NAME
t.vect.univar - Calculates univariate statistics of attributes for each registered vector map of a space time vector datasetKEYWORDS
temporal, statistics, vector, timeSYNOPSIS
t.vect.univar
t.vect.univar --helpt.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
Table of contents
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.infoAUTHOR
Sören Gebbert, Thünen Institute of Climate-Smart AgricultureSOURCE CODE
Available at: t.vect.univar source code (history)
Latest change: Thursday Feb 03 11:10:06 2022 in commit: 547ff44e6aecfb4c9cbf6a4717fc14e521bec0be
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