v.db.univar(1grass) GRASS GIS User's Manual v.db.univar(1grass)
NAME
v.db.univar - Calculates univariate statistics on selected table col-
umn 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,...]] [--help] [--ver-
bose] [--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 ac-
cess 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
DESCRIPTION
v.db.univar calculates basic univariate statistics for numeric at-
tributes in a vector attribute table. It will calculate minimum, maxi-
mum, range, mean, standard deviation, variance, coefficient of varia-
tion, quartiles, median, and 90th percentile.
v.db.univar uses db.univar which in turn uses db.select to get the at-
tribute 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, in-
stead 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 per-
formed:
# 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
SEE ALSO
db.univar, r.univar, v.univar, db.select, d.vect.thematic, v.random
AUTHOR
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: unknown
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GRASS 7.8.7 v.db.univar(1grass)
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