stacked barplot with errorbars -> errorbars are off

Ingo Miller

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Nov 10, 2021, 10:21:06 AM11/10/21

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Hi,

I'm trying to create a stacked faceted barplot with errorbars for percent data. The problem is that the errorbars seem to be off somehow.

Here's what I did: (I post the input data in the comment below.)

library(ggplot2); library(ggthemes); library(plyr); library(dplyr); library(patchwork); library(lemon)

DF$effect <- factor(DF$effect,levels = c("swimming", "metamorphosis", "settlement", "dead"))

DF$treatment = factor(DF$treatment, levels = c('NEG', 'CCA', '10', '20', '30', '40'))

DF$time = factor(DF$time, levels = c('T0','T13.5','T22', 'T31', 'T38.5', 'T55.5', 'T155.5'))

ggplot(data=DF, aes(x=treatment, y=mean, ymax=110, fill=effect)) +

geom_bar(stat="identity", position='stack', width = 0.5)+

labs(x='Treatment', y="% Response (Mean ± SE)", size=12)+

scale_fill_manual(values=c('steelblue2','gray60', 'coral', 'lightpink'))+

facet_rep_wrap(~ time, ncol=2, scales='fixed', repeat.tick.labels = 'top')+

geom_errorbar(aes(ymin=mean-se, ymax=mean+se), width=0.1, size=0.1, position='identity')+

scale_y_continuous(expand = c(0,0), limit=c(0, 110)) +

scale_color_manual(values=c('steelblue2','gray60', 'coral', 'lightpink'))+

theme_bw()

And here's the resulting plot with errorbars all over the place:

Then I tried the follwoing to re-arrange the stacked error-bars:

DF1 <- within(DF, mean2 <- ave(mean,time,treatment,FUN=cumsum))

ggplot(data=DF1, aes(x=treatment, y=mean, ymax=110, fill=effect)) +

geom_bar(stat="identity", position='stack', width = 0.5)+

labs(x='Treatment', y="% Response (Mean ± SE)", size=12)+

scale_fill_manual(values=c('steelblue2','gray60', 'coral', 'lightpink'))+

facet_rep_wrap(~ time, ncol=2, scales='fixed', repeat.tick.labels = 'top')+

geom_errorbar(aes(ymin=mean2-se, ymax=mean2+se), width=0.1, size=0.1, position='identity')+

scale_y_continuous(expand = c(0,0), limit=c(0, 110)) +

scale_color_manual(values=c('steelblue2','gray60', 'coral', 'lightpink'))+

theme_bw()

And this results in the follwing plot whith errorbars still not where they should be. Does anyone know how to solve this problem?

Cheers,

Ingo

Ingo Miller

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Nov 10, 2021, 10:21:41 AM11/10/21

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structure(list(time = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,

3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,

4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,

4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,

5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,

6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,

6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,

7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L), .Label = c("T0", "T13.5",

"T22", "T31", "T38.5", "T55.5", "T155.5"), class = "factor"),

treatment = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,

3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L,

1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L,

4L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 1L, 1L, 1L, 1L, 2L, 2L,

2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 6L,

6L, 6L, 6L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,

4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 1L, 1L, 1L,

1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L,

5L, 5L, 6L, 6L, 6L, 6L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,

3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L

), .Label = c("NEG", "CCA", "10 µg", "20 µg", "30 µg", "40 µg"

), class = "factor"), effect = structure(c(1L, 2L, 3L, 4L,

1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L,

4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L,

3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,

2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L,

1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L,

4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L,

3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,

2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L,

1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L,

4L, 1L, 2L, 3L, 4L), .Label = c("swimming", "metamorphosis",

"settlement", "dead"), class = "factor"), mean = c(100, 0,

0, 0, 0, 0, 100, 0, 100, 0, 0, 0, 100, 0, 0, 0, 100, 0, 0,

0, 80, 20, 0, 0, 100, 0, 0, 0, 0, 0, 100, 0, 100, 0, 0, 0,

100, 0, 0, 0, 86.667, 6.667, 6.667, 0, 6.667, 60, 33.333,

0, 100, 0, 0, 0, 0, 0, 100, 0, 100, 0, 0, 0, 100, 0, 0, 0,

86.667, 6.667, 6.667, 0, 0, 13.333, 86.667, 0, 100, 0, 0,

0, 0, 0, 100, 0, 100, 0, 0, 0, 100, 0, 0, 0, 73.333, 6.667,

20, 0, 0, 6.667, 93.333, 0, 100, 0, 0, 0, 0, 0, 100, 0, 100,

0, 0, 0, 100, 0, 0, 0, 80, 0, 20, 0, 0, 0, 100, 0, 100, 0,

0, 0, 0, 0, 100, 0, 86.667, 6.667, 6.667, 0, 33.333, 5.333,

61, 0, 46.667, 0, 46.667, 6.667, 0, 0, 100, 0), se = c(0,

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

11.547, 11.547, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

0, 0, 0, 0, 13.333, 6.667, 6.667, 0, 6.667, 23.094, 17.638,

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13.333,

6.667, 6.667, 0, 0, 6.667, 6.667, 0, 0, 0, 0, 0, 0, 0, 0,

0, 0, 0, 0, 0, 0, 0, 0, 0, 17.638, 6.667, 20, 0, 0, 6.667,

6.667, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

20, 0, 20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13.333,

6.667, 6.667, 0, 33.333, 5.333, 30.892, 0, 24.037, 0, 17.638,

6.667, 0, 0, 0, 0)), row.names = 25:168, class = "data.frame")

Robert Winkelman

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Oct 14, 2022, 7:19:37 PM10/14/22

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I think all the NA's are the cause of the problem. They result in multiple occurrences of what should be a unique row.

Crude patch:

> ggplot(data=DF %>% filter(!is.na(treatment)), ...

The source of the problem in the data:

> DF %>% group_by(time, treatment, effect) %>% mutate(counter = n()) %>% arrange(-counter)

# A tibble: 144 x 6
# Groups: time, treatment, effect [72]
time treatment effect mean se counter
<fct> <fct> <fct> <dbl> <dbl> <int>
1 T13.5 NA swimming 100 10 4
2 T13.5 NA metamorphosis 0 10 4
3 T13.5 NA settlement 0 10 4
4 T13.5 NA dead 0 10 4
5 T13.5 NA swimming 100 10 4
6 T13.5 NA metamorphosis 0 10 4
7 T13.5 NA settlement 0 10 4

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