Update data_processor.py

data_processor.py

@@ -184,14 +184,16 @@
 
 
 
-
 import re
 import pandas as pd
 import os
 from huggingface_hub import InferenceClient
 
 class DataProcessor:
-    INTERVENTION_COLUMN = 'Did the intervention happen today?'
+    INTERVENTION_COLUMN_OPTIONS = [
+        'Did the intervention happen today?',
+        'Did the Intervention Take Place Today?'
+    ]
     ENGAGED_STR = 'Engaged'
     PARTIALLY_ENGAGED_STR = 'Partially Engaged'
     NOT_ENGAGED_STR = 'Not Engaged'
@@ -202,7 +204,7 @@ class DataProcessor:
             raise ValueError("HF_API_KEY not set in environment variables")
         self.client = InferenceClient(api_key=self.hf_api_key)
         self.student_metrics_df = student_metrics_df
-
+        self.intervention_column = None  # Will be set when processing data
 
     def read_excel(self, uploaded_file):
         return pd.read_excel(uploaded_file)
@@ -256,9 +258,17 @@ class DataProcessor:
         df.columns = updated_columns
         return df
 
+    def find_intervention_column(self, df):
+        for column in self.INTERVENTION_COLUMN_OPTIONS:
+            if column in df.columns:
+                self.intervention_column = column
+                return column
+        raise ValueError("No intervention column found in the dataframe.")
+
     def compute_intervention_statistics(self, df):
+        intervention_column = self.find_intervention_column(df)
         total_days = len(df)
-        sessions_held = df[self.INTERVENTION_COLUMN].str.strip().str.lower().eq('yes').sum()
+        sessions_held = df[intervention_column].str.strip().str.lower().eq('yes').sum()
         intervention_frequency = (sessions_held / total_days) * 100 if total_days > 0 else 0
         return pd.DataFrame({
             'Intervention Dosage (%)': [round(intervention_frequency, 0)],
@@ -266,6 +276,7 @@ class DataProcessor:
             'Intervention Sessions Not Held': [total_days - sessions_held],
             'Total Number of Days Available': [total_days]
         })
+    
 
     def classify_engagement(self, engagement_str):
         engagement_str = engagement_str.lower()