Sklearn logistic regression, plotting probability curve graph

python pandas scikit-learn scatter-plot
Tony picture Tony · Sep 7, 2017 · Viewed 23.5k times · Source

I'm trying to create a logistic regression similar to the ISLR's example, but using python instead

data=pd.read_csv("data/Default.csv")

#first we'll have to convert the strings "No" and "Yes" to numeric values
data.loc[data["default"]=="No", "default"]=0
data.loc[data["default"]=="Yes", "default"]=1
X = data["balance"].values.reshape(-1,1)
Y = data["default"].values.reshape(-1,1)

LogR = LogisticRegression()
LogR.fit(X,np.ravel(Y.astype(int)))

#matplotlib scatter funcion w/ logistic regression
plt.scatter(X,Y)
plt.xlabel("Credit Balance")
plt.ylabel("Probability of Default")

But I keep getting the graph on the left, when I want the one on the right:

enter image description here

Edit: plt.scatter(x,LogR.predict(x)) was my second, and also wrong guess.

Answer

Woody Pride picture Woody Pride · Sep 7, 2017

You can use seaborn regplot with the following syntax

import seaborn as sns
sns.regplot(x='balance', y='default', data=data, logistic=True)

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