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


       vector, statistics, attribute table


       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

       map=name [required]
           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

       column=name [required]
           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 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.


   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 -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 samples
       v.db.univar samples column=heights


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


       Michael Barton, Arizona State University

       and authors of (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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