Unable to align tableGrob with barplot (ggplot2) - would like dates in table to align with dates on plot

Question

So, I have made this barplot of categories by date and I want to put a table of the data below it. I'm able to assemble it but I can't get the table to align. It could be anything in my code that's the issue. I was mainly fooling around with patchwork but was trying grid.arrange before that. I would appreciate any help as I am not very familiar with either gridExtra or patchwork.

Here's the data and the code:

SNcats <- structure(list(spec.date = c("2022-01", "2022-01", "2022-01", 
"2022-02", "2022-02", "2022-02", "2022-03", "2022-03", "2022-03", 
"2022-04", "2022-04", "2022-04", "2022-05", "2022-05", "2022-05", 
"2022-06", "2022-06", "2022-06", "2022-07", "2022-07", "2022-07", 
"2022-08", "2022-08", "2022-08", "2022-09", "2022-09", "2022-09", 
"2022-10", "2022-10", "2022-10", "2022-11", "2022-11", "2022-11", 
"2022-12", "2022-12", "2022-12", "2023-01", "2023-01", "2023-01"
), Prevalence = c(35.7532730691516, 51.6020332612438, 87.3553063302596, 
39.8444277893643, 48.2160832971785, 88.0605110865005, 37.8209796975328, 
52.0475030126012, 89.8684827108602, 38.5822017341404, 46.8328075784517, 
85.415009306803, 37.5983114267099, 49.2418346993315, 86.8401461257731, 
37.073216269802, 50.973491711575, 88.0467079815322, 37.4924651917319, 
48.2141737283447, 85.7066389192143, 37.1730646315648, 50.507713438577, 
87.6807780703307, 34.011831202632, 54.668835496198, 88.6806667081123, 
33.4879698539608, 57.2879814032989, 90.7759512541417, 34.6890742481581, 
57.8203887753151, 92.5094630233588, 37.0324544253768, 54.7515011379788, 
91.783955355063, 36.4346779568341, 52.4230523876185, 88.8577303442384
), LL = c(31.0036784955892, 46.6865137568222, 84.0294744708075, 
35.8934911175723, 44.2294678836092, 85.5201746651143, 32.5918045075412, 
46.7021252787722, 86.6574439277593, 35.7332321084506, 43.9378408519578, 
83.2690129542333, 34.8236562801895, 46.4112667974695, 84.8490432647019, 
34.1589303783171, 47.9808527735242, 86.1062268727187, 35.170825504927, 
45.8461086423908, 83.8557052884791, 35.0257696395504, 48.2978225201125, 
86.1304138927419, 32.0510320212288, 52.6197412698121, 87.4441418189029, 
31.7620042685515, 55.4799317423969, 89.7021275089891, 32.9350706471155, 
56.001650789056, 91.5045773434199, 34.7511549769303, 52.4364225437364, 
90.6046115548134, 34.5985811363114, 50.5172303158065, 87.6570267772486
), UL = c(40.5028676427141, 56.5175527656655, 90.6811381897116, 
43.7953644611564, 52.2026987107478, 90.6008475078866, 43.0501548875245, 
57.3928807464302, 93.0795214939611, 41.4311713598303, 49.7277743049456, 
87.5610056593728, 40.3729665732303, 52.0724026011934, 88.8312489868442, 
39.9875021612869, 53.9661306496258, 89.9871890903457, 39.8141048785368, 
50.5822388142986, 87.5575725499494, 39.3203596235792, 52.7176043570414, 
89.2311422479195, 35.9726303840352, 56.7179297225839, 89.9171915973217, 
35.2139354393702, 59.096031064201, 91.8497749992943, 36.4430778492006, 
59.6391267615742, 93.5143487032977, 39.3137538738233, 57.0665797322211, 
92.9632991553127, 38.2707747773567, 54.3288744594304, 90.0584339112283
), SN.cat = structure(c(2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L), levels = c("S+", 
"S+N-", "S+N+"), class = "factor"), group = structure(c(3L, 2L, 
1L, 3L, 2L, 1L, 3L, 2L, 1L, 3L, 2L, 1L, 3L, 2L, 1L, 3L, 2L, 1L, 
3L, 2L, 1L, 3L, 2L, 1L, 3L, 2L, 1L, 3L, 2L, 1L, 3L, 2L, 1L, 3L, 
2L, 1L, 3L, 2L, 1L), levels = c("1", "2", "3"), class = "factor")), row.names = c(NA, 
-39L), class = "data.frame")



