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I am in a bit of a struggle and I can't find a solution (it should be very simple) my Code is this

df Ch1 V1 V2 ID A a1 a2 1 B b1 b2 2 C a1 b2 1 D d1 d2 3 ...

in total we have values ranging from 1 to 9. I simply want to plot how often 1(,2,3,...,9) occurs in this data frame. My code is this

ggplot(df,aes(ID))+ #because I read that leaving y value makes ggplot count the occurences which is T geom_bar()+

This works but unfortunately I get this as a result enter image description here I want all values to be displayed though. I tried to modify this with scale_x_continuous but it didn't work (made the whole x-axis go away and display only 1)

I know I can also create a table = table(df)

But I want to find a universal solution. Because later I want to be able to apply this while making several bars per x-axis value with dependency on V1 or V2 ...

Thank you very much for your help!

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    Convert ID to a factor then plot. Commented Jan 24, 2020 at 0:50
  • Perfect worked - easy as that. I actually did factor(ID). Commented Jan 24, 2020 at 0:54
  • If I would like to plot V1 with different bars depending on how often ID-value occurs for V1-value, how exactly would I do that? Commented Jan 24, 2020 at 1:09
  • I am trying this ggplot(data=df%>% gather(Variable, ID, -V1), aes(x = factor(reorder(V1,-ID)), fill = Variable)) Commented Jan 24, 2020 at 1:17
  • Just add fill = V1 to the aesthetic. You shouldn't need to reshape your data. ggplot(df, aes(x = ID, fill = V1)) + geom_bar() The bars are stacked by default - if you don't want this use geom_bar(position = "dodge"). Commented Jan 24, 2020 at 1:26

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According to the OP, the intention is to create

several bars per x-axis value with dependency on V1 or V2

This can be solved either by using fill = V1 and position = "dodge" as already suggested H 1 or by facetting. Both approaches have their merits depending on the aspect the OP wants to focus on.

Note that in all variants ID is turned into a discrete variable (using factor()) and by overriding the default axis title to solve the issue with labeling the x-axis.

Dogded position

library(ggplot2) ggplot(df) + aes(x = factor(ID), fill = V1) + geom_bar(position = "dodge") + xlab("ID")

enter image description here

This is good if the focus is on comparing the differences between V1 within each ID value.

Facets

library(ggplot2) ggplot(df) + aes(x = factor(ID), fill = V1) + geom_bar() + xlab("ID") + facet_wrap(~ V1, nrow = 1L)

enter image description here

Here, the focus is on comparing the distribution of ID counts within each V1.

Colouring the bars in addition to faceting is redundant (but I find it aesthetically more pleasing as compared to all-black bars).

Data

As there were no reproducible data supplied in the question, I have tried to simulate the data by

nr <- 1000L set.seed(123L) # required to reproduce the data df <- data.frame(Ch1 = sample(LETTERS[1:4], nr, TRUE), V1 = paste0(sample(letters[1:4], nr, TRUE), "1"), V2 = paste0(sample(letters[1:4], nr, TRUE), "2"), ID = pmin(1L + rgeom(nr, 0.3), 9L) )

"Raw" plot for comparison with OP's chart

library(ggplot2) ggplot(df) + aes(x = ID) + geom_bar()

enter image description here

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