Update app.py

app.py

@@ -30,36 +30,50 @@ st.image("https://study.com/academy/lesson/star-formation-main-sequence-dwarf-gi
 def main():
     st.text('For comparing all models of ML It can be used for prediction')
     with st.form("questionaire"):
-         Temperature = st.slider('Temperature',min_value=1900,max_value=40000)
+         K = st.slider('Temperature',min_value=1900,max_value=40000)
          L = st.slider('Relative Luminosity',min_value=0,max_value=1000000)
          R = st.slider('Relative Radius',min_value=0,max_value=2000)
          A_M = st.slider('Absolute Magnitude',min_value=0,max_value=25)
          Color = st.selectbox("General Color of Spectrum",options=unique_CL)
          Spectral_Class = st.selectbox("Spectral_Class",options=unique_SC)
          clicked = st.form_submit_button("Predict type")
-         if clicked:
-            result=model.predict(pd.DataFrame({"Temperature": [Temperature],
-                                               "Relative Luminosity": [L],
-                                               "Relative Radiusducation": [R],
-                                               "Absolute Magnitude": [A_M],
-                                               "General Color of Spectrum": [CL_DICT[Color]],
-                                               "Spectral_Class": [SC_DICT[Spectral_Class]]
-                                               }))
-            # Show prediction
-            if result[0] == 0:
-               result = "Red Dwarf" 
-            elif result[0] == 1:
-               result = "Brown Dwarf"
-            elif result[0] == 2:
-               result = "White Dwarf"
-            elif result[0] == 3:
-               result = "Main Sequence"
-            elif result[0] == 4:
-               result = "Super Giants"
-            elif result[0] == 5:
-               result = "Hyper Giants"
-               
-            st.success("Your star type is "+result)
+        if clicked:
+            result = model.predict(pd.DataFrame({"Temperature(K)": [K],
+                                                 "Relative Luminosity(Watts)": [L],
+                                                 "Relative Radius(m)": [R],
+                                                 "Absolute Magnitude": [A_M],
+                                                 "Color": [Color],
+                                                 "Spectral_Class": [Spectral_Class]})
+            )
+
+            prob = model.predict_prob(pd.DataFrame({"Temperature(K)": [K],
+                                                 "Relative Luminosity(Watts)": [L],
+                                                 "Relative Radius(m)": [R],
+                                                 "Absolute Magnitude": [A_M],
+                                                 "Color": [Color],
+                                                 "Spectral_Class": [Spectral_Class]})
+            )
+            
+            prob = pd.DataFrame(prob, columns = ["Red Dwarf",'Brown Dwarf','White Dwarf','Main Sequence','Super Giants','Hyper Giants']).reset_index(drop=True)
+            prob['Type'] = 'Probability'
+            prob = prob.set_index('Type')
+                           
+            st.write(prob)           
+            
+            if result[0] == '0':
+                st.text('Red Dwarf')
+            elif result[0] == '1':
+                st.text('Brown Dwarf')
+            elif result[0] == '2':
+                st.text('White Dwarf')
+            elif result[0] == '3':
+                st.text('Main Sequence')
+            elif result[0] == '4':
+                st.text('Super Giants')
+            else:
+                st.text('Hyper Giants')
+                
+            st.write("My star type is...", result[0])
         
 if __name__=="__main__":
     main()