only sensible for linewise operations. Other uses are deprecated and will be removed in a future version of GNU Datamash.
group via fields X,[Y,Z]; equivalent to primary operation 'groupby'
first input line is column headers
print column headers as first line
same as '--header-in --header-out'
ignore upper/lower case when comparing text; this affects grouping, and string operations
sort the input before grouping; this removes the need to manually pipe the input through 'sort'
use X to separate elements in collapse and unique lists (default: comma)

allow lines with varying number of fields
fill missing values with X (default N/A)

use X instead of TAB as field delimiter
print numeric values with printf style floating-point FORMAT.
use X instead as output field delimiter (default: use same delimiter as -t/-W)
skip NA/NaN values
round numeric output to N decimal places
use whitespace (one or more spaces and/or tabs) for field delimiters
end lines with 0 byte, not newline
Alternative sort(1) to use.
display this help and exit
output version information and exit

Primary operations affect the way the file is processed. If used, the primary operation must be listed first. If primary operation is not listed the entire file is processed - either line-by-line (for 'per-line' operations) or all lines as one group (for grouping operations). See Examples section below.

group the file by given fields. Equivalent to option '-g'. For each group perform operation op on field fld.
cross-tabulate a file by two fields (cross-tabulation is also known as pivot tables). If no operation is specified, counts how many incidents exist of X,Y.
transpose rows, columns of the input file
reverse field order in each line
verify the input file has same number of fields in all lines, or the expected number of lines/fields. number of lines and fields are printed to STDOUT. Exits with non-zero code and prints the offending line if there's a mismatch in the number of lines/ fields.

remove lines with duplicated key value

Encode the field as base64
Decode the field as base64, exit with error if invalid base64 string
Calculate md5/sha1/sha224/sha256/sha384/sha512 hash of the field value
bin numeric values into buckets of size BUCKET-SIZE (defaults to 100).
hashes the input and returns a numeric integer value between zero and BUCKET-SIZE (defaults to 10).
numeric rounding operations. round (round half away from zero), floor (round down), ceil (ceiling, round up), trunc (truncate, round towards zero), frac (fraction, return fraction part of a decimal-point value).
extract the directory name and the base file name from a given string (same as to dirname(1) and basename(1)).
extract the extension of the file name (without the '.').
extract the base file name without the extension.
extract a number from the field. TYPE is optional single letter option n/i/d/p/h/o (see examples below).
copy input field to output field (similar to cut(1)). The echo command is simply an alias to cut.

sum the of values
minimum value
maximum value
minimum of the absolute values
maximum of the absolute values
the values range (max-min)

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 The uniq command is simply an alias to unique.
comma-separated list of all input values
number of unique/distinct values

A p/s prefix indicates the variant: population or sample. Typically, the sample variant is equivalent with GNU R's internal functions (e.g datamash's sstdev operation is equivalent to R's sd() function).

mean of the values
geometric mean of the values
harmonic mean of the values
trimmed mean of the values. PERCENT should be between 0 and 0.5. (trimmean:0 is equivalent to mean. trimmean:0.5 is equivalent to median).
mean square of the values
root mean square of the values
median value
1st quartile value
3rd quartile value
inter-quartile range
percentile value PERCENTILE (defaults to 95).
mode value (most common value)
anti-mode value (least common value)
population/sample standard deviation
population/sample variance
median absolute deviation, scaled by constant 1.4826 for normal distributions
median absolute deviation, unscaled
skewness of the group
values x reported by 'sskew' and 'pskew' operations:
          x > 0       -  positively skewed / skewed right
      0 > x           -  negatively skewed / skewed left
          x > 1       -  highly skewed right
      1 > x >  0.5    -  moderately skewed right
    0.5 > x > -0.5    -  approximately symmetric
   -0.5 > x > -1      -  moderately skewed left
     -1 > x           -  highly skewed left
excess Kurtosis of the group
p-value of the Jarque-Beta (jarque) and D'Agostino-Pearson Omnibus (dpo) tests for normality:
null hypothesis is normality;
low p-Values indicate non-normal data;
high p-Values indicate null-hypothesis cannot be rejected.
covariance of fields X and Y
Pearson product-moment correlation coefficient [Pearson's R] of fields X and Y

Print the sum and the mean of values from field 1:

$ seq 10 | datamash sum 1 mean 1
55  5.5

Group input based on field 1, and sum values (per group) on field 2:

$ cat example.txt
A  10
A  5
B  9
B  11
$ datamash -g 1 sum 2 < example.txt
A  15
B  20
$ datamash groupby 1 sum 2 < example.txt
A  15
B  20

Unsorted input must be sorted (with '-s'):

$ cat example.txt
A  10
C  4
B  9
C  1
A  5
B  11
$ datamash -s -g1 sum 2 < example.txt
A  15
B  20
C  5

Which is equivalent to:

$ cat example.txt | sort -k1,1 | datamash -g 1 sum 2

Use -H (--headers) if the input file has a header line:

