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DATAMASH(1) User Commands DATAMASH(1)

NAME

datamash - command-line calculations

SYNOPSIS

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

DESCRIPTION

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').

Primary operations:

groupby, crosstab, transpose, reverse, check

Line-Filtering operations:

rmdup

Per-Line operations:

base64, debase64, md5, sha1, sha256, sha512, bin, strbin, round, floor, ceil, trunc, frac

Numeric Grouping operations:

sum, min, max, absmin, absmax, range

Textual/Numeric Grouping operations:

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

Statistical Grouping operations:

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

Grouping Options:

-f, --full
print entire input line before op results (default: print only the grouped keys)
-g, --group=X[,Y,Z]
group via fields X,[Y,Z]; equivalent to primary operation 'groupby'
--header-in
first input line is column headers
--header-out
print column headers as first line
-H, --headers
same as '--header-in --header-out'
-i, --ignore-case
ignore upper/lower case when comparing text; this affects grouping, and string operations
-s, --sort
sort the input before grouping; this removes the need to manually pipe the input through 'sort'

File Operation Options:

--no-strict
allow lines with varying number of fields
--filler=X
fill missing values with X (default %s)

General Options:

-t, --field-separator=X
use X instead of TAB as field delimiter
--narm
skip NA/NaN values
-W, --whitespace
use whitespace (one or more spaces and/or tabs) for field delimiters
-z, --zero-terminated
end lines with 0 byte, not newline
--help
display this help and exit
--version
output version information and exit

OPTIONS

AVAILABLE OPERATIONS

Primary Operations

Primary operations affect the way the file is processed. If used, the primary operation must be listed first. Some operations require field numbers (groupby, crosstab) while others do not (reverse,check,transpose). 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.
groupby X,Y,... op fld ...
group the file by given fields. Equivalent to option '-g'. For each group perform operation op on field fld.
crosstab X,Y [op 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
transpose rows, columns of the input file
reverse
reverse field order in each line
check [N lines] [N fields]
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.

Line-Filtering operations

rmdup
remove lines with duplicated key value

Per-Line operations

base64
Encode the field as base64
debase64
Decode the field as base64, exit with error if invalid base64 string
md5/sha1/sha256/sha512
Calculate md5/sha1/sha256/sha512 hash of the field value
bin[:BUCKET-SIZE]
bin numeric values into buckets of size BUCKET-SIZE (defaults to 100).
strbin[:BUCKET-SIZE]
hashes the input and returns a numeric integer value between zero and BUCKET-SIZE (defaults to 10).
round/floor/ceil/trunc/frac
numeric rounding operations. round (round half away from zero), floor (round up), ceil (ceiling, round down), trunc (truncate, round towards zero), frac (fraction, return fraction part of a decimal-point value).

Numeric Grouping operations

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

Textual/Numeric Grouping operations

count
count number of elements in the group
first
the first value of the group
last
the last value of the group
rand
one random value from the group
unique
comma-separated sorted list of unique values
collapse
comma-separated list of all input values
countunique
number of unique/distinct values

Statistical Grouping operations

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
mean of the values
median
median value
q1
1st quartile value
q3
3rd quartile value
iqr
inter-quartile range
perc[:PERCENTILE]
percentile value ERCENTILE (defaults to 95).
mode
mode value (most common value)
antimode
anti-mode value (least common value)
pstdev/sstdev
population/sample standard deviation
pvar/svar
population/sample variance
mad
median absolute deviation, scaled by constant 1.4826 for normal distributions
madraw
median absolute deviation, unscaled
pskew/sskew
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
    
pkurt/skurt
excess Kurtosis of the group
jarque/dpo
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.
pcov/scov [X:Y]
covariance of fields X and Y
ppearson/spearson [X:Y]
Pearson product-moment correlation coefficient [Pearson's R] of fields X and Y

EXAMPLES

Basic usage

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

Header lines

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 devian 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

Multiple fields

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

Rounding

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

Reversing fields

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

Transposing a file

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

Removing Duplicated lines

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

Checksums

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 file structure

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

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

Binning numeric values

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    -15
 -7.5    -10
 -5.0    -10
 -2.5     -5
  0.0      0
  2.5      0
  5.0      5
  7.5      5
 10.0     10

Binning string values

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"}'

ADDITIONAL INFORMATION

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

AUTHOR

Written by Assaf Gordon.

COPYRIGHT

Copyright © 2017 Assaf Gordon License GPLv3+: GNU GPL version 3 or later <http://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.

SEE ALSO

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.
August 2017 datamash 1.2