t.rast.univar(1grass)

✨ t.rast.univar ✨

okay bestie, gather round, because t.rast.univar is literally that girl 💅 it's a GRASS User's Manual classic, and she's here to spill the stats.

🌸 NAME 🌸

t.rast.univar — she calculates univariate statistics from the non-null cells for each registered raster map of a space time raster dataset. yes, every single one. no skips. 🎀

🦋 KEYWORDS 🦋

temporal, statistics, raster, time, parallel

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👑 SYNOPSIS 👑

t.rast.univar
t.rast.univar --help
t.rast.univar [-eru] input=name  [zones=name]   [nprocs=integer]
[output=name]   [percentile=float[,float,...]]   [where=sql_query]
[region_relation=string]   [separator=character]   [--overwrite]
[--help]  [--verbose]  [--quiet]  [--ui]

💖 Flags 💖

• -e — Calculate extended statistics. more numbers, more power, slay.
• -r — Use the raster map regions for univar statistical calculation instead of the current region.
• -u — Suppress printing of column names. just the data, no labels, mysterious queen energy.
• --overwrite — Allow output files to overwrite existing files (so she can just take over, respectfully).
• --help — Print usage summary.
• --verbose — Verbose module output (she will narrate).
• --quiet — Quiet module output (she will simply not).
• --ui — Force launching GUI dialog. buttons and everything ✨

🎀 Parameters 🎀

• input=name [required] — Name of the input space time raster dataset. this one's mandatory, no cap.
• zones=name — Raster map used for zoning, must be of type CELL.
• nprocs=integer — Number of threads for parallel computing.
  • 0: use OpenMP default; >0: use nprocs; <0: use MAX-nprocs
  • Default: 0
• output=name — Name for output file.
• percentile=float[,float,...] — Percentile to calculate (requires extended statistics flag, so bestie bring -e or she can't help you 💀).
  • Options: 0-100
• where=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'
• region_relation=string — Process only maps with this spatial relation to the current computational region.
  • Options: overlaps, contains, is_contained
• separator=character — Field separator character between the output columns.
  • Special characters: pipe, comma, space, tab, newline
  • Default: pipe

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💜 DESCRIPTION 💜

okay so t.rast.univar calculates univariate statistics from the non-null cells for each registered raster map of a space time raster dataset. that's the whole vibe. 🫶

By default it returns the name of the map, the semantic label of the map, the start and end date of the map and the following values: mean, minimum and maximum vale, mean_of_abs, standard deviation, variance, coeff_var, number of null cells, total number of cells. (yes, "vale" — we keep it exactly as the legend says, character for character, it's iconic now 🌈)

Using the e flag it can calculate also extended statistics: first quartile, median value, third quartile and percentile 90. extra credit stats, ate.

If a zones raster map is provided, statistics are computed for each zone (category) in that input raster map. The zones option does not support space time raster datasets (STRDS) but only a single, static raster map. so like, one map only, don't come at her with a whole series 🙈

Space time raster datasets may contain raster maps with varying spatial extent like for example series of scenes of satellite images. With the region_relation option, computations can be limited to maps of the space time raster dataset that have a given spatial relation to the current computational region. Supported spatial relations are:

• "overlaps": process only maps that spatially overlap ("intersect") with the current computational region
• "is_contained": process only maps that are fully within the current computational region
• "contains": process only maps that contain (fully cover) the current computational region

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⭐ EXAMPLE ⭐

Obtain the univariate statistics for the raster space time dataset "tempmean_monthly" (precision reduced to 2 decimals in this example):

t.rast.univar -e tempmean_monthly
id|start|end|mean|min|max|mean_of_abs|stddev|variance|coeff_var|sum|null_cells|cells|first_quartile|median|third_quartile|percentile_90
2009_01_tempmean@climate_2009_2012|2009-01-01 00:00:00|2009-02-01 00:00:00|3.90|-3.38|7.43|3.95|1.79|3.20|45.91|1977967.31|503233|1010600|2.80|3.92|5.21|6.23
2009_02_tempmean@climate_2009_2012|2009-02-01 00:00:00|2009-03-01 00:00:00|5.91|-1.82|8.01|5.92|1.63|2.65|27.53|2999555.60|503233|1010600|5.44|6.26|7.07|7.48
...
2012_11_tempmean@climate_2009_2012|2012-11-01 00:00:00|2012-12-01 00:00:00|8.03|1.79|10.91|8.03|1.32|1.73|16.41|4072472.77|503233|1010600|7.49|8.13|8.96|9.48
2012_12_tempmean@climate_2009_2012|2012-12-01 00:00:00|2013-01-01 00:00:00|8.71|1.76|11.98|8.71|1.72|2.95|19.74|4418403.77|503233|1010600|7.84|8.95|9.99|10.67

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🌈 SEE ALSO 🌈

t.create, t.info t.create,

(yes, that's literally what it says. we don't question the reference list, we just respect it 💀)

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🧚 AUTHOR 🧚

Sören Gebbert, Thünen Institute of Climate-Smart Agriculture Stefan Blumentrath (support for zones, parallel processing, and spatial relations)

🍓 SOURCE CODE 🍓

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

Latest change: Saturday Oct 11 04:38:40 2025 in commit: 3dd71f5fab83b72a2db2da959fe075c5b3b52200

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

© 2003-2026 GRASS Development Team, GRASS 8.5.0 Reference Manual

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and that's the whole page, bestie 💖 this was t.rast.univar from the GRASS User's Manual, GRASS 8.5.0, with the latest change landing Saturday Oct 11 04:38:40 2025 in that commit 3dd71f5fab83b72a2db2da959fe075c5b3b52200, © 2003-2026 GRASS Development Team. go run your stats, you're gonna do amazing, periodt 👑✨