Looping through dataframe names and plotting in R - r

Question

I have a dataframe of 12 variables and I'd like to plot exactly one variable against others using ggplot's geom_point(). Wouldn't want to do it manually so i need to loop through the variables making plots.
For example, I have a df like this (simplified to 4 variables for readability):
> head(df)
letters value1 value2 value3
A 1 0 10
B 3 1 9
C 6 0 8
D 76 0 7
E 13 1 6
F 58 1 5
And I'd like to produce two plots where value1 is plotted over value2 and value3.
I've tried this:
plts <- vector()
for (i in names(df)) {
p <- ggplot(df, aes(x=value1, y=i, fill=letters)) + geom_point())
plts <- append(plts, p)
}
but it treats the values 2 & 3 different than the value 1 and produces something like this (e.g., value1 over value3):
Plot of value1 over value3
What should be done to improve this and achieve the goal of having the plots like this:
ggplot(df, aes(x=value1, y=value3, fill=letters)) + geom_point()
Produced without a loop

Answer 1

I think using aes_string() instead of aes will give you what you want. Your problem is caused by the tidyverse's use of non-standard evaluation (NSE).
lapply(
names(df),
function(y) {
df %>% ggplot() + geom_point(aes_string(x="value1", y=y, colour="letters"))
}
)
giving, for example
You can customise the first argument to lapply to select the variables you need.
That said, I think it would be easier and more robust to reformat your data frame to a more helpful layout and then create your plots...
For example,
df %>%
pivot_longer(
cols=c("value2", "value3"),
names_to="Variable",
values_to="y"
) %>%
ggplot() +
geom_point(aes(x=value1, y=y, colour=letters)) +
facet_grid(rows=vars(Variable))
Giving
By the way, using colour=letters is probably more informative than fill=letters when using geom_point.