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v.db.univar(1) Grass User's Manual v.db.univar(1)

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

vector, statistics, attribute table

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]

-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

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

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.

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
 [...]

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

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

Michael Barton, Arizona State University
and authors of r.univar.sh (Markus Neteler et al.)
Last changed: $Date: 2018-09-30 19:02:53 +0200 (Sun, 30 Sep 2018) $

Available at: v.db.univar source code (history)
Main index | Vector index | Topics index | Keywords index | Graphical index | Full index
© 2003-2018 GRASS Development Team, GRASS GIS 7.4.3 Reference Manual
GRASS 7.4.3

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