user1701545 - 1 month ago 4

R Question

Below is a code for producing a boxplot using ggplot2 I'm trying to modify in order to suit my problem:

`library(ggplot2)`

set.seed(1)

# create fictitious data

a <- rnorm(10)

b <- rnorm(12)

c <- rnorm(7)

d <- rnorm(15)

# data groups

group <- factor(rep(1:4, c(10, 12, 7, 15)))

# dataframe

mydata <- data.frame(c(a,b,c,d), group)

names(mydata) <- c("value", "group")

# function for computing mean, DS, max and min values

min.mean.sd.max <- function(x) {

r <- c(min(x), mean(x) - sd(x), mean(x), mean(x) + sd(x), max(x))

names(r) <- c("ymin", "lower", "middle", "upper", "ymax")

r

}

# ggplot code

p1 <- ggplot(aes(y = value, x = factor(group)), data = mydata)

p1 <- p1 + stat_summary(fun.data = min.mean.sd.max, geom = "boxplot") + ggtitle("Boxplot con media, 95%CI, valore min. e max.") + xlab("Gruppi") + ylab("Valori")

In my case I do not have the actual data points but rather only their mean and standard deviation (the data are normally distributed). So for this example it will be:

`mydata.mine = data.frame(mean = c(mean(a),mean(b),mean(c),mean(d)),sd = c(sd(a),sd(b),sd(c),sd(d)),group = c(1,2,3,4))`

However I would still like to produce a boxplot. I thought of defining:

ymin = mean - 3*sd

lower = mean - sd

mean = mean

upper = mean + sd

ymax = mean + 3*sd

but I don't know how to define a function that will access mean and sd of mydata.mine from fun.data in stat_summary. Alternatively, I can just use

`rnorm`

Answer

```
ggplot(mydata.mine, aes(x = as.factor(group))) +
geom_boxplot(aes(
lower = mean - sd,
upper = mean + sd,
middle = mean,
ymin = mean - 3*sd,
ymax = mean + 3*sd),
stat = "identity")
```

Source (Stackoverflow)

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