The goal of valuemap is to save data analysts’ efforts & time with pre-set sf polygon visualization.
You can also visualize with plain data.frame based on H3 addresses
To install the stable version from CRAN, simply run the following from an R console:
install.packages('valuemap')
To install the latest development builds directly from GitHub, run this instead:
if (!require('remotes')) install.packages('remotes')
remotes::install_github('Curycu/valuemap')
Your data must have two columns named as name & value
name column is used for mouse over popup informationvalue column is used for mouse over popup information & color polygons & display center number of polygonslibrary(valuemap)
data('seoul')
seoul
#> Simple feature collection with 25 features and 2 fields
#> Geometry type: POLYGON
#> Dimension: XY
#> Bounding box: xmin: 126.7643 ymin: 37.42901 xmax: 127.1836 ymax: 37.70108
#> Geodetic CRS: WGS 84
#> # A tibble: 25 x 3
#> name value geometry
#> <chr> <int> <POLYGON [arc_degree]>
#> 1 1111 17 ((126.969 37.56819, 126.968 37.56718, 126.9679 37.5671, 126.9673~
#> 2 1114 15 ((127.0163 37.55301, 127.0132 37.54994, 127.0117 37.54851, 127.0~
#> 3 1117 16 ((126.9825 37.51351, 126.9801 37.51212, 126.9756 37.5123, 126.96~
#> 4 1120 17 ((127.0628 37.54019, 127.0566 37.5291, 127.0491 37.53255, 127.04~
#> 5 1121 15 ((127.0923 37.52679, 127.0904 37.526, 127.0885 37.52549, 127.087~
#> 6 1123 14 ((127.0786 37.57186, 127.0782 37.57094, 127.0778 37.57008, 127.0~
#> 7 1126 16 ((127.0958 37.5711, 127.0957 37.5711, 127.0955 37.57105, 127.095~
#> 8 1129 20 ((127.0245 37.5792, 127.0232 37.57804, 127.0225 37.5781, 127.018~
#> 9 1130 13 ((127.022 37.61229, 127.0207 37.6125, 127.0206 37.61252, 127.020~
#> 10 1132 14 ((127.0464 37.63916, 127.0455 37.63783, 127.0453 37.63749, 127.0~
#> # ... with 15 more rows Quick & easy visualization of sf polygons with value
Emphasize greater or equal to 20 polygons (>= 20, < 20 : two level only)
valuemap(seoul, legend.cut=c(20))Visualize without center number on polygons
valuemap(seoul, legend.cut=c(15,17,20), show.text=FALSE)Change color palette & center number on polygons text color, format & change background map
valuemap( seoul, map=leaflet::providers$Stamen.Toner, palette='YlOrRd', text.color='blue', text.format=function(x) paste(x,'EA') )You can visualize based on plain data.frame with h3 address
data('seoul_h3')
seoul_h3
#> # A tibble: 1,329 x 2
#> name value
#> <chr> <dbl>
#> 1 8830e03449fffff 4
#> 2 8830e03453fffff 3
#> 3 8830e0345bfffff 3
#> 4 8830e034c9fffff 3
#> 5 8830e03601fffff 4
#> 6 8830e03603fffff 4
#> 7 8830e03605fffff 4
#> 8 8830e03607fffff 4
#> 9 8830e03609fffff 3
#> 10 8830e0360bfffff 4
#> # ... with 1,319 more rows
valuemap_h3(seoul_h3, legend.cut=1:6, show.text=FALSE)
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