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 inhab >= 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

   Sren Gebbert, Thnen Institute of Climate-Smart Agriculture

   Last changed: $Date: 2015-09-22 10:10:38 +0200 (Tue, 22 Sep 2015) $

SOURCE CODE

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

   Main index | Temporal index | Topics index | Keywords index | Graphical
   index | Full index

    2003-2016 GRASS Development Team, GRASS GIS 7.2.0 Reference Manual





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