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,...]]   [format=string]   [--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 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

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.

       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.

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 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

SEE ALSO

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

        GRASS SQL interface

AUTHORS

       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)

       Accessed: Friday Apr 04 01:21:13 2025

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

       © 2003-2025 GRASS Development Team, GRASS GIS 8.4.1 Reference Manual

GRASS 8.4.1                                                                                  v.db.univar(1grass)