tmap: Thematic Maps

{ggplot2}風に操作できる主題図を描くためのパッケージ

> library(tmap)
> data("World")
> data("Europe")
> data("NLD_prov")
> data("NLD_muni")

バージョン: 1.2

関数名 概略
+.tmap Stacking of tmap elements World World, Europe, and Netherlands map
animation_tmap Create animations
append_data Append data to a shape object
approx_areas Approximate area sizes of the shapes
calc_densities Calculate densities
get_IDs Get ID's of the shape items
get_asp_ratio Get aspect ratio
land Spatial data of global land cover
metro Spatial data of metropolitan areas
print.tmap Draw thematic map
qtm Quick thematic map plot
read_shape Read shape file
rivers Spatial data of rivers
sbind Combine shape objects
set_projection Set and get the map projection
split.SpatialPolygonsDataFrame Divide into multiple shape objects
tm_bubbles Draw bubbles
tm_credits Credits text
tm_facets Small multiples
tm_fill Draw polygons
tm_grid Coordinate grid lines
tm_layout Layout elements of cartographic maps
tm_lines Draw spatial lines
tm_raster Draw a raster
tm_scale_bar Scale bar
tm_shape Specify the shape object
tm_text Add text labels
tmap-element tmap element
tmap-package Thematic Maps
write_shape Write shape file

Europe

> data("Europe")
> Europe %>% dim()

[1] 70 15

land

空間データ

> data("land")
> land %>% str()

Formal class 'SpatialGridDataFrame' [package "sp"] with 4 slots
  ..@ data       :'data.frame':    583200 obs. of  4 variables:
  .. ..$ cover    : Factor w/ 20 levels "Broadleaf Evergreen Forest",..: 20 20 20 20 20 20 20 20 20 20 ...
  .. ..$ cover_cls: Factor w/ 8 levels "Forest","Other natural vegetation",..: 8 8 8 8 8 8 8 8 8 8 ...
  .. ..$ trees    : int [1:583200] NA NA NA NA NA NA NA NA NA NA ...
  .. ..$ elevation: int [1:583200] NA NA NA NA NA NA NA NA NA NA ...
  ..@ grid       :Formal class 'GridTopology' [package "sp"] with 3 slots
  .. .. ..@ cellcentre.offset: Named num [1:2] -179.8 -89.8
  .. .. .. ..- attr(*, "names")= chr [1:2] "x" "y"
  .. .. ..@ cellsize         : num [1:2] 0.333 0.333
  .. .. ..@ cells.dim        : int [1:2] 1080 540
  ..@ bbox       : num [1:2, 1:2] -180 -90 180 90
  .. ..- attr(*, "dimnames")=List of 2
  .. .. ..$ : chr [1:2] "x" "y"
  .. .. ..$ : chr [1:2] "min" "max"
  ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot
  .. .. ..@ projargs: chr "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"

metro

空間データ

> data("metro")
> metro %>% str()

Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots
  ..@ data       :'data.frame':    436 obs. of  12 variables:
  .. ..$ name     : chr [1:436] "Kabul" "Algiers" "Luanda" "Buenos Aires" ...
  .. ..$ name_long: chr [1:436] "Kabul" "El Djazair  (Algiers)" "Luanda" "Buenos Aires" ...
  .. ..$ iso_a3   : chr [1:436] "AFG" "DZA" "AGO" "ARG" ...
  .. ..$ pop1950  : num [1:436] 170784 516450 138413 5097612 429249 ...
  .. ..$ pop1960  : num [1:436] 285352 871636 219427 6597634 605309 ...
  .. ..$ pop1970  : num [1:436] 471891 1281127 459225 8104621 809794 ...
  .. ..$ pop1980  : num [1:436] 977824 1621442 771349 9422362 1009521 ...
  .. ..$ pop1990  : num [1:436] 1549320 1797068 1390240 10513284 1200168 ...
  .. ..$ pop2000  : num [1:436] 2401109 2140577 2591388 12406780 1347561 ...
  .. ..$ pop2010  : num [1:436] 3722320 2432023 4508434 14245871 1459268 ...
  .. ..$ pop2020  : num [1:436] 5721697 2835218 6836849 15894307 1562509 ...
  .. ..$ pop2030  : num [1:436] 8279607 3404575 10428756 16956491 1718192 ...
  ..@ coords.nrs : num(0) 
  ..@ coords     : num [1:436, 1:2] 69.17 3.04 13.23 -58.4 -64.18 ...
  .. ..- attr(*, "dimnames")=List of 2
  .. .. ..$ : chr [1:436] "2" "8" "13" "16" ...
  .. .. ..$ : chr [1:2] "Longitude" "Latitude"
  ..@ bbox       : num [1:2, 1:2] -123.1 -37.8 174.8 60.2
  .. ..- attr(*, "dimnames")=List of 2
  .. .. ..$ : chr [1:2] "Longitude" "Latitude"
  .. .. ..$ : chr [1:2] "min" "max"
  ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot
  .. .. ..@ projargs: chr "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0"

qtm

簡単な主題図を描画する

> data("Europe")
> qtm(Europe)

read_shape

shapeファイルの読み込み

> read_shape(file, current.projection = NULL, ...)

tm_shape

> data(World, metro)
> tm_shape(World, projection="longlat") + 
+     tm_polygons() + 
+ tm_layout("Long lat coordinates (WGS84)", inner.margins=c(0,0,.1,0), title.size=.8)

World

> data("World")
> World %>% {
+   print(.)
+   class(.)
+ }

class       : SpatialPolygonsDataFrame 
features    : 177 
extent      : -16656124, 16656124, -8451673, 8375779  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=eck4 +lon_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs +towgs84=0,0,0 
variables   : 15
names       : iso_a3,        name,  sovereignt,     continent,      subregion,         area,    pop_est,    pop_est_dens,  gdp_md_est, gdp_cap_est,                   economy,           income_grp, life_exp, well_being,      HPI 
min values  :    AFG, Afghanistan, Afghanistan,        Africa,     Antarctica,     2590.000,        140,    0.0003498711,       16.00,    300.4693,   1. Developed region: G7, 1. High income: OECD,     47.8,   2.807855, 22.59117 
max values  :    ZWE,    Zimbabwe,    Zimbabwe, South America, Western Europe, 16376870.000, 1338612970, 1198.8237151417, 15094000.00, 200000.0000, 7. Least developed region,        5. Low income,     83.4,   7.770515, 64.03593

[1] "SpatialPolygonsDataFrame"
attr(,"package")
[1] "sp"

> data("Europe")
> data("NLD_prov")
> data("NLD_muni")