Update app.py

app.py

@@ -13,10 +13,10 @@ loaded_model = pickle.load(open("classroom_xgb.pkl", 'rb'))
 explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS.
 
 # Create the main function for server
-def main_func(Target, Admission grade, Curricular units 2nd sem (grade), Previous qualification (grade), Curricular units 1st sem (grade), Course, Curricular units 2nd sem (approved), Age at enrollment):
-    new_row = pd.DataFrame.from_dict({'Target':Target,'Admission grade':AdmissionGrade,
-              'Curricular units 2nd sem (grade)':CurricularUnits2ndSemGrade,'Previous qualification (grade)':PreviousQualificationGrade,'Curricular units 1st sem (grade)':CurricularUnits1stSemGrade,
-              'Course':Course,'Curricular units 2nd sem (approved)':CurricularUnits2ndSemApproved,'Age at enrollment':AgeAtEnrollment,
+def main_func(Target, Admission_Grade, 2nd_Sem_Grades, Previous_Qualification_Grade, 1st_Sem_Grades, Course, 2nd_Sem_Units_Approved, Age_at_Enrollment):
+    new_row = pd.DataFrame.from_dict({'Target':Target,'Admission_Grade':Admission_Grade,
+              '2nd_Sem_Grades':2nd_Sem_Grades,'Previous_Qualification_Grade':Previous_Qualification_Grade,'1st_Sem_Grades':1st_Sem_Grades,
+              'Course':Course,'2nd_Sem_Units_Approved':2nd_Sem_Units_Approved,'Age_at_Enrollment':Age_at_Enrollment},
                                       orient = 'index').transpose() 
     
     prob = loaded_model.predict_proba(new_row)
@@ -49,12 +49,13 @@ with gr.Blocks(title=title) as demo:
     with gr.Row():
         with gr.Column():
         Target = gr.Number(label="Target Score", value=40)
-        AdmissionGrade = gr.Slider(label="AdmissionGrade Score", minimum=0, maximum=1, value=1, step=1)
-        PreviousQualificationGrade = gr.Slider(label="PreviousQualificationGrade Score", minimum=1, maximum=5, value=4, step=1)
-        CurricularUnits1stSemGrade = gr.Slider(label="CurricularUnits1stSemGrade Score", minimum=1, maximum=5, value=4, step=1) 
-        Course = gr.Slider(label="Course Score", minimum=1, maximum=5, value=4, step=1)
-        CurricularUnits2ndSemApproved = gr.Slider(label="CurricularUnits2ndSemApproved Score", minimum=1, maximum=5, value=4, step=1)
-        AgeAtEnrollment = gr.Slider(label="AgeAtEnrollment Score", minimum=1, maximum=5, value=4, step=1)
+        Admission_Grade = gr.Slider(label="AdmissionGrade Score", minimum=0, maximum=1, value=1, step=1)
+        2nd_Sem_Grades = gr.Slider(label="PreviousQualificationGrade Score", minimum=1, maximum=5, value=4, step=1)
+        Previous_Qualification_Grade = gr.Slider(label="CurricularUnits1stSemGrade Score", minimum=1, maximum=5, value=4, step=1) 
+        1st_Sem_Grades = gr.Slider(label="Course Score", minimum=1, maximum=5, value=4, step=1)
+        Course = gr.Slider(label="Course", minimum=1, maximum=5, value=4, step=1)
+        2nd_Sem_Units_Approved = gr.Slider(label="2nd_Sem_Units_Approved", minimum=1, maximum=5, value=4, step=1)
+        Age_at_Enrollment = gr.Slider(label="AgeAtEnrollment Score", minimum=1, maximum=5, value=4, step=1)
         submit_btn = gr.Button("Analyze")
 
         with gr.Column(visible=True) as output_col:
@@ -63,11 +64,12 @@ with gr.Blocks(title=title) as demo:
 
     submit_btn.click(
         main_func,
-        [Target, AdmissionGrade, CurricularUnits2ndSemGrade, PreviousQualificationGrade, CurricularUnits1stSemGrade, Course, CurricularUnits2ndSemApproved, AgeAtEnrollment],
+        [Target, Admission_Grade, 2nd_Sem_Grades, Previous_Qualification_Grade, 1st_Sem_Grades, Course, 2nd_Sem_Units_Approved, Age_at_Enrollment],
         [label,local_plot], api_name="Graduation_Predictor"
     )
     
     gr.Markdown("### Click on any of the examples below to see how it works:")
-    gr.Examples([['Graduate',119.6,13.000000,122.0,9773,5,18], [Target, AdmissionGrade, CurricularUnits2ndSemGrade, PreviousQualificationGrade, CurricularUnits1stSemGrade, Course, CurricularUnits2ndSemApproved, AgeAtEnrollment], [label,local_plot], main_func, cache_examples=True)
+    gr.Examples([['Graduate',119.6,13.000000,122.0,9773,5,18], [Target, Admission_Grade, 2nd_Sem_Grades, Previous_Qualification_Grade, 1st_Sem_Grades, Course, 2nd_Sem_Units_Approved, Age_at_Enrollment]
+                 , [label,local_plot], main_func, cache_examples=True)
 
 demo.launch()