1v.univar(1)                   Grass User's Manual                  v.univar(1)
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NAME

6       v.univar  - Calculates univariate statistics of vector map features.
7       Variance and standard deviation is calculated only for points if speci‐
8       fied.
9

KEYWORDS

11       vector, statistics, univariate statistics, attribute table, geometry
12

SYNOPSIS

14       v.univar
15       v.univar --help
16       v.univar [-gewd] map=name  [layer=string]    [type=string[,string,...]]
17       [column=name]     [where=sql_query]    [percentile=integer]    [--help]
18       [--verbose]  [--quiet]  [--ui]
19
20   Flags:
21       -g
22           Print the stats in shell script style
23
24       -e
25           Calculate extended statistics
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27       -w
28           Weigh by line length or area size
29
30       -d
31           Calculate geometric distances instead of attribute statistics
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33       --help
34           Print usage summary
35
36       --verbose
37           Verbose module output
38
39       --quiet
40           Quiet module output
41
42       --ui
43           Force launching GUI dialog
44
45   Parameters:
46       map=name [required]
47           Name of vector map
48           Or data source for direct OGR access
49
50       layer=string
51           Layer number or name
52           Vector features can have category values in different layers.  This
53           number  determines  which  layer  to use. When used with direct OGR
54           access this is the layer name.
55           Default: 1
56
57       type=string[,string,...]
58           Input feature type
59           Options: point, line, boundary, centroid, area
60           Default: point,line,area
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62       column=name
63           Name of attribute column
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65       where=sql_query
66           WHERE conditions of SQL statement without ’where’ keyword
67           Example: income < 1000 and population >= 10000
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69       percentile=integer
70           Percentile to calculate (requires extended statistics flag)
71           Options: 0-100
72           Default: 90
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DESCRIPTION

75       v.univar calculates univariate statistics on (by default) an  attribute
76       of,  or,  through the -d flag on distance between, vector map features.
77       Attributes are read per feature and per category value. This means that
78       if  the map contains several features with the same category value, the
79       attribute is read as many times as there are  features.  On  the  other
80       hand,  if  a  feature  has more than one category value, each attribute
81       value linked to each of the category values of the feature is read. For
82       statistics  on  one  attribute  per  category  value,  instead  of  one
83       attribute per feature and per category, see v.db.univar.
84
85       Extended statistics (-e) adds median, 1st and 3rd quartiles,  and  90th
86       percentile to the output.
87

NOTES

89       When using the -d flag, univariate statistics of distances between vec‐
90       tor features are calculated. The distances from  all  features  to  all
91       other features are used. Since the distance from feature A to feature B
92       is the same like the distance from feature B to feature  A,  that  dis‐
93       tance is considered only once, i.e. all pairwise distances between fea‐
94       tures are used. Depending on the selected vector  type,  distances  are
95       calculated as follows:
96
97           ·   type=point: point distances are considered;
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99           ·   type=line: line to line distances are considered;
100
101           ·   type=area:  not  supported,  use type=centroid instead (and see
102               v.distance for calculating distances between areas)
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EXAMPLES

105       The examples are based on the North Carolina sample dataset.
106
107   Example dataset preparation
108       g.region raster=elevation -p
109       v.random output=samples npoints=100
110       v.db.addtable map=samples columns="heights double precision"
111       v.what.rast map=samples rast=elevation column=heights
112       v.db.select map=samples
113
114   Calculate height attribute statistics
115       v.univar -e samples column=heights type=point
116       number of features with non NULL attribute: 100
117       number of missing attributes: 0
118       number of NULL attributes: 0
119       minimum: 57.2799
120       maximum: 148.903
121       range: 91.6235
122       sum: 10825.6
123       mean: 108.256
124       mean of absolute values: 108.256
125       population standard deviation: 20.2572
126       population variance: 410.356
127       population coefficient of variation: 0.187123
128       sample standard deviation: 20.3593
129       sample variance: 414.501
130       kurtosis: -0.856767
131       skewness: 0.162093
132       1st quartile: 90.531
133       median (even number of cells): 106.518
134       3rd quartile: 126.274
135       90th percentile: 135.023
136
137   Compare to statistics of original raster map
138       r.univar -e elevation
139       total null and non-null cells: 2025000
140       total null cells: 0
141       Of the non-null cells:
142       ----------------------
143       n: 2025000
144       minimum: 55.5788
145       maximum: 156.33
146       range: 100.751
147       mean: 110.375
148       mean of absolute values: 110.375
149       standard deviation: 20.3153
150       variance: 412.712
151       variation coefficient: 18.4057 %
152       sum: 223510266.558102
153       1st quartile: 94.79
154       median (even number of cells): 108.88
155       3rd quartile: 126.792
156       90th percentile: 138.66
157
158   Calculate statistic of distance between sampling points
159       v.univar -d samples type=point
160       number of primitives: 100
161       number of non zero distances: 4851
162       number of zero distances: 0
163       minimum: 69.9038
164       maximum: 18727.7
165       range: 18657.8
166       sum: 3.51907e+07
167       mean: 7254.33
168       mean of absolute values: 7254.33
169       population standard deviation: 3468.53
170       population variance: 1.20307e+07
171       population coefficient of variation: 0.478132
172       sample standard deviation: 3468.89
173       sample variance: 1.20332e+07
174       kurtosis: -0.605406
175       skewness: 0.238688
176

SEE ALSO

178        db.univar, r.univar, v.db.univar, v.distance, v.neighbors, v.qcount
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AUTHORS

181       Radim Blazek, ITC-irst
182
183       extended by:
184       Hamish Bowman, University of Otago, New Zealand
185       Martin Landa
186
187       Last changed: $Date: 2018-09-30 18:55:29 +0200 (Sun, 30 Sep 2018) $
188

SOURCE CODE

190       Available at: v.univar source code (history)
191
192       Main index | Vector index | Topics index | Keywords index  |  Graphical
193       index | Full index
194
195       © 2003-2019 GRASS Development Team, GRASS GIS 7.6.0 Reference Manual
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199GRASS 7.6.0                                                        v.univar(1)
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