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valuemap

CRAN Downloads

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

Installation

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')

How to Use?

Your data must have two columns named as name & value
- name column is used for mouse over popup information
- value column is used for mouse over popup information & color polygons & display center number of polygons

library(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

Example 1

Quick & easy visualization of sf polygons with value
valuemap(seoul)

Example 2

Emphasize greater or equal to 20 polygons (>= 20, < 20 : two level only)
valuemap(seoul, legend.cut=c(20))

Example 3

Visualize without center number on polygons
valuemap(seoul, legend.cut=c(15,17,20), show.text=FALSE)

Example 4

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')
)

Example 5

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)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.