r.stats.quantile(1grass)
| r.stats.quantile(1grass) | GRASS User's Manual | r.stats.quantile(1grass) |
NAME
r.stats.quantile - Compute category quantiles using two passes.
KEYWORDS
raster, statistics, zonal statistics, percentile, quantile
SYNOPSIS
r.stats.quantile
r.stats.quantile --help
r.stats.quantile [-rpt] base=name
cover=name [quantiles=integer]
[percentiles=float[,float,...]]
[bins=integer] [output=name[,name,...]]
[file=name] [separator=character]
format=name [--overwrite] [--help]
[--verbose] [--quiet] [--ui]
Flags:
- -r
-
Create reclass map with statistics as category labels - -p
-
Do not create output maps; just print statistics - -t
-
Print statistics in table format [deprecated]
This flag is deprecated and will be removed in a future release. Use format=csv instead. - --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:
- base=name [required]
-
Name of base raster map - cover=name [required]
-
Name of cover raster map - quantiles=integer
-
Number of quantiles - percentiles=float[,float,...]
-
List of percentiles
Default: 50 - bins=integer
-
Number of bins to use
Default: 1000 - output=name[,name,...]
-
Resultant raster map(s) - file=name
-
Name for output file (if omitted or "-" output to stdout) - separator=character
-
Field separator
Special characters: pipe, comma, space, tab, newline - format=name [required]
-
Output format
Options: plain, csv, json
Default: plain
plain: Human readable text output
csv: CSV (Comma Separated Values)
json: JSON (JavaScript Object Notation)
DESCRIPTION
r.stats.quantile is a tool to analyse exploratory statistics of a floating-point "cover layer" according to how it intersects with objects in a "base layer". It provides quantile calculations as selected "zonal statistics".
NOTES
r.stats.quantile is intended to be a partial replacement for r.statistics, with support for floating-point cover maps. It provides quantile calculations, which are absent from r.stats.zonal.
Quantiles are calculated following algorithm 7 from Hyndman and Fan (1996), which is also the default in R and numpy.
EXAMPLE
In this example, the raster polygon map zipcodes in the North
Carolina sample dataset is used to calculate quantile raster statistics
using the elevation raster map:
g.region raster=zipcodes -p # print quantiles r.stats.quantile base=zipcodes cover=elevation quantiles=3 -p 27511:0:33.333333:134.717392 27511:1:66.666667:143.985723 27513:0:33.333333:140.669993 27513:1:66.666667:146.279449 27518:0:33.333333:115.140101 27518:1:66.666667:129.893723 [...] # write out percentile raster maps r.stats.quantile base=zipcodes cover=elevation percentiles=25,50,75 \
output=zipcodes_elev_q25,zipcodes_elev_q50,zipcodes_elev_q75
REFERENCES
- Hyndman and Fan (1996) Sample Quantiles in Statistical Packages, American Statistician. American Statistical Association. 50 (4): 361-365. DOI: 10.2307/2684934
- Engineering Statistics Handbook: Percentile, NIST
SEE ALSO
r.quantile, r.stats.zonal, r.statistics
AUTHORS
Glynn Clements
Markus Metz
SOURCE CODE
Available at: r.stats.quantile source code (history)
Accessed: Thursday Jun 18 12:48:27 2026
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