How to annotate regression lines in seaborn lmplot?

Question

I have plotted two variables against each other in Seaborn and used the hue keyword to separate the variables into two categories.

I want to annotate each regression line with the coefficient of determination. This question only describes how to show the labels for a line with using the legend.

 import pandas as pd 
 import seaborn as sns
 import matplotlib.pyplot as plt 

df = pd.read_excel(open('intubation data.xlsx', 'rb'), sheet_name='Data 
(pretest)', header=1, na_values='x')
vars_of_interest = ['PGY','Time (sec)','Aspirate (cc)']
df['Resident'] = df['PGY'] < 4

 lm = sns.lmplot(x=vars_of_interest[1], y=vars_of_interest[2],
        data=df, hue='Resident', robust=True, truncate=True,
        line_kws={'label':"bob"})

Answer 1

Using your code as it is:

 import pandas as pd 
 import seaborn as sns
 import matplotlib.pyplot as plt 

df = pd.read_excel(open('intubation data.xlsx', 'rb'), sheet_name='Data 
(pretest)', header=1, na_values='x')
vars_of_interest = ['PGY','Time (sec)','Aspirate (cc)']
df['Resident'] = df['PGY'] < 4

p = sns.lmplot(x=vars_of_interest[1], y=vars_of_interest[2],
        data=df, hue='Resident', robust=True, truncate=True,
        line_kws={'label':"bob"}, legend=True)
# assuming you have 2 groups
ax = p.axes[0, 0]
ax.legend()
leg = ax.get_legend()
L_labels = leg.get_texts()
# assuming you computed r_squared which is the coefficient of determination somewhere else
label_line_1 = r'$R^2:{0:.2f}$'.format(0.3)
label_line_2 = r'$R^2:{0:.2f}$'.format(0.21)
L_labels[0].set_text(label_line_1)
L_labels[1].set_text(label_line_2)

Voila: Graph created with my own random data since OP hasn't provided any.