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,...]] [--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 inhab >= 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.
It uses
db.select to create list values for statistical calculations.
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
Michael Barton, Arizona State University
and authors of r.univar.sh (Markus Neteler et al.)
Last changed: $Date: 2016-11-14 00:09:36 +0100 (Mon, 14 Nov 2016) $
SOURCE CODE
Available at: v.db.univar source code (history)
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© 2003-2017
GRASS Development Team,
GRASS GIS 7.2.1 Reference Manual