Upload 2 files

app.py

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+import pandas as pd
+
+# new_data = pd.DataFrame({
+#     'gender':0,
+#     'ssc_p':55.0,
+#     'ssc_b':0,
+#     'hsc_p':75.0,
+#     'hsc_b':0,
+#     'hsc_s':1,
+#     'degree_p':65.0,
+#     'degree_t':2,
+#     'workex':0,
+#     'etest_p':55.0,
+#      'specialisation':1,
+#     'mba_p':58.8,
+# },index=[0])
+
+import joblib
+
+model = joblib.load('model_campus_placement')
+
+# p=model.predict(new_data)
+# prob=model.predict_proba(new_data)
+
+# if p[0]==1:
+#     print('Placed')
+#     print(f"You will be placed with probability of {prob[0][1]:.2f}")
+# else:
+#     print("Not-placed")
+
+import streamlit as st
+
+st.title('Campus-Placement-Prediction-Using-Machine-Learning')
+
+gender=st.number_input('gender',value=0)
+ssc_p=st.number_input('ssc_p',value=0)
+ssc_b=st.number_input('ssc_b',value=0)
+hsc_p=st.number_input('hsc_p',value=0)
+hsc_b=st.number_input('hsc_b',value=0)
+hsc_s=st.number_input('hsc_s',value=0)
+degree_p=st.number_input('degree_p',value=0)
+degree_t=st.number_input('degree_t',value=0)
+workex=st.number_input('workex',value=0)
+etest_p=st.number_input('etest_p',value=0)
+specialisation=st.number_input('specialisation',value=0)
+mba_p=st.number_input('mba_p',value=0)
+
+if st.button('submit'):
+
+    new_data = pd.DataFrame({
+        'gender':gender,
+        'ssc_p':ssc_p,
+        'ssc_b':ssc_b,
+        'hsc_p':hsc_p,
+        'hsc_b':hsc_b,
+        'hsc_s':hsc_s,
+        'degree_p':degree_p,
+        'degree_t':degree_t,
+        'workex':workex,
+        'etest_p':etest_p,
+        'specialisation':specialisation,
+        'mba_p':mba_p,
+    },index=[0])
+
+    p=model.predict(new_data)
+    prob=model.predict_proba(new_data)
+
+    
+    if p[0]==1:
+        # print('Placed')
+        st.write('Placed')
+        # print(f"You will be placed with probability of {prob[0][1]:.2f}")
+        st.write(f"You will be placed with probability of {prob[0][1]:.2f}")
+
+    else:
+        # print("Not-placed")
+        st.write('Not-placed')
+
+
+
+
+
+
+
+
+
+
+

model.py

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+import pandas as pd
+data = pd.read_csv('D:\Downloads\Campus-Placement-Prediction-Using-Machine-Learning-main\Campus-Placement-Prediction-Using-Machine-Learning-main\Placement_Data_Full_Class (1).csv')
+import warnings
+warnings.filterwarnings('ignore')