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v.db.univar(1)		    GRASS GIS User's Manual		v.db.univar(1)

NAME
       v.db.univar   - Calculates univariate statistics	on selected table col-
       umn for a GRASS vector map.

KEYWORDS
       vector, statistics, attribute table

SYNOPSIS
       v.db.univar
       v.db.univar --help
       v.db.univar     [-eg]	 map=name      [layer=string]	   column=name
       [where=sql_query]    [percentile=float[,float,...]]   [--help]  [--ver-
       bose]  [--quiet]	 [--ui]

   Flags:
       -e
	   Extended statistics (quartiles and 90th percentile)

       -g
	   Print stats in shell	script style

       --help
	   Print usage summary

       --verbose
	   Verbose module output

       --quiet
	   Quiet module	output

       --ui
	   Force launching GUI dialog

   Parameters:
       map=nameA [required]
	   Name	of vector map
	   Or data source for direct OGR access

       layer=string
	   Layer number	or name
	   Vector features can have category values in different layers.  This
	   number determines which layer to use. When used with	direct OGR ac-
	   cess	this is	the layer name.
	   Default: 1

       column=nameA [required]
	   Name	of attribute column on which to	calculate statistics (must  be
	   numeric)

       where=sql_query
	   WHERE conditions of SQL statement without 'where' keyword
	   Example: income < 1000 and population >= 10000

       percentile=float[,float,...]
	   Percentile to calculate (requires extended statistics flag)
	   Options: 0-100
	   Default: 90

DESCRIPTION
       v.db.univar  calculates	basic  univariate  statistics  for numeric at-
       tributes	in a vector attribute table. It	will calculate minimum,	 maxi-
       mum,  range,  mean, standard deviation, variance, coefficient of	varia-
       tion, quartiles,	median,	and 90th percentile.

       v.db.univar uses	db.univar which	in turn	uses db.select to get the  at-
       tribute	values on which	it calculates the statistics.  This means that
       statistics are calculated based on the entries in the attribute	table,
       not  based on the features in the map. One attribute value is read from
       each line in the	attribute table, whether there are no, one or  several
       features	 with  the  category value referenced by that line, or whether
       any features have more than one category	value.	For feature-based, in-
       stead of	attribute table-based, univariate statistics on	attributes see
       v.univar.  NOTES	A database connection must be defined for the selected
       vector layer.

EXAMPLES
   Univariate statistics on attribute table column
       In this example,	the 30 years precipitation data	table is statistically
       analysed	(North Carolina	sample dataset)	and univariate statistics per-
       formed:
       # show columns of attribute table connected to precipitation map
       v.info -c precip_30ynormals
       # univariate statistics on 30 years annual precipitation	in NC
       v.db.univar precip_30ynormals column=annual
	Number of values: 136
	Minimum: 947.42
	Maximum: 2329.18
	Range: 1381.76
	Mean: 1289.31147058823
	[...]

   Univariate statistics on randomly sampled data points
       In  this	 example,  random  points  are	sampled	from the elevation map
       (North Carolina sample dataset) and univariate statistics performed:
       g.region	raster=elevation -p
       v.random	output=samples n=100
       v.db.addtable samples column="heights double precision"
       v.what.rast samples raster=elevation column=heights
       v.db.select samples
       v.db.univar samples column=heights

SEE ALSO
	db.univar, r.univar, v.univar, db.select, d.vect.thematic, v.random

AUTHOR
       Michael Barton, Arizona State University

       and authors of r.univar.sh (Markus Neteler et al.)

SOURCE CODE
       Available at: v.db.univar source	code (history)

       Main index | Vector index | Topics index	| Keywords index  |  Graphical
       index | Full index

       A(C) 2003-2020 GRASS Development	Team, GRASS GIS	7.8.4 Reference	Manual

GRASS 7.8.4							v.db.univar(1)

NAME | KEYWORDS | SYNOPSIS | DESCRIPTION | EXAMPLES | SEE ALSO | AUTHOR | SOURCE CODE

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