Joint plot with regression line and classes by hue - seaborn

Question

I have the following dataframe
df = pd.DataFrame({
'Product': ['AA', 'AA', 'BB', 'BB', 'AA', 'AA', 'BB', 'BB'],
'Sales': [ 200, 100, 400, 100, 300, 100, 200, 500],
'Price': [ 5, 3, 3, 6, 4, 7, 4, 1]})
I would like to plot the regression line of the overall data, but also the scatter points by hue (in this case by Product) in the same chart.
I can get the regression line by:
g = sns.jointplot(y='Sales', x='Price', data=df, kind='reg', scatter = False)
And I can get the scatter by:
g = sns.scatterplot(y='Sales', x='Price', data=df, hue='Product')
But there are two different charts. Anyway that I can combine the two commands?

Answer 1

You have to tell the scatterplot in which axis object you want to plot. Options for a seaborn jointplot are the main plot area ax_joint or the two minor plot areas ax_marg_x and ax_marg_y.
from matplotlib import pyplot as plt
import seaborn as sns
import pandas as pd
df = pd.DataFrame({
'Product': ['AA', 'AA', 'BB', 'BB', 'AA', 'AA', 'BB', 'BB'],
'Sales': [ 200, 100, 400, 100, 300, 100, 200, 500],
'Price': [ 5, 3, 3, 6, 4, 7, 4, 1]})
g = sns.jointplot(y='Sales', x='Price', data=df, kind='reg', scatter = False)
sns.scatterplot(y='Sales', x='Price', data=df, hue="Product", ax=g.ax_joint)
plt.show()
Sample output:

Answer 2

To extend on Mr. T's answer, you could also do something like this to keep the kde marginal plots of the jointplot:
from matplotlib import pyplot as plt
import seaborn as sns
import pandas as pd
df = pd.DataFrame({
'Product': ['AA', 'AA', 'BB', 'BB', 'AA', 'AA', 'BB', 'BB'],
'Sales': [ 200, 100, 400, 100, 300, 100, 200, 500],
'Price': [ 5, 3, 3, 6, 4, 7, 4, 1]})
g = sns.jointplot(y='Sales', x='Price', data=df, hue="Product", alpha=0.5, xlim=(0.5,7.5), ylim=(-50, 550))
g1 = sns.regplot(y='Sales', x='Price', data=df, scatter=False, ax=g.ax_joint)
regline = g1.get_lines()[0]
regline.set_color('red')
regline.set_zorder(5)
plt.show()