labs | experiments created by me to explain some concept | Data Visualization library

So, this is a good opportunity to use purrr::map. You are half way there by applying code to one dataframe.

You can take the code that you have written above and put it into a function.

We can loop over the list 'l' with lapply, then get the table for each of the columns by looping over the columns with sapply after converting the column to factor with levels specified as 'u', get the proportions, transpose, convert to data.frame (as.data.frame), split by row (asplit - MARGIN = 1), then use transpose from purrr to change the structure so that each column from all the list elements will be blocked as a single unit, bind them with bind_rows

When you know all your 90 bacci names in front of plotting, you can try.

Tidyverse solution: You use your inputs to filter the dataset, right before plotting it. Therefore you need to get the data in long format with tidyr::pivot_longer() before.
Afterwards you can filter here:

Answer

You have to add the font.family argument to fviz_pca:

Flipping the 2nd plot

To achieve this, we need to add two functions:

• scale_y_reverse: This will flip the y axis; 0 is at the top, 10 at the bottom.
• scale_x_discrete(position = top): This will put the x-axis at the top.

Fixing the y-axis limits

It would be best to keep the same y-axis limits for both plots, to make them comparable. As such, we have to supply ylim() to the first plot. For the second plot, we already have scale_y_reverse, so we can supply our limits there.

Fixing the x labels

Since you only want the labels to appear once, you'd have to use element_blank() for theme(axis.text.x) and theme(axis.title.x) in the 2nd plot. Similarly, I would remove the x-axis title in the first plot to keep it balanced.

Combining the plots

Now, you want to combine the plots. However, the first plot has a lot of information on the x-axis, while the second plot doesn't. This means they have different heights. I like to use cowplot::plot_grid for combining plots, because it allows you to set the relative height of the plots. In this case, we can use it to account for the height difference between the two plots.

Final code

You can specify the legend shape using key_glyph and then manually specify the shape by type the same way you have done for fill.

You could alternatively shift the relevant data up:

To solve the syntax error you have to create an dynamic query using a cursor: