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db.univargrass - Online in the Cloud

Run db.univargrass in OnWorks free hosting provider over Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator

This is the command db.univargrass that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator

PROGRAM:

NAME


db.univar - Calculates univariate statistics on selected table column.

KEYWORDS


database, statistics, attribute table

SYNOPSIS


db.univar
db.univar --help
db.univar [-eg] table=name column=name [database=name] [driver=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:
table=name [required]
Name of attribute table

column=name [required]
Name of attribute column on which to calculate statistics (must be numeric)

database=name
Name of database

driver=name
Name of database driver
Options: dbf, odbc, ogr, sqlite, pg

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

DESCRIPTION


db.univar calculates basic univariate statistics for numeric attributes in a data 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 If the database and driver are not specified,
the default values set in db.connect will be used.

EXAMPLE


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 colum=heights
v.db.select samples
db.univar samples colum=heights

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