Update app.py

app.py

@@ -1,7 +1,13 @@
+import pandas as pd
+from sklearn.model_selection import train_test_split
+from sklearn.linear_model import LogisticRegression
 import pickle
 import gradio as gr
 import numpy as np
 
+# Load the CSV data
+data = pd.read_csv('/content/Untitled spreadsheet - Heart desiese data.csv')  # Ensure the correct file path
+
 # Load the trained model
 model = pickle.load(open('/content/heart_disease_model.sav', 'rb'))
 
@@ -9,7 +15,7 @@ model = pickle.load(open('/content/heart_disease_model.sav', 'rb'))
 def predict_heart_disease(age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal):
     input_data = np.array([[age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal]])
     prediction = model.predict(input_data)
-    
+
     if prediction[0] == 1:
         return "The person has heart disease."
     else:
@@ -43,3 +49,6 @@ def heart_disease_interface():
 
 # Launch the Gradio Interface
 heart_disease_interface().launch()
+
+# Check the first few rows of the data (optional)
+print(data.head())