Displaying R and Python Plots Side by Side in Quarto

Question

I am attempting to display two plots in a Quarto document side by side. The issue is that one is generated through R and the other through Python. Ideally, I would like the plots to appear as they do in this document:

However, this seems to only work for images created by the same method (either both plots are created in R or both are created in Python). Here's the link where I got this example from: https://quarto.org/docs/get-started/computations/rstudio.html

Additionally, here is the code that I am using the create these plots:
R Plot:

```{r, fig.show = 'hold', out.width = '50%'}
#| label: fig-r
#| fig-cap: "Car Weight Vs. MPG Scatterplot (R)"
#| layout-ncol: 2
#| column: page
library(ggplot2)

# Color Scale
mtcars$pc <- predict(prcomp(~wt + mpg, mtcars))[,1]

# Scatter Plot
ggplot(mtcars, aes(wt, mpg, color = pc)) +
  geom_point(shape = 16, size = 5, alpha = 0.4, show.legend = FALSE) +
  theme_minimal() + 
  scale_color_gradient(low = "#0091ff", high = "#f0650e") +
  xlab('Weight (1,000 lbs)') +
  ylab('MPG') +
  ggtitle('Weight Vs. MPG')
```

Python Plot:

```{python, fig.show = 'hold', out.width = '50%'}
#| label: fig-python
#| fig-cap: "Car Weight Vs. MPG Scatterplot (Python)"
#| layout-ncol: 2
#| column: page
import numpy as np
import pandas as pd
import seaborn as sns
import statsmodels.api as sm

mtcars = sm.datasets.get_rdataset('mtcars', 'datasets', cache = True).data
sns.scatterplot(x = "wt", 
                y = "mpg",
                data = mtcars).set_title('Weight Vs. MPG')
                
sns.regplot(x = mtcars['wt'], y = mtcars['mpg'], 
            fit_reg = False)
```

Updated Code:

Output:

Answer 1

You can render a document with both R and python code with the knitr engine specified, if you have the {reticulate} R-package installed in your computer.

And to show plot (figures) side by side we can use pandoc figure divs with layout-ncol=2.

---

---
title: "R and Python"
format: html
engine: knitr
---

::: {layout-ncol=2 .column-page}

```{r}
#| label: fig-r
#| fig-cap: "Car Weight Vs. MPG Scatterplot (R)"
#| echo: false

library(ggplot2)

# Color Scale
mtcars$pc <- predict(prcomp(~wt + mpg, mtcars))[,1]

# Scatter Plot
ggplot(mtcars, aes(wt, mpg, color = pc)) +
  geom_point(shape = 16, size = 5, alpha = 0.4, show.legend = FALSE) +
  theme_minimal() + 
  scale_color_gradient(low = "#0091ff", high = "#f0650e") +
  xlab('Weight (1,000 lbs)') +
  ylab('MPG') +
  ggtitle('Weight Vs. MPG')
```

```{python}
#| label: fig-python
#| fig-cap: "Car Weight Vs. MPG Scatterplot (Python)"
#| echo: false

import numpy as np
import pandas as pd
import seaborn as sns
import statsmodels.api as sm

mtcars = sm.datasets.get_rdataset('mtcars', 'datasets', cache = True).data
sns.scatterplot(x = "wt", 
                y = "mpg",
                data = mtcars).set_title('Weight Vs. MPG')
                
sns.regplot(x = mtcars['wt'], y = mtcars['mpg'], 
            fit_reg = False)
```

:::

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