How can I enumerate and add margin_titles to each subplot in a seaborn lmplot facetgrid?

Question

I have the following attached lmplot facetgrid

To start with, I want to simplify the title of each subplot, to only have corpus = {corpus name}.

I am generating these plots using the lmplot as per

g=sns.lmplot('x', 'y', data=test_plot, col='corpus', hue = 'monotonicity', row='measure', sharey=True, sharex=True, height=2.5,aspect=1.25, truncate=False, scatter_kws={"marker": "D", "s": 20})

g=(g.set_axis_labels("Max-Min (measure)", "Max-Min (comp measure)")
        .set(xlim=(0, 1), ylim=(-.1, 1))
        .fig.subplots_adjust(wspace=.02))

I want to use the facetgrid margin_title option to put the measure value on the right y-axis, but get lmplot() got an unexpected keyword argument 'margin_titles'

I then tried using a facetgrid, as per:

p = sns.FacetGrid(data = test_plot,
                           col = 'corpus',
                           hue = 'monotonicity',
                           row = 'measure',
                           margin_titles=True)
    

p.map(sns.lmplot, 'diff_', 'score_diff',  data=test_plot, he='monotonicity', truncate=False, scatter_kws={"marker": "D", "s": 20})

but then I get an error about lmplot() got an unexpected keyword argument 'color' (cannot figure out why that is being thrown?).

My second problem is that I want to add a letter/enumeration to each subplot's title, as in (a), ..., (i), but for the life of me cannot figure out how to do this.

Answer 1

Because of your custom needs, consider iterating through all the axes of the FacetGrid after running your lmplot. Regarding your specific error, seaborn.lmplot is a FacetGrid so will conflict if nested in another FacetGrid as tried in your second attempt. Also, in below solution, do not re-assign g to axes setup which returns NoneType:

#... SAME lmplot ...

(
  g.set_axis_labels("Max-Min (measure)", "Max-Min (comp measure)")
   .set(xlim=(0, 1), ylim=(-.1, 1))
   .fig.subplots_adjust(wspace=.02)
)

alpha = list('abcdefghijklmnopqrstuvwxyz')
axes = g.axes.flatten()

# ADJUST ALL AXES TITLES
for ax, letter in zip(axes, alpha[:len(axes)]):
    ttl = ax.get_title().split("|")[1].strip()   # GET CURRENT TITLE
    ax.set_title(f"({letter}) {ttl}")            # SET NEW TITLE

# ADJUST SELECT AXES Y LABELS
for i, m in zip(range(0, len(axes), 3), test_plot["measure"].unique()):
    axes[i].set_ylabel(m)

Input (purely random data for demonstration)

import numpy as np
import pandas as pd

np.random.seed(1172021)

test_plot = pd.DataFrame({
    'measure': np.random.choice(["precision", "recall", "F1-score"], 500),
    'corpus': np.random.choice(["Fairview", "i2b2", "MiPACQ"], 500),
    'monotonicity': np.random.choice(["increasing", "non", "decreasing"], 500),
    'x': np.random.uniform(0, 1, 500),
    'y': np.random.uniform(0, 1, 500)
})

Output