diff --git a/random_pick_crm_mandatory.py b/random_pick_crm_mandatory.py
index 880d158..21f061b 100644
--- a/random_pick_crm_mandatory.py
+++ b/random_pick_crm_mandatory.py
@@ -9,16 +9,46 @@ checker = LinguisticChecker(api_key, api_secret, assistant_id)
 
 df = pd.read_excel('./data_src/pingcap_pipeline.xlsx')
 
+report = []
+
+
+crm_fields = ['客户业务场景','友商信息']
+
+for crm_field in crm_fields:
+    # Randomly select 20 items from the DataFrame
+    random_pick_20 = df.sample(n=20, random_state=42)
+
+    # Reset the index of the randomly selected items
+    random_pick_20 = random_pick_20.reset_index(drop=True)
+
+    print(f"Randomly selected {len(random_pick_20)} items from the DataFrame.")
 # Iterate over the DataFrame
-for index, row in df.iterrows():
-    try:
-        # Assuming 'CRM Field' and 'User Input' are column names in the Excel file
-        # Adjust these names if they're different in your actual file
-        crm_field = row['CRM Field']
-        user_input = row['User Input']
-        
-        # Check the input using the LinguisticChecker
-        result = checker.check_input(crm_field, user_input)
-    except Exception as e:
-        print(f"Error processing row {index}: {str(e)}")
-        result = None
+    for index, row in random_pick_20.iterrows():
+        try:
+            # Adjust these names if they're different in your actual file
+            user_input = row[crm_field]
+            
+            # Check the input using the LinguisticChecker
+            result = checker.check_input(crm_field, user_input)
+            # result = 'ssss'
+            # Append the results to the report list
+            report.append({
+                '商机ID':row['唯一性ID（必填）'],
+                'CRM必填项': crm_field,
+                '用户输入': user_input,
+                '分析诊断': result
+            })
+        except Exception as e:
+            print(f"Error processing row {index}: {str(e)}")
+            result = f"Error processing row {index}: {str(e)}"
+
+        # Convert the report list to a DataFrame
+report_df = pd.DataFrame(report)
+
+# Write the DataFrame to an Excel file
+output_file = 'crm_mandatory_fields_analysis.xlsx'
+report_df.to_excel(output_file, index=False)
+
+print(f"Analysis report has been saved to {output_file}")
+
+