# Logistic Regression on purchase incidence vs average candy price

I am going through the Customer Analystic section. In this section, logistic regression is conduted to fit the model with our X or price and our Y or incidence.

The codes provided by the course are as follow:

""

# We create a Logistic Regression model using sk learn. Then we fit the model with our X or price and our Y or incidence.

model_purchase = LogisticRegression(solver = 'sag')

model_purchase.fit(X, Y)

""

I try to do scatter plot on X,Y to see what happen. My codes following the above codes are

""

f=plt.figure(figsize=(16,8))

ax=f.add_subplot(111)

ax.scatter(X,Y)

**

However, I found that plot is not like a sigmoid function as we commonly have in Logistic Regression. ( it looks like a pair of parrell lines)

Confused.. is my scatter plot making sense here? do we expect to see a sigmoid-like scatter plot?

Many thanks!!