SNcats.w <- structure(list(SN.cat = c("S+", "S+N+", "S+N-"), `2022-01` = c("87.4 (84 - 90.7)", 
"51.6 (46.7 - 56.5)", "35.8 (31 - 40.5)"), `2022-02` = c("88.1 (85.5 - 90.6)", 
"48.2 (44.2 - 52.2)", "39.8 (35.9 - 43.8)"), `2022-03` = c("89.9 (86.7 - 93.1)", 
"52 (46.7 - 57.4)", "37.8 (32.6 - 43.1)"), `2022-04` = c("85.4 (83.3 - 87.6)", 
"46.8 (43.9 - 49.7)", "38.6 (35.7 - 41.4)"), `2022-05` = c("86.8 (84.8 - 88.8)", 
"49.2 (46.4 - 52.1)", "37.6 (34.8 - 40.4)"), `2022-06` = c("88 (86.1 - 90)", 
"51 (48 - 54)", "37.1 (34.2 - 40)"), `2022-07` = c("85.7 (83.9 - 87.6)", 
"48.2 (45.8 - 50.6)", "37.5 (35.2 - 39.8)"), `2022-08` = c("87.7 (86.1 - 89.2)", 
"50.5 (48.3 - 52.7)", "37.2 (35 - 39.3)"), `2022-09` = c("88.7 (87.4 - 89.9)", 
"54.7 (52.6 - 56.7)", "34 (32.1 - 36)"), `2022-10` = c("90.8 (89.7 - 91.8)", 
"57.3 (55.5 - 59.1)", "33.5 (31.8 - 35.2)"), `2022-11` = c("92.5 (91.5 - 93.5)", 
"57.8 (56 - 59.6)", "34.7 (32.9 - 36.4)"), `2022-12` = c("91.8 (90.6 - 93)", 
"54.8 (52.4 - 57.1)", "37 (34.8 - 39.3)"), `2023-01` = c("88.9 (87.7 - 90.1)", 
"52.4 (50.5 - 54.3)", "36.4 (34.6 - 38.3)")), row.names = c(NA, 
-3L), class = c("tbl_df", "tbl", "data.frame"))

library(ggplot2)
library(ggpattern)

g0 <- ggplot(SNcats, aes(x=spec.date, y=Prevalence, color=SN.cat, fill=SN.cat)) +
  geom_bar(stat="identity", position=position_dodge(0.85), width=0.8) +
  geom_errorbar( aes(x=spec.date, ymin=LL, ymax=UL, color="black"),
                 position=position_dodge(0.85), 
                 width=0.3) +   
  geom_bar_pattern(aes(pattern=SN.cat, fill=SN.cat, color=SN.cat),
                              position=position_dodge(0.85),
                              stat="identity") +
  theme_minimal() +
  theme(legend.title = element_blank())+
  labs(x="Date")+
  scale_color_manual(values=c("S+"= "steelblue4", "S+N-"="darkorange", "S+N+"="springgreen4"), aesthetics=c("color", "fill")) +
  scale_pattern_manual(values=c(rep(c('stripe', 'circle', 'crosshatch'),1))) 

library(gridExtra)

tt <- ttheme_default(
  base_size = 9,
  padding = unit(c(2, 4), "mm"),
  # Alternate the row fill colours
  core = list(fg_params=list(hjust = 1, x=1),
              bg_params=list(fill=c("white", "white"))),
  
  # Change column header to white text and red background
  colhead = list(fg_params=list(col="black"),
                 bg_params=list(fill="white")))

tbl <- tableGrob(SNcats.w, rows=NULL, theme=tt)

grid.arrange(g0, tbl, nrow=2, heights=c(1,0.5))

library(patchwork)

layout <- c(
  area(t = 1, l = 1, b = 8, r = 5),
  area(t = 9, l = 1, b = 10, r = 5))  # r = 4 shoves it off the left side

p1 <- g0 + tbl + plot_layout(design=layout) 

p1

Answer 1

Your table plot needs to have the same x axis scale as your main plot. I would use only your first dataframe to generate both plots here.

Your main plot is problematic. Using dodged bars here is unnecessary, makes it harder to see the patterns in the data, and distorts the apparent time group measurements were taken. The patterns in the bars don't add anything to the information shown and seem to be purely for decoration, yet they make everything look cluttered and less aesthetically appealing. I would probably use error bars and ribbons here:

library(tidyverse)
library(patchwork)

p1 <- SNcats %>%
  mutate(spec.date = lubridate::ym(spec.date)) %>%
  ggplot(aes(spec.date, Prevalence, ymin = LL, ymax = UL)) +
  geom_ribbon(aes(color = SN.cat, fill = after_scale(alpha(color, 0.1))),
              linetype = 0) +
  geom_errorbar(aes(color = SN.cat), width = 1) +
  geom_point(aes(color = SN.cat)) +
  scale_color_brewer(palette = "Set1") +
  theme_minimal() +
  scale_x_date(NULL, date_breaks = "month", date_labels = "%Y-%m") +
  theme(legend.position = "top")

 p2 <- SNcats %>%
  mutate(spec.date = lubridate::ym(spec.date)) %>%
  ggplot(aes(spec.date, SN.cat)) +
  geom_text(aes(label = paste0(round(Prevalence, 1), "\n",
                               " (", round(LL, 1),  " - ", 
                               round(UL, 1), ")")), size = 2.5) +
  scale_x_date(NULL, date_breaks = "month", date_labels = "%Y-%m",
               position = "top") +
  theme_void() +
  theme(axis.text.y = element_text())
 
p1 + p2 + plot_layout(heights = c(3, 1))