CODEWITHSUNDEEP
rggplot2
Jessica
Jessica

Reputation: 461

confidence interval error bars for ggplot

I want to put confidence interval error bars for ggplot.

I have a dataset and I am plotting it with ggplot as:

df <- data.frame(
        Sample=c("Sample1", "Sample2", "Sample3", "Sample4", "Sample5"), 
        Weight=c(10.5, NA, 4.9, 7.8, 6.9))

p <- ggplot(data=df, aes(x=Sample, y=Weight)) + 
geom_bar(stat="identity", fill="black") + 
scale_y_continuous(expand = c(0,0), limits = c(0, 8)) + 
theme_classic() + 
theme(axis.text.x = element_text(angle = 45, hjust = 1)

p

I am new to adding error bars. I looked at some options using geom_bar but I could not make it work.

I will appreciate any help to put confidence interval error bars in the barplot. Thank you!

Upvotes: 5

Views: 9863

Answers (2)

Denis Cousineau
Denis Cousineau

Reputation: 497

It is possible to generate error bars automatically with a tool called superb (summary plot with error bars).

First, lets have more than one point per sample using random data

df2 <- data.frame(
  Sample = rep(c("Sample1", "Sample2", "Sample3", "Sample4", "Sample5"),5),
  Weight = rep(c(10.5, NA, 4.9, 7.8, 6.9),5)+rnorm(25)
)

Then load the library and ask for the plot (default will be to show 95% confidence intervals):

library(superb)
superb( Weight ~ Sample, df2)

Mean plot of the 5 samples

You can ask for standard error (SE) rather than the default confidence intervals (CI) and add any additional formatting options, for example:

p <- superb( Weight ~ Sample, df2,
  errorbar = "SE" # or CI for confidence intervals
) + 
scale_y_continuous(expand = c(0,0), limits = c(0, 12)) + 
theme_classic() + 
theme(axis.text.x = element_text(angle = 45, hjust = 1))
p

Mean plot of the 5 samples with standard error and formating

Note that I am the creator of superb.

Upvotes: 0

Dij
Dij

Reputation: 1378

Add a layer of error bars with geom_errorbar

df <- data.frame(
  Sample=c("Sample1", "Sample2", "Sample3", "Sample4", "Sample5"), 
  Average.Weight=c(10.5, NA, 4.9, 7.8, 6.9),
  # arbitrarily make up some Standard Errors for each mean:
  SE = c(1, NA, .3, .25, .2)) # JUST MAKING THINGS UP HERE

Now you have a data frame with a column of Average Weight and the SE for each sample in your study. Use ggplot to plot:

ggplot(data = na.omit(df)) + #don't bother plotting the NA
  geom_bar(stat = "identity", aes(x = Sample,y = Average.Weight)) +
  geom_errorbar(
    aes(x=Sample, 
        ymin = Average.Weight - 1.96*SE, 
        ymax = Average.Weight + 1.96*SE), 
    color = "red"
  )

enter image description here

Upvotes: 7

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