Lots of the code you run in this class is actually a big long chain of functions or plot layers, like this set of {dplyr} functions that are all connected with %>%s or this set of {ggplot2} functions that are all connected with +s:
library(tidyverse)library(gapminder)library(scales)gapminder_gdp_thing <- gapminder %>%filter(year >1990) %>%mutate(gdp_total = gdpPercap * pop, is_africa =ifelse(continent =="Africa", "Is Africa", "Isn't Africa")) %>%group_by(year, continent) %>%mutate(gdp_above_continent_median =ifelse(gdp_total >median(gdp_total), TRUE, FALSE)) %>%ungroup() %>%arrange(desc(gdp_total)) %>%mutate(continent =fct_inorder(continent), country =fct_inorder(country))ggplot(gapminder_gdp_thing, aes(x = pop, y = gdp_total, color = gdp_above_continent_median)) +geom_point(aes(shape = continent), size =1, alpha =0.75) +geom_smooth(method ="lm") +scale_x_log10(labels =label_comma(scale_cut =cut_short_scale())) +scale_y_log10(labels =label_dollar(scale_cut =cut_short_scale())) +scale_color_manual(values =c("#EDAD08", "#6F4070")) +labs(x ="Population", y ="Total GDP", color ="GDP above continent median", shape ="Continent", title ="Relationship between population and GDP", subtitle ="In Africa and not in Africa", caption ="A pretty meaningless plot, but it has a lot of layers, so.") +facet_grid(rows =vars(is_africa), vars(cols = year)) +theme_bw() +theme(legend.position ="bottom", legend.box ="vertical", plot.title =element_text(face ="bold", size =rel(1.3)),panel.grid.minor =element_blank())
Inevitably, something will go wrong at some point in the chain—often a misspelled word or a misplaced comma or a misplaced parenthesis. Tracking down (or debugging) the issue can be often be tricky!
For example, four (4) things are wrong in this code. See if you can spot them without running it—good luck!
It’s nearly impossible to figure out what’s wrong here without running it. And even if you do run it, you’ll get somewhat cryptic errors.
I have two important techniques and tips that fix 90% of my debugging problems:
Reformat the code by reindenting it and breaking it into multiple lines
Run the code incrementally, line by line
Each of these techniques help track down issues in the code above and are good skills to know in general. I’ll explain each approach and give a little video demonstration below.
Reformat the code
In the R style suggestions in the Resources section, it explains that each layer of a %>%-chained pipeline or ggplot plot should be on separate lines, with the %>% or the + at the end of the line, indented with two spaces.
RStudio can actually reindent code for you automatically, and it can use either of these approaches. If you want the first approach (where argument names align after the opening (), check “Tools > Global Options > Code > Vertically align arguments in auto-indent”; if you want the second approach (where argument names are all a little indented from where the argument starts), make sure that option is unchecked.
To have RStudio reindent code for you, select the code you want to be reindented and go to “Code > Reindent lines”, or use the keyboard shortcut ⌘I on macOS or ctrl + I on Windows.
Here’s what that looks like. Notice how distorted the indentation is initially—RStudio is smart enough to fix it all:
Not only does reindentation make it easier to read your code, it can reveal issues with the code. Remember that code from the beginning of this post with four things wrong? If we reindent it, the line that starts with is_africa = ifelse( is indented funny—it gets put at the start of the line, when really it should be at the same level as gdp_total, since those are both arguments for the mutate() function. If you look at the line above, you’ll see that there’s a ) after gdpPercap * pop, which closes mutate() prematurely, so is_africa isn’t actually inside mutate(). If we get rid of the ) at the end of pop and reindent again, is_africa shows up in the right place.
Extra strength formatting
Reindenting your code only shifts things around horizontally. If you want more powerful code reformatting, try using “Code > Reformat Code” (or use ⌘⇧A on macOS or ctrl + shift + A on Windows). It’s a more aggressive form of reformatting that will add extra line breaks and other things to make the code more readable:
It doesn’t fix everything—there should be a line break after each %>% in that example ↑ so you’d need to add your own line break before filter(year > 1990) and arrange(desc(gdp_total)), but it works well.
I’d recommend trying to keep things indented consistently as you write your code, and periodically reindenting stuff just to make sure everything is nice and aligned. Ultimately R doesn’t care how your code is indented (other languages do, like Python, where one errant space can mess up everything), but humans do care and nicer indentation will help others (and future you!).
Run the code incrementally
Your code is often a series of functions or layers connected with %>% or +. If something goes wrong at any step in the chain of functions, your code won’t work. When that happens, the best strategy for figuring out what went wrong is to run the code incrementally. Just run a few layers of it at a time and then check to see how it looks. Run the first two lines, look at the results, make sure it worked, the run the first three lines, look at the results, make sure it worked, and so on.
This is also a good approach for writing your code initially. That big gapminder-based plot at the beginning of this post? I didn’t write that all at once. I started with the initialy ggplot() + geom_point(), ran it, then added another layer or two, ran it with those, then added some more layers or changed some settings inside existing layers, then ran it with those, and so on until the whole thing was built.
There are a couple ways to do this. One way is to select just the code you want to run (like from the beginning of ggplot() to right before a + on some layer), then press ⌘ + return on macOS or ctrl + enter on Windows to run just that selection. If it worked as expected, select from the beginning again (i.e. at ggplot()) and go to right before a + on some other layer and run that selection:
If you don’t want to keep using your mouse and want to keep your hands at your keyboard, you can add a # right before a + or %>% to comment it out. That essentially breaks the chain of functions at that point, so when you type ⌘ + return or ctrl + enter, R only runs the code up to that point. Then you can remove the #, put it before another + or %>%, and run it again.
Here’s what my typical process for dealing with weirdly indented, broken code looks like. I try to run the whole thing initially, then when it breaks, I reindent it to see if anything is obvious from that. Then I start running it incrementally and check the results of each step to make sure it works up to that point. I do that over and over until the whole pipeline works.
