R语言tmap绘图报错：as.numeric(...)数据兼容问题求助

研究纽约州门罗县种族数据时，使用R语言获取2020年人口普查tract层级数据，计算种族占比后筛选Black群体数据，调用tmap绘图时出现以下错误和警告：

错误：! Assigned data as.numeric(...) must be compatible with existing data。具体为现有数据211行，赋值数据210行，仅大小为1的向量可循环
警告：The shape monroe_black contains empty units

使用的代码如下：

monroe_race <- get_decennial(
  geography = "tract",
  state = "NY",
  county = "Monroe",
  variables = c(
    Hispanic = "P2_002N",
    White = "P2_005N",
    Black = "P2_006N",
    Native = "P2_007N",
    Asian = "P2_008N"
  ),
  summary_var = "P2_001N",
  year = 2020,
  geometry = TRUE
) %>%
  mutate(percent = 100 * (value / summary_value))

monroe_black <- filter(monroe_race, 
                         variable == "Black")

tm_shape(shp = monroe_black) + 
  tm_polygons()

解决步骤 #

问题根源 #

报错和警告的核心原因是monroe_black数据中存在空几何单元（即部分tract没有有效的多边形边界），导致tmap处理时数据行与几何行数量不匹配，触发赋值错误。

修正代码 #

在筛选Black群体后，添加过滤空几何的操作，确保所有行都有有效几何和对应数据：

library(tidycensus)
library(tmap)
library(dplyr)
library(sf)

monroe_race <- get_decennial(
  geography = "tract",
  state = "NY",
  county = "Monroe",
  variables = c(
    Hispanic = "P2_002N",
    White = "P2_005N",
    Black = "P2_006N",
    Native = "P2_007N",
    Asian = "P2_008N"
  ),
  summary_var = "P2_001N",
  year = 2020,
  geometry = TRUE
) %>%
  mutate(percent = 100 * (value / summary_value))

# 筛选Black群体并移除空几何单元
monroe_black <- monroe_race %>%
  filter(variable == "Black") %>%
  filter(!st_is_empty(geometry))  # 关键：剔除空几何行

# 绘图时明确指定填充变量，避免默认匹配问题
tm_shape(shp = monroe_black) + 
  tm_polygons(col = "percent")

额外说明 #

1. st_is_empty(geometry)函数识别所有几何为空的行，!符号用于反向筛选，保留有有效几何的行。
2. 绘图时指定col = "percent"，明确告诉tmap使用计算好的种族占比作为填充颜色变量，避免默认字段匹配混乱。

内容的提问来源于stack exchange，提问作者Jack