Provided by: grass-doc_7.8.7-1_all
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: unknown Main index | Temporal index | Topics index | Keywords index | Graphical index | Full index © 2003-2022 GRASS Development Team, GRASS GIS 7.8.7 Reference Manual