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 population >= 10000

percentile=float[,float,...]

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

format=string

Output format
Options: plain, json, shell
plain: Plain text output
json: JSON (JavaScript Object Notation)
shell: Shell script style for Bash eval

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 column=heights
v.db.select samples
v.db.univar samples column=heights

JSON output¶

This uses the JSON output of the module which is passed using a pipe (in Bash or other unix-like shell) to the jq tool which selects just the relevant statistic.

v.db.univar precip_30ynormals column=annual format=json | jq .statistics.mean