fix: 특정 직무/레벨 결측 데이터 및 에러 방어 로직 추가

core/core.py

@@ -121,6 +121,9 @@ def get_final_level(user_score, level_range, factors):
             final_level = level
             break
 
+    # 최종 판정 레벨이 직무의 지원 레벨 범위를 벗어나지 않도록 클리핑 방어
+    final_level = max(min_level, min(max_level, final_level))
+
     low_set = s[s < final_level].sort_values().index.tolist()
     middle_set = s[(s >= final_level) & (s < final_level+1)].sort_values().index.tolist()
     high_set = s[s >= final_level].sort_values(ascending=False).index.tolist()
@@ -161,26 +164,32 @@ def judge_level(user_score, level_range, job):
     final_level, max_level, guides = get_final_level(user_score, level_range, factors)
 
     level_dict = level_def[level_def['직무'] == job].set_index('수준')['수준 정의']
+    
+    def get_level_definition(level_str):
+        if level_str in level_dict.index:
+            return level_dict[level_str]
+        return f"{job} {level_str} 수준에 대한 상세 정의가 데이터베이스에 존재하지 않습니다."
+
     if final_level == max_level:
         output = {
             'left' : {
-                'title' : "하위 레벨:" + f'L{final_level-1}',
-                'definition' : level_dict[f'L{final_level-1}']
+                'title' : "하위 레벨: " + f'L{final_level-1}',
+                'definition' : get_level_definition(f'L{final_level-1}')
                 },
             'right' : {
-                'title' : "현재 레벨:" + f'L{final_level}',
-                'definition' : level_dict[f'L{final_level}']
+                'title' : "현재 레벨: " + f'L{final_level}',
+                'definition' : get_level_definition(f'L{final_level}')
                 },
             }
     else:
         output = {
             'left' : {
                 'title' : "현재 레벨: " + f'L{final_level}',
-                'definition' : level_dict[f'L{final_level}']
+                'definition' : get_level_definition(f'L{final_level}')
                 },
             'right' : {
                 'title' : "상위 레벨: " + f'L{final_level+1}',
-                'definition' : level_dict[f'L{final_level+1}']
+                'definition' : get_level_definition(f'L{final_level+1}')
                 },
             }
 
@@ -231,8 +240,17 @@ def judge_wage(
     job_pool_df = raw_df[(raw_df['ITSQF 직무(변환)'] == job)&(raw_df['ITSQF 수준'] == final_level)]
     job_pool_vals = pd.to_numeric(job_pool_df[base_type], errors="coerce").dropna().to_numpy(dtype=float)
 
-    std_pool = float(np.std(job_pool_vals, ddof=1))
-    mean_job = float(np.mean(job_pool_vals))
+    # 데이터가 비어있는 경우(Empty data pool)에 대한 Fallback 방어 코드
+    if job_pool_vals.size == 0:
+        print(f"[WARN] Empty data pool for Job={job}, Level={final_level}. Falling back to Level={final_level} all jobs.")
+        job_pool_df = raw_df[raw_df['ITSQF 수준'] == final_level]
+        job_pool_vals = pd.to_numeric(job_pool_df[base_type], errors="coerce").dropna().to_numpy(dtype=float)
+        if job_pool_vals.size == 0:
+            print(f"[WARN] No data at all for Level={final_level}. Falling back to all raw data.")
+            job_pool_vals = pd.to_numeric(raw_df[base_type], errors="coerce").dropna().to_numpy(dtype=float)
+
+    std_pool = float(np.std(job_pool_vals, ddof=1)) if job_pool_vals.size >= 2 else 0.0
+    mean_job = float(np.mean(job_pool_vals)) if job_pool_vals.size >= 1 else 0.0
 
     # 2) cohort (직무 + 레벨 + 옵션 필터)
     def get_cohort_df(df, bm, sales, emp):
@@ -374,11 +392,13 @@ def generate_dataset(request_options, user_choice):
     pages = []
     charts = []
     for label in definitions.loc['title'].tolist():
-        level = label.split(': ')[1]
+        parts = [p.strip() for p in label.split(':')]
+        title_prefix = parts[0]
+        level = parts[1]
         table = target_table[['평가요소', level]].copy()
         table, chart = format_table(table, user_score, level)
         pages.append({
-            "title": label.split(': ')[0],
+            "title": title_prefix,
             "table": [table]
         })
         charts.append(chart)