Update app.py

app.py

@@ -16,7 +16,6 @@ data_filename = hf_hub_download(repo_id="poudel/Job_Predictor", filename="cleane
 # Load the CSV dataset
 data = pd.read_csv(data_filename)
 
-
 # Get unique values for dropdowns
 position_titles = data['PositionTitle'].unique().tolist()
 designations = data['Designation'].unique().tolist()
@@ -44,8 +43,10 @@ def predict_applicants(position_title, designation, agency, vacancy_type, employ
     # Calculate additional features
     input_data['Success_Ratio'] = input_data['NumberOfSuccessfulApplicants'] / input_data['NumberOfVacancies'].replace(0, np.nan)
     input_data['Applicants_per_Vacancy'] = input_data['NumberOfVacancies'] / np.where(input_data['NumberOfSuccessfulApplicants'] == 0, np.nan, input_data['NumberOfSuccessfulApplicants'])
-    input_data['Success_Ratio'].fillna(0, inplace=True)
-    input_data['Applicants_per_Vacancy'].fillna(0, inplace=True)
+    
+    # Avoid inplace modification, return to the column
+    input_data['Success_Ratio'] = input_data['Success_Ratio'].fillna(0)
+    input_data['Applicants_per_Vacancy'] = input_data['Applicants_per_Vacancy'].fillna(0)
 
     # Make predictions using the loaded model pipeline
     try: