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v.db.univar(1grass) Grass User's Manual v.db.univar(1grass)

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

vector, statistics, attribute table

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


Extended statistics (quartiles and 90th percentile)

Print stats in shell script style

Print usage summary

Verbose module output

Quiet module output

Force launching GUI dialog


Name of vector map
Or data source for direct OGR access

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 access this is the layer name.
Default: 1

Name of attribute column on which to calculate statistics (must be numeric)

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

Percentile to calculate (requires extended statistics flag)
Options: 0-100
Default: 90

v.db.univar calculates basic univariate statistics for numeric attributes in a vector attribute table. It will calculate minimum, maximum, range, mean, standard deviation, variance, coefficient of variation, quartiles, median, and 90th percentile.

v.db.univar uses db.univar which in turn uses db.select to get the attribute 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, instead of attribute table-based, univariate statistics on attributes see v.univar. NOTES A database connection must be defined for the selected vector layer.

In this example, the 30 years precipitation data table is statistically analysed (North Carolina sample dataset) and univariate statistics performed: 

# 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


 [...]

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

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

Michael Barton, Arizona State University

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

Last changed: $Date: 2018-09-30 18:55:29 +0200 (Sun, 30 Sep 2018) $

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

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GRASS 7.6.0