round off

utils/ghg_classifier.py

@@ -71,7 +71,7 @@ def ghg_classification(haystack_doc:pd.DataFrame,
     """
     logging.info("Working on GHG Extraction")
     haystack_doc['GHG Label'] = 'NA'
-    haystack_doc['GHG Score'] = 'NA'
+    haystack_doc['GHG Score'] = 0.0
     # applying GHG Identifier to only 'Target' paragraphs.
     temp = haystack_doc[haystack_doc['Target Label'] == 'TARGET']
     temp = temp.reset_index(drop=True)
@@ -88,6 +88,7 @@ def ghg_classification(haystack_doc:pd.DataFrame,
     # merge back Target and non-Target dataframe
     df = pd.concat([df,temp])
     df = df.reset_index(drop =True)
+    df['GH Score'] = df['GH Score'].round(2)
     df.index += 1
 
     return df

utils/netzero_classifier.py

@@ -70,7 +70,7 @@ def netzero_classification(haystack_doc:pd.DataFrame,
     """
     logging.info("Working on Netzero Extraction")
     haystack_doc['Netzero Label'] = 'NA'
-    haystack_doc['Netzero Score'] = 'NA'
+    haystack_doc['Netzero Score'] = 0.0
     # we apply Netzero to only paragraphs which are classified as 'Target' related
     temp = haystack_doc[haystack_doc['Target Label'] == 'TARGET']
     temp = temp.reset_index(drop=True)
@@ -87,6 +87,7 @@ def netzero_classification(haystack_doc:pd.DataFrame,
     # merging Target with Non Target dataframe
     df = pd.concat([df,temp])
     df = df.reset_index(drop =True)
+    df['Netzero Score'] = df['Netzero Score'].round(2)
     df.index += 1
 
     return df