# Given a file with student name, field, test score...
$ head -n5 scores_h.txt
Name           Major            Score
Shawn          Engineering      47
Caleb          Business         87
Christian      Business         88
Derek          Arts             60
# Calculate the mean and standard deviation for each major
$ datamash --sort --headers --group 2 mean 3 pstdev 3 < scores_h.txt
 (or use short form)
$ datamash -sH -g2 mean 3 pstdev 3 < scores_h.txt
 (or use named fields)
$ datamash -sH -g Major mean Score pstdev Score < scores_h.txt
GroupBy(Major)    mean(Score)   pstdev(Score)
Arts              68.9          10.1
Business          87.3           4.9
Engineering       66.5          19.1
Health-Medicine   90.6           8.8
Life-Sciences     55.3          19.7
Social-Sciences   60.2          16.6

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

Use -C (--skip-comments) to skip lines starting with '#' or ';' characters (and optional whitespace before them):

$ cat in.txt
 #foo   3
bar     5
;baz    7
$ datamash sum 2 < in.txt
15
$ datamash -C sum 2 < in.txt
5

Use comma or dash to specify multiple fields. The following are equivalent:

$ seq 9 | paste - - -
1   2   3
4   5   6
7   8   9
$ seq 9 | paste - - - | datamash sum 1 sum 2 sum 3
12  15  18
$ seq 9 | paste - - - | datamash sum 1,2,3
12  15  18
$ seq 9 | paste - - - | datamash sum 1-3
12  15  18

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

$ seq 6 | paste - - | datamash reverse
2    1
4    3
6    5

$ seq 6 | paste - - | datamash transpose
1    3    5
2    4    6

Remove lines with duplicate key value from field 1 (Unlike first,last operations, rmdup is much faster and does not require sorting the file with -s):

# Given a list of files and sample IDs:
$ cat INPUT
SampleID  File
2         cc.txt
3         dd.txt
1         ab.txt
2         ee.txt
3         ff.txt
# Remove lines with duplicated Sample-ID (field 1):
$ datamash rmdup 1 < INPUT
# or use named field:
$ datamash -H rmdup SampleID < INPUT
SampleID  File
2         cc.txt
3         dd.txt
1         ab.txt

Calculate the sha1 hash value of each TXT file, after calculating the sha1 value of each file's content:

$ sha1sum *.txt | datamash -Wf sha1 2

Check the structure of the input file: ensure all lines have the same number of fields, or expected number of lines/fields:

$ seq 10 | paste - - | datamash check && echo ok || echo fail
5 lines, 2 fields
ok
$ seq 13 | paste - - - | datamash check && echo ok || echo fail
line 4 (3 fields):
  10  11  12
line 5 (2 fields):
  13
datamash: check failed: line 5 has 2 fields (previous line had 3)
fail
$ seq 10 | paste - - | datamash check 2 fields 5 lines
5 lines, 2 fields
$ seq 10 | paste - - | datamash check 4 fields
line 1 (2 fields):
  1     2
datamash: check failed: line 1 has 2 fields (expecting 4)
$ seq 10 | paste - - | datamash check 7 lines
datamash: check failed: input had 5 lines (expecting 7)

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

An optional grouping operation can be used instead of counting:

$ datamash -s crosstab 1,2 sum 3 < input.txt
     x    y
a    43   7
b    21   N/A
$ datamash -s crosstab 1,2 unique 3 < input.txt
     x    y
a    3,40 7
b    21   N/A

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

Hash any 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"}'

The 'getnum' operation extracts a numeric value from the field:

$ echo zoom-123.45xyz | datamash getnum 1
123.45
getnum accepts an optional single-letter TYPE option:
    getnum:n - natural numbers (positive integers, including zero)
    getnum:i - integers
    getnum:d - decimal point numbers
    getnum:p - positive decimal point numbers (this is the default)
    getnum:h - hex numbers
    getnum:o - octal numbers

Examples:

$ echo zoom-123.45xyz | datamash getnum 1
123.45
$ echo zoom-123.45xyz | datamash getnum:n 1
123
$ echo zoom-123.45xyz | datamash getnum:i 1
-123
$ echo zoom-123.45xyz | datamash getnum:d 1
123.45
$ echo zoom-123.45xyz | datamash getnum:p 1
-123.45
# Hex 0x123 = 291 Decimal
$ echo zoom-123.45xyz | datamash getnum:h 1
291
# Octal 0123 = 83 Decimal
$ echo zoom-123.45xyz | datamash getnum:o 1
83

See GNU Datamash Website (https://www.gnu.org/software/datamash)

decimal-point character and thousands separator

Written by Assaf Gordon, Tim Rice, Shawn Wagner, Erik Auerswald.

Copyright © 2022 Assaf Gordon and Tim Rice License GPLv3+: GNU GPL version 3 or later https://gnu.org/licenses/gpl.html.
This is free software: you are free to change and redistribute it. There is NO WARRANTY, to the extent permitted by law.

The full documentation for datamash is maintained as a Texinfo manual. If the info and datamash programs are properly installed at your site, the command

info datamash

should give you access to the complete manual.

July 2022 datamash 1.8-dirty