Correctly plotting geom_errorbar() to fit the min/max of a group

October 16, 2022

I have some data which takes in predictions and actual results. The predictions take on a range and I plot the average also.

I want to add a geom_errorbar() to display the range by each group. The best I can do is to take the range across the whole group.

I currently have:

x %>%
  ggplot(aes(x = Fecha, y = MC_Clientes, color = Type, group = Zona)) +
  geom_point() +
  stat_summary(geom = "point", fun = "mean", col = "black", size = 3, shape = 24, fill = "red") +
  geom_errorbar(aes(ymin = min(MC_Clientes), ymax = max(MC_Clientes)), width = 0.2) +
  #geom_hline(aes(yintercept = mean(MC_Clientes)), color="blue") +
  facet_wrap(~ Zona)

But I would like only the error bars to display for the predictions – and to only consider the min/max for that given day.

Data:

    x = structure(list(Fecha = structure(c(18993, 19448, 19723, 19631, 
19997, 19083, 19631, 19174, 19631, 19539, 19905, 18993, 19083, 
19266, 19448, 19083, 19358, 19723, 19539, 19358, 19358, 19814, 
19266, 17987, 19723, 19723, 19083, 19723, 17987, 18993, 18993, 
19174, 19814, 19905, 19997, 19539, 19266, 19358, 19905, 18993, 
19723, 18993, 19174, 19814, 19448, 19358, 18262, 19266, 19083, 
18536, 18628, 19448, 19083, 19997, 19997, 19723, 19448, 19723, 
19997, 19266), class = "Date"), MC_Clientes = c(`10` = 3.30914630982938, 
`163` = 3.40705102004165, `148` = 3.27210950513308, `225` = 3.30737187089665, 
`114` = 3.27216488807394, `156` = 3.29952915488204, `110` = 3.39960342129031, 
`65` = 3.44020887082005, `226` = 3.3477486021078, `72` = 3.37828428718909, 
`89` = 3.35889902349877, `130` = 3.24841711499344, `33` = 3.39557631661649, 
`96` = 3.30867139996011, `48` = 3.29220186390159, `39` = 3.38775370812839, 
`11` = 3.33638404617856, `28` = 3.34128523097663, `196` = 3.32642364225741, 
`20` = 3.30914630982938, `15` = 3.32250928717776, `59` = 3.38775370812839, 
`215` = 3.30737187089665, 3.23830671159728, `143` = 3.262723490499, 
`144` = 3.28580416922959, `154` = 3.19317306859439, `146` = 3.22387486690392, 
3.50997312704934, `125` = 3.2916234598844, `128` = 3.27210950513308, 
`68` = 3.42813783609873, `57` = 3.36530584016227, `204` = 3.43236203716387, 
`118` = 3.3861339757903, `192` = 3.4510934126958, `211` = 3.26617681913074, 
`140` = 3.24841711499344, `87` = 3.43574132492634, `2` = 3.30010088087279, 
`27` = 3.33539993355129, `129` = 3.27777616345452, `184` = 3.43236203716387, 
`55` = 3.31622658677549, `42` = 3.34351801788172, `132` = 3.28169122393979, 
3.18803129400015, `92` = 3.35020429586366, `157` = 3.39074839564108, 
3.11563497015824, 3.40541198110811, `166` = 3.29952915488204, 
`38` = 3.29220186390159, `111` = 3.25522990668431, `113` = 3.26178511373003, 
`150` = 3.24841711499344, `167` = 3.39074839564108, `22` = 3.30010088087279, 
`233` = 3.40771653641682, `214` = 3.26936263234189), Zona = c("A", 
"B", "B", "B", "A", "B", "A", "A", "B", "A", "A", "B", "A", "A", 
"A", "A", "A", "A", "B", "A", "A", "A", "B", "B", "B", "B", "B", 
"B", "A", "B", "B", "A", "A", "B", "A", "B", "B", "B", "A", "A", 
"A", "B", "B", "A", "A", "B", "B", "A", "B", "B", "A", "B", "A", 
"A", "A", "B", "B", "A", "B", "B"), Type = c("Predictions", "Predictions", 
"Predictions", "Predictions", "Predictions", "Predictions", "Predictions", 
"Predictions", "Predictions", "Predictions", "Predictions", "Predictions", 
"Predictions", "Predictions", "Predictions", "Predictions", "Predictions", 
"Predictions", "Predictions", "Predictions", "Predictions", "Predictions", 
"Predictions", "Actual", "Predictions", "Predictions", "Predictions", 
"Predictions", "Actual", "Predictions", "Predictions", "Predictions", 
"Predictions", "Predictions", "Predictions", "Predictions", "Predictions", 
"Predictions", "Predictions", "Predictions", "Predictions", "Predictions", 
"Predictions", "Predictions", "Predictions", "Predictions", "Actual", 
"Predictions", "Predictions", "Actual", "Actual", "Predictions", 
"Predictions", "Predictions", "Predictions", "Predictions", "Predictions", 
"Predictions", "Predictions", "Predictions")), row.names = c(NA, 
-60L), class = c("tbl_df", "tbl", "data.frame"))

>Solution :

Are you looking for something more like this?

library(tidyverse)

x |>
  group_by(Type, Zona) |>
  mutate(min = min(MC_Clientes),
         max = max(MC_Clientes))|>
  ggplot(aes(x = Fecha, y = MC_Clientes, color = Type, group = Zona)) +
  geom_point()+
  stat_summary(geom = "point", fun = "mean", col = "black", size = 3, shape = 24, fill = "red") +
  geom_errorbar(aes(ymin = min, ymax = max), width = 0.2) +
  #geom_hline(aes(yintercept = mean(MC_Clientes)), color="blue") +
  facet_wrap(~ Zona)

Edit based on comment:


x |>
  group_by(Fecha,Type, Zona) |>
  mutate(min = min(MC_Clientes),
         max = max(MC_Clientes))|>
  ggplot(aes(x = Fecha, y = MC_Clientes, color = Type, group = Zona)) +
  geom_point()+
  stat_summary(geom = "point", fun = "mean", col = "black", size = 3, shape = 24, fill = "red") +
  geom_errorbar(aes(ymin = min, ymax = max), width = 0.2) +
  #geom_hline(aes(yintercept = mean(MC_Clientes)), color="blue") +
  facet_wrap(~ Zona)