Plotting a grouped bar chart using ggplot

im new to R and trying to create a grouped bar chart but having a few issues.
I written some code but the chart doesn't look the way I want it to.

dveR <- data.frame(values = c(3.921, 3.557, 3.793, 3.154, 2.387, 1.906),group = rep(c("Cardia","Anterior","Posterior"),each = 2),subgroup = LETTERS[1:2])

ggplot(dveR,aes(x = group,y = values, fill = subgroup)) + geom_bar(stat = "identity",position = "dodge") + scale_fill_manual(values=c("springgreen4","orange2")

I want the axis labels to be Y=Log Re and X=tissue and I want the order of the bars to be cardia, anterior, posterior but it seems to sort them in to alphabetical order. the subgroup labels should also be 0 hours and 24 but im not sure how to change this. Any help would be appreciated, thanks!

As you are new to R, it's important that you learn about how R treats categorical variables, or factors. If you provide R with a set of character values in a column of a data frame, it tries to infer what you intended those values to represent. As you discovered, it won't always make the correct inference.

When you provide a set of character values in a column of a data frame and then try to use those values in a regression or a graphical display, R will typically treat those values as a factor but will order the levels of the factor alphanumerically. I find that it's safest to convert such columns to factors yourself and specify the order that you desire. One way to do that in this case is:

dveR$group <- factor(dveR$group)
dveR$group <- relevel(dveR$group,ref="Cardia")

A comment suggested that you use the fct_inorder() function from the forcats package to do that directly in ggplot. That package can make such manipulations easier, but I think that you will be better off if you do these manipulations yourself at the start of your learning so that you have a better idea of what's going on.

The labs(x= "tissue", y="Log Re") term suggested in a comment is one way to specify axis labels. You can also use xlab("Tissue") and ylab("Log Re").

You can use additional arguments to scale_fill_manual() to set the name of the legend and the labels of the factor levels.

scale_fill_manual(values = c("springgreen4","orange2"),
                  labels = c("0","24"), name = "Hour")

The danger is that you might then accidentally mix up the order between the original factor levels and what you ask ggplot to display. I find it safer to specify factors in the data frame that explicitly represent what I want to show. For example, in this case:

dveR[,"Hour"] <- ifelse (dveR$subgroup=="A", "0" ,"24")

Then, after re-leveling group and defining Hour as above, you could generate the plot you want with

ggplot(dveR,aes(x = group, y = values, fill = Hour)) + 
       geom_bar(stat = "identity", position = "dodge") + 
       scale_fill_manual(values = c("springgreen4", "orange2")) + 
       xlab("Tissue") + ylab("Log Re")

For this type of data, however, you might not want to show a bar chart at all. As Edward Tufte often notes, such plots use up a lot of space without conveying a lot of information. From this page, for example:

> The bar chart wastes space; you could show at least 100 numbers in the space that now shows 1 number. People read numbers in tables all the time (see the financial section and sports section of any good newspaper) and they don't need bars to see a bar to understand 1 number.

Also, bar charts are sometime misused (in a way that you aren't) by resetting the bottom of the scale to something other than 0, close to the top of the range, to make truly small differences appear very large. So I'd recommend learning how to specify axis labels and legends properly, but choosing a different way to display this type of data.