GRASS GIS manual: v.db.univar

Note: A new GRASS GIS stable version has been released: GRASS GIS 7.4, available here.
Updated manual page: here

NAME

v.db.univar - Calculates univariate statistics on selected table column 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] [--verbose] [--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=name [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 access this is the layer name.; Default: 1
column=name [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 inhab >= 10000
percentile=float[,float,...]: Percentile to calculate (requires extended statistics flag); Options: 0-100; Default: 90

DESCRIPTION
EXAMPLES
- Univariate statistics on attribute table column
- Univariate statistics on randomly sampled data points
SEE ALSO
AUTHOR

DESCRIPTION

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. It uses db.select to create list values for statistical calculations. 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 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
 [...]

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 colum=heights
v.db.select samples

v.db.univar samples colum=heights

AUTHOR

Michael Barton, Arizona State University

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

Last changed: $Date: 2016-05-17 07:10:47 -0700 (Tue, 17 May 2016) $

SOURCE CODE

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