在地理空间中结合分类填充和渐变填充-R [英] Combine Categorical and Gradient Fill in Geospatial - R

问题描述

我正在尝试在地图上填充组合的分类变量和连续变量.因此，举例来说，在下面的示例中，我想显示每个县的KrispyKreme Donut商店数量，通常这是我想在渐变上填充的连续变量.但是我也有一些县禁止用"-1"表示的KrispyKremes县和那些正在建设中的"-2"的县.我想以未映射在渐变上的其他颜色显示这些.我的真实数据中也没有NA.

I'm trying to fill a combined categorical and continuous variable on a map. So, for instance, in my minimally reproducible example below, say I want to display the number of KrispyKreme Donut shops in each county, which is generally a continuous variable I want to fill on a gradient. But I also have counties that forbid KrispyKremes indicated by a "-1" and those that have them under construction "-2". I want to display these in a different color not mapped on the gradient. I also have NA in my real data.

-到目前为止，我所拥有的:

--What I have so far:

library(sf)
library(ggplot2)

nc <- st_read(system.file("shape/nc.shp", package="sf"))
nc$Status<-rep(c(-2,-1,runif(8)), 10)

ggplot(nc) + 
  geom_sf(aes(fill=Status),color = "black") + 
  coord_sf(datum = NA) + 
  theme_minimal()

如果我添加以下行，显然会中断.所以，我知道我的语法有误，但这表明我想尽最大努力做到这一点

It breaks if I add the following line, obviously. So, I know I have the syntax wrong but it indicates what I want to do in as best as I can figure code for this

  scale_fill_manual(breaks= c("-2","-1", >=0),values = c("blue", "yellow", scale_fill_viridis()))

非常感谢您的帮助，我整天都在工作.

Any help is much appreciated, I've been on this all day.

推荐答案

您将需要将连续变量切成不同的类别.

You will need to cut your continuous variable into different categories.

library(sf)
library(ggplot2)
library(dplyr)

# Set seed for reproducibility
set.seed(122)

nc <- st_read(system.file("shape/nc.shp", package="sf"))
nc$Status<-rep(c(-2,-1,runif(8)), 10)

首先，检查变量的分布.

First, check the distribution of your variable.

nc %>%
  filter(Status >= 0) %>%
  pull("Status") %>%
  summary()
#     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
# 0.002789 0.153144 0.602395 0.491287 0.735787 0.906851

我决定根据分位数如下切割变量.

I decided to cut the variable based on the quantile as follows.

nc2 <- nc %>%
  mutate(Status2 = case_when(
    Status == -2 ~ "-2",
    Status == -1 ~ "-1",
    Status >= 0 & Status < 0.15 ~ "0 - 0.15",
    Status >= 0.15 & Status < 0.6 ~ "0.15 - 0.6",
    Status >= 0.6 & Status < 0.75 ~ "0.6 - 0.75",
    Status >= 0.75                ~ "0.75 - 0.91"
  ))

现在， Status2 是一个分类变量.我们可以绘制它并使用 scale_fill_manual 提供颜色.注意，我们需要在 values 参数中提供颜色代码. viridis :: viridis(4)用于基于绿色元素生成四种颜色.

Now Status2 is a categorical variable. We can plot it and use scale_fill_manual to provide colors. Notice that we need to provide the color code in the values argument. viridis::viridis(4) is to generate four colors based on the viridis.

ggplot(nc2) + 
  geom_sf(aes(fill=Status2),color = "black") + 
  coord_sf(datum = NA) + 
  theme_minimal() +
  scale_fill_manual(values = c("blue", "yellow", viridis::viridis(4)))

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