osm.getFrequency

Get Frequency Table

osm.getFrequency(indf, inword = "shop", removeNA = T)

Arguments

indf

The vec

inword

Boole

removeNA

Ad

Value

A nice histogram of a single variable with an additional Cumulative Density curve.

See also

Other osm: osm.ClipSFnetwork_with_poly(), osm.CreateEmptyRaster(), osm.bb_2_pol(), osm.combineAmenities(), osm.combineShops(), osm.getLength_footway(), osm.getPOI_usingbb(), osm.getPOI(), osm.getRoads(), osm.osmdata_result_2_bbox_pol()

Author

Dimitris Kavroudakis dimitris123@gmail.com

Examples

library(goal)
sh = osm.getPOI(inPerioxi = "Mytilene Municipal Unit", inkey = "shop")
#> Issuing query to Overpass API ...
#> Announced endpoint: gall.openstreetmap.de/
#> Query complete!
#> converting OSM data to sf format
shops = osm.combineShops(sh)
#> Warning: st_centroid assumes attributes are constant over geometries
#> Warning: GDAL Error 1: PROJ: proj_as_wkt: DatumEnsemble can only be exported to WKT2:2019
#> Warning: GDAL Error 1: PROJ: proj_as_wkt: DatumEnsemble can only be exported to WKT2:2019
#> Warning: st_centroid assumes attributes are constant over geometries
#> Warning: GDAL Error 1: PROJ: proj_as_wkt: DatumEnsemble can only be exported to WKT2:2019
freq2 = osm.getFrequency(shops, inword = "shop", removeNA = F)
freq2
#> # A tibble: 93 × 3
#>    shop            n  freq
#>  * <chr>       <int> <dbl>
#>  1 NA            463 40.1 
#>  2 clothes        91  7.88
#>  3 convenience    62  5.37
#>  4 hairdresser    40  3.46
#>  5 jewelry        27  2.34
#>  6 bakery         25  2.16
#>  7 supermarket    25  2.16
#>  8 kiosk          24  2.08
#>  9 shoes          22  1.90
#> 10 butcher        20  1.73
#> # ℹ 83 more rows