Labelled geom_hline in faceted plot

[Nilafhiosagam]

Hi

I would like to add labels to my geom_hline in a faceted plot. The y value would vary be facet

Right now I have:

df %>% 
  ggplot(aes(name, value)) +
  geom_point(size = 5) +
  geom_hline(aes(yintercept = upper_limit)) +
  geom_hline(aes(yintercept = lower_limit)) +
  facet_wrap(~process_attribute, scales = "free" ) +
  labs(x = "Batch", y = "Value") +
  theme_light()

I'm not sure how I can use geom_text or annotate to add "Upper CL" and "Lower CL" to the lines

Thanks

structure(list(process_attribute = c("Yield (%)", "Yield (%)", 
"Plates at Column Pack", "Plates at Column Pack", "Asymmetry at Column Pack", 
"Asymmetry at Column Pack", "Eluate Concentration (mg/mL)", "Eluate Concentration (mg/mL)", 
"Eluate Volume (CV)", "Eluate Volume (CV)", "Eluate pH", "Eluate pH", 
"Eluate Conductivity (mS/cm)", "Eluate Conductivity (mS/cm)"), 
    name = c("eng_1", "eng_2", "eng_1", "eng_2", "eng_1", "eng_2", 
    "eng_1", "eng_2", "eng_1", "eng_2", "eng_1", "eng_2", "eng_1", 
    "eng_2"), value = c(90, 72, 1005, 804, 1, 0.8, 14, 11.2, 
    4, 3.2, 4.5, 3.6, 3, 2.4), type = c("KPA", "KPA", "KPA", 
    "KPA", "KPA", "KPA", "KPA", "KPA", "PA", "PA", "PA", "PA", 
    "PA", "PA"), data_normal = c("Yes", "Yes", "No", "No", "No", 
    "No", "Yes", "Yes", "Yes", "Yes", "No", "No", "No", "No"), 
    ppk = c(7.7, 7.7, NA, NA, NA, NA, 2.94, 2.94, NA, NA, NA, 
    NA, NA, NA), upper_limit = c(NA, NA, NA, NA, 1.6, 1.6, 20.6, 
    20.6, 3.7, 3.7, 4.64, 4.64, 3.2, 3.2), lower_limit = c(70, 
    70, 1000, 1000, 0.8, 0.8, 4.7, 4.7, 1.1, 1.1, 4.25, 4.25, 
    0.4, 0.4), upper_control_limit = c(NA, NA, NA, NA, NA, NA, 
    12.9, 12.9, NA, NA, NA, NA, NA, NA), lower_control_limit = c(82, 
    82, NA, NA, NA, NA, 8.6, 8.6, NA, NA, NA, NA, NA, NA)), row.names = c(NA, 
-14L), class = c("tbl_df", "tbl", "data.frame"))

[FJCC]

Here are two methods to label the limits. The limit values seem to be mislabeled in your data, by the way. I much prefer the second method because placing the text is hard to do in a way that works in all cases.

library(ggplot2)
library(dplyr, warn.conflicts = FALSE)
library(tidyr)

DF <- structure(list(process_attribute = c("Yield (%)", "Yield (%)", 
                                           "Plates at Column Pack", "Plates at Column Pack", "Asymmetry at Column Pack", 
                                           "Asymmetry at Column Pack", "Eluate Concentration (mg/mL)", "Eluate Concentration (mg/mL)", 
                                           "Eluate Volume (CV)", "Eluate Volume (CV)", "Eluate pH", "Eluate pH", 
                                           "Eluate Conductivity (mS/cm)", "Eluate Conductivity (mS/cm)"), 
                     name = c("eng_1", "eng_2", "eng_1", "eng_2", "eng_1", "eng_2", 
                              "eng_1", "eng_2", "eng_1", "eng_2", "eng_1", "eng_2", "eng_1", 
                              "eng_2"), 
                     value = c(90, 72, 1005, 804, 1, 0.8, 14, 11.2, 
                              4, 3.2, 4.5, 3.6, 3, 2.4), 
                     type = c("KPA", "KPA", "KPA", "KPA", "KPA", "KPA", "KPA", "KPA", "PA", "PA", "PA", "PA", 
                              "PA", "PA"), 
                     data_normal = c("Yes", "Yes", "No", "No", "No","No", "Yes", "Yes", "Yes", "Yes", "No", "No", "No", "No"), 
                     ppk = c(7.7, 7.7, NA, NA, NA, NA, 2.94, 2.94, NA, NA, NA, 
                             NA, NA, NA), 
                     upper_limit = c(NA, NA, NA, NA, 0.8, 0.8, 4.7, 
                                     4.7, 1.1, 1.1, 4.25, 4.25, 0.4, 0.4), 
                     lower_limit = c(70,70, 1000, 1000, 1.6, 1.6, 20.6, 20.6, 3.7, 3.7, 4.64, 4.64, 
                                    3.2, 3.2), 
                     upper_control_limit = c(NA, NA, NA, NA, NA, NA,8.6, 8.6, NA, NA, NA, NA, NA, NA), 
                     lower_control_limit = c(82,82, NA, NA, NA, NA, 12.9, 12.9, NA, NA, NA, NA, NA, NA)), 
                row.names = c(NA, -14L), class = c("tbl_df", "tbl", "data.frame"))
DF %>% 
  ggplot(aes(name, value)) +
  geom_point(size = 5) +
  geom_hline(aes(yintercept = upper_limit)) +
  geom_hline(aes(yintercept = lower_limit)) +
  geom_text(aes(x = 0.7, y = upper_limit), label = "UCL", size = 3, vjust = -0.3) +
  geom_text(aes(x = 0.7, y = lower_limit), label = "LCL", size = 3, vjust = 1) +
  facet_wrap(~process_attribute, scales = "free" ) +
  labs(x = "Batch", y = "Value") +
  theme_light()
#> Warning: Removed 4 rows containing missing values (geom_hline).
#> Warning: Removed 4 rows containing missing values (geom_text).

Limits <- DF %>% select(process_attribute, upper_limit, lower_limit) %>% 
  pivot_longer(cols = c("upper_limit", "lower_limit"), names_to = "LimitType") %>% 
  unique()

DF %>% 
  ggplot(aes(name, value)) +
  geom_point(size = 5) +
  geom_hline(aes(yintercept = value, color = LimitType), data = Limits) +
  facet_wrap(~process_attribute, scales = "free" ) +
  labs(x = "Batch", y = "Value") +
  theme_light()
#> Warning: Removed 2 rows containing missing values (geom_hline).

^{Created on 2021-03-30 by the reprex package (v0.3.0)}

[Nilafhiosagam]

Thank you that exactly what I need

Much appreciated