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: Tuesday Jun 27 11:14:34 2023

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       © 2003-2023 GRASS Development Team, GRASS GIS 8.3.0 Reference Manual