在 ggplot2 堆叠条形图中保留缺失数据

Question

This is my sample data. ID 144 contains 6 positions while ID AB01 contains only 3. In a stacked plot I still want to show 6 positions in AB01 with missing positions shown in a specific color.

ID   YEAR  POS
    144 2017   10
    144 2017  12
    144 2017  18
    144 2017  15
    144 2017  163
    144 2017 200
    AB01 2018  10
    AB01 2018 15
    AB01 2018 18

This is what I tried.

ggplot(data1, aes(x = ID, y=1, fill = as.factor(POS))) +
 geom_bar(stat = "identity", position = "stack", exclude = NULL) +
 facet_wrap(~ data1$Year, ncol=1, scale="free") +
 labs(x="Year", y= "Number ", fill = "Position", Title= "Pos plot") +
 theme(text = element_text(size = 15, color = "Black"))

data

data <- structure(list(ID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L), .Label = c("144", "AB01"), class = "factor"), YEAR = c(2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2018L, 2018L, 2018L), POS = c(10L, 12L, 18L, 15L, 163L, 200L, 10L, 15L, 18L)), class = "data.frame", row.names = c(NA, -9L))

Answer 1

Can you use geom_tile instead?

data <- structure(list(ID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L), .Label = c("144", "AB01"), class = "factor"), YEAR = c(2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2018L, 2018L, 2018L), POS = c(10L, 12L, 18L, 15L, 163L, 200L, 10L, 15L, 18L)), class = "data.frame", row.names = c(NA, -9L))

ggplot(data, aes(x = ID, y = as.factor(POS), fill = as.factor(POS))) +
  geom_tile(color = "black") +
  coord_cartesian(expand = F) + # get rid of space around tiles
  theme_classic() # make background white

Answer 2

ggplot(data, aes(x = ID, y = as.factor(POS), fill = as.factor(POS))) +
geom_tile(color = "black") + facet_wrap(~ data1$Year, ncol=2, scale="free_x") + 
coord_cartesian(expand = F) + theme(strip.background = element_blank(), strip.text.x = element_blank())

Answer 3

How about this:

data <- structure(list(ID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L), .Label = c("144", "AB01"), class = "factor"), YEAR = c(2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2018L, 2018L, 2018L), POS = c(10L, 12L, 18L, 15L, 163L, 200L, 10L, 15L, 18L)), class = "data.frame", row.names = c(NA, -9L))



library(ggplot2)
library(forcats)
library(tidyr)
library(dplyr)


data_1 <- 
  data %>% 
  mutate(temp = as.character(POS)) %>%
  complete(ID, POS) %>% 
  mutate(temp = fct_explicit_na(fct_inseq(temp), na_level = "Missing"))


col_map <- c("10" = "powderblue",
             "12" = "red",
             "18" = "orange",
             "15" = "yellow",
             "163" = "green",
             "200" = "blue",
             "Missing" = "White")

ggplot(data_1, aes(x = ID, y = fct_rev(factor(POS)), fill = temp)) +
  geom_tile(color = "black", width = 0.5, height = 0.8) +
  scale_fill_manual(values = col_map)+
  coord_cartesian(expand = F) + 
  labs(x = NULL, 
       y = NULL,
       fill = NULL)+
  theme_classic()+
  theme(axis.ticks = element_blank(),
        axis.text.y = element_blank(),
        axis.text.x = element_text(size = 14),
        axis.line = element_blank())

^{Created on 2020-07-08 by the reprex package (v0.3.0)}