t.vect.univar(1grass)

NAME
t.vect.univar - Calculates univariate statistics of attributes for each registered vector map of a space time vector dataset

KEYWORDS
temporal, statistics, vector, time

SYNOPSIS
t.vect.univar
t.vect.univar --help
t.vect.univar [-eu] input=name [output=name] [layer=string] column=name [twhere=sql_query] [where=sql_query] [type=string] [separator=character] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

  Flags:

-e
    Calculate extended statistics

-u
    Suppress printing of column names

--overwrite
    Allow output files to overwrite existing files

--help
    Print usage summary

--verbose
    Verbose module output

--quiet
    Quiet module output

--ui
    Force launching GUI dialog

  Parameters:

input=name [required]
    Name of the input space time vector dataset

output=name
    Name for output file

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

twhere=sql_query
    WHERE conditions of SQL statement without ’where’ keyword used in the temporal GIS framework
    Example: start_time > ’2001-01-01 12:30:00’

where=sql_query
    WHERE conditions of SQL statement without ’where’ keyword
    Example: income < 1000 and population >= 10000

type=string
    Input feature type
    Options: point, line, boundary, centroid, area
    Default: point

separator=character
    Field separator character between the output columns
    Special characters: pipe, comma, space, tab, newline
    Default: pipe

DESCRIPTION
The module t.vect.univar computes univariate statistics of a space time vector dataset based on a single attribute row.

EXAMPLE
The example is based on the t.vect.observe.strds example; so create the precip_stations space time vector dataset and after run the following command:

t.vect.univar input=precip_stations col=month
id|start|end|n|nmissing|nnull|min|max|range|mean|mean_abs|population_stddev|population_variance|population_coeff_variation|sample_stddev|sample_variance|kurtosis|skewness
precip_stations_monthly@climate_2009_2012|2009-01-01 00:00:00|2009-02-01 00:00:00|132|0|4|-2.31832|7.27494|9.59326|3.44624|3.5316|1.79322|3.21564|0.520341|1.80005|3.24019|0.484515|-0.338519
precip_stations_monthly@climate_2009_2012|2009-02-01 00:00:00|2009-03-01 00:00:00|132|0|4|-0.654152|7.90613|8.56028|5.47853|5.48844|1.73697|3.01708|0.317051|1.74359|3.04011|0.875252|-1.0632
....
precip_stations_monthly@climate_2009_2012|2012-10-01 00:00:00|2012-11-01 00:00:00|132|0|4|9.67596|18.4654|8.78945|14.945|14.945|1.90659|3.6351|0.127574|1.91386|3.66285|-0.0848967|-0.700833
precip_stations_monthly@climate_2009_2012|2012-11-01 00:00:00|2012-12-01 00:00:00|132|0|4|3.56755|10.6211|7.05357|7.72153|7.72153|1.33684|1.78715|0.173132|1.34194|1.8008|0.90434|-0.863935
precip_stations_monthly@climate_2009_2012|2012-12-01 00:00:00|2013-01-01 00:00:00|132|0|4|3.04325|11.6368|8.5935|8.20147|8.20147|1.78122|3.17275|0.217183|1.78801|3.19697|-0.177991|-0.501295

SEE ALSO
t.create, t.info

AUTHOR
Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

SOURCE CODE

Available at: t.vect.univar source code (history)

Accessed: Monday Apr 01 03:09:33 2024

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