Scatterplot with regression lines

scatterplot_reg.py

palette = iter(sns.color_palette("tab10"))

# Plot points
g = sns.scatterplot(x=x, y=y, color=next(palette))
g.grid(False)

# Plot regression line
m, b = np.polyfit(x, y, 1)
linecolor = next(palette)
xr = range(x.min(), x.max(), 1)
line1 = plt.plot(xr, m*xr+b, color=linecolor, linestyle="solid")

outliers = ["sample10", "sample27"]

# Label outliers on plot
for o in outliers: 
    plt.annotate(
        o, 
        (
            x[o] + 2,
            y[o],
        ),
        color="gray"
    )

# Drop outliers
x = x.drop(index=outliers)
y = y.drop(index=outliers)

# Refit without outliers
m, b = np.polyfit(x, y, 1)
x = range(x.min(), x.max(), 1)
line2 = plt.plot(x, m*x+b, color=linecolor, linestyle="dotted")

# Add legend
g.legend(
    [line1[0], line2[0]], 
    ["all data", "outliers removed"], 
    loc="lower right"
)