How to Extract Linear Model Parameters from Seaborn lmplot()?

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Is there a way to extract the parameters of the regression line(s) that seaborn.lmplot() fits for a given set of data? I have looked up the documentation and haven't been able to spot anything that would help me in this regard.

Just to be clear, I don't mean the lmplot()'s function parameters, but the m,
and b of y = mx + b.

seaborn linear-regression python
1 Answers

seaborn uses scipy stats linregress, so you could get it directly from there.

from scipy import stats
slope, intercept, r_value, p_value, std_err = stats.linregress(df.x,df.y)
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