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!!

Logistic Regression on purchase incidence vs average candy price

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