Sometimes you want to add chunk options to the code chunks in your Quarto documents. They are also in YAML format and are prefixed with a special type of comment (#|). It can look something like this:

```{python}
#| echo: false
from datetime import date
print(date.today())
```

• Add the chunk option above to your document and render the document again.

Notice how we no longer see the code itself, just the output? This is because the echo option specifies just that: whether we see the code or not. There are a number of such chunk options that are useful to know about:

• Check what happens if you change echo: False to eval: False.

Now the code in the code chunk is not run, which means that if you previously added the python inline code it will no longer work because it depends on date from the datetime module that we import in the code chunk. Remove the inline code snippet if you added it. Then try rendering again. Now you should see the code itself but it won’t be run and therefore has no output.

Figure options

There are also options related to figures, but for that we need to actually have some code that produces a figure.

• Change the YAML header to use R instead of Python, remove the Python code chunk and replace it with the following (don’t worry if you don’t understand the R code itself, it’s just as example):

```{r}
library("ggplot2")
library("palmerpenguins")
data(penguins, package = "palmerpenguins")
ggplot(penguins, aes(x      = bill_length_mm,
                     y      = body_mass_g,
                     colour = species)) +
    geom_point(size = 2) +
    theme_bw() +
    labs(x      = "Bill length (mm)",
         y      = "Body mass (g)",
         colour = "Species") +
    ggtitle("Penguin weight and bill length") +
    theme(plot.title = element_text(hjust = 0.5)) +
    scale_colour_manual(values = c("#c1dea0", "#85be42", "#425f21"))
```

When you’ve rendered the document you should see both the code and a figure using the Palmer Penguins dataset Links to an external site.. You should also see a warning along the lines of Removed 2 rows containing missing values.

• Suppress the warning by adding #| warning: false as a chunk option and render.

There are two chunk options related to figure sizes: fig-width and fig-height (expressed in inches). These allow you to experiment with your figures and make them look the way you want.

• Add both the fig-width: 10 and fig-height: 5 chunk options and render.

Note
These two chunk options are only available when using the Knitr engine, not for Jupyter. There is a way to set these for the whole document with Jupyter, though, which we’ll talk more about in the next section of the tutorial.

You can also add captions and alt text using fig-cap and fig-alt, respectively.

• Add a suitable caption and alt text to the figure and render.

If you want to place the caption in the margin of your document you can use the cap-location chunk option.

• Add cap-location: margin to your chunk options and render.

Note

On some quarto versions the cap-location: option may not work as expected. If you experience this, try also adding #| label: fig-penguins to the chunk.

Cross-references

A convenient way to be able to refer to figures in text is by adding a figure label, which will automatically add a figure number before your caption.

• Add a suitable label, e.g. label: fig-penguins to the chunk options.

Cross-references use the @ symbol and the corresponding label. You can thus write some markdown outside of a code chunk and refer to e.g. @fig-penguins, as per the example here. This is extremely useful if you’re writing a paper or a report where you want to refer to figures and content in the markdown text. Quarto even adds a clickable link to the figure itself as well!

Sub-figures

It’s also possible to create sub-figures using Quarto, instead of using whatever plotting library that your created the figures with.

• Add the following (almost identical) code at the bottom of the chunk you already have:

ggplot(penguins, aes(x      = bill_depth_mm,
                     y      = body_mass_g,
                     colour = species)) +
    geom_point(size = 2) +
    theme_bw() +
    labs(x      = "Bill depth (mm)",
         y      = "Body mass (g)",
         colour = "Species") +
    scale_colour_manual(values = c("#c1dea0", "#85be42", "#425f21"))

• Also add the following to the chunk options:

#| fig-subcap:
#|     - Bill length vs. body mass
#|     - Bill depth vs. body mass

You should now see that we have two figures with separate sub-captions as well as the overall figure caption we previously added. We can also control the layout of these figures using the layout-ncol chunk option.

• Add a layout-ncol: 2 chunk option and render the document.

We now have a different, two-column layout instead, but whether you prefer this or just a one-column layout is up to you.

Tables

Tables work much in the same way as figures. It might, in our example, be nice to add a table with the data we previously plotted.

• Add the following code chunk to your document and render it:

```{r Penguin table}
#| label: tbl-penguins
#| tbl-cap: Palmer penguins bill length, width and body mass.
#| tbl-cap-location: margin
knitr::kable(
    penguins[1:10, c("species", "bill_length_mm", "bill_depth_mm", "body_mass_g")],
    col.names = c("Species", "Bill length (mm)", "Bill depth (mm)", "Body mass (g)")
)
```

Quick recap
In this section you learned several chunk, figure and table options, how cross-referencing works and how to add sub-figures.