action policy split

utils/policyaction_classifier.py

@@ -82,20 +82,25 @@ def policyaction_classification(haystack_doc:pd.DataFrame,
       list_.append(placeholder)
     labels_ = [{**list_[l]} for l in range(len(predictions))]
     truth_df = DataFrame.from_dict(labels_)
-    st.write(truth_df)
     truth_df = truth_df.round(2)
+    temp = truth_df.copy()
     truth_df = truth_df.astype(float) >= threshold
     truth_df = truth_df.astype(str)
-    categories = list(truth_df.columns)
-    truth_df['Policy-Action Label'] = truth_df.apply(lambda x: {i if x[i]=='True' 
-                                        else None for i in categories}, axis=1)
-    # st.dataframe(truth_df)                                    
-    truth_df['Policy-Action Label'] = truth_df.apply(lambda x: 
-                                  list(x['Policy-Action Label'] -{None}),axis=1)
+    truth_df.rename(columns = {'Action':'Action Label','Policies_Plans':'Policies_Plans Label'},
+                                 inplace =True)
+    temp.rename(columns  = {'Action':'Action Score','Policies_Plans':'Policies_Plans Score'},
+                          inplace=True)
+    # categories = list(truth_df.columns)
+    # truth_df['Policy-Action Label'] = truth_df.apply(lambda x: {i if x[i]=='True' 
+    #                                     else None for i in categories}, axis=1)
+    st.dataframe(truth_df) 
+    st.dataframe(temp)                                   
+    # truth_df['Policy-Action Label'] = truth_df.apply(lambda x: 
+    #                               list(x['Policy-Action Label'] -{None}),axis=1)
 
-    haystack_doc['Policy-Action Label'] =  list(truth_df['Policy-Action Label'])
-    haystack_doc['Policy-Action Label'] = haystack_doc['Policy-Action Label'].apply(
-                                            lambda x:x if x else ['NA'])
+    # haystack_doc['Policy-Action Label'] =  list(truth_df['Policy-Action Label'])
+    # haystack_doc['Policy-Action Label'] = haystack_doc['Policy-Action Label'].apply(
+    #                                         lambda x:x if x else ['NA'])
     # st.dataframe(haystack_doc)  
 
     return haystack_doc