改为保存xx天xx小时xx分钟

predict_with_excel.py

@@ -316,6 +316,37 @@ def get_welding_time(row):
     return welding_time
 
 
+def minutes_to_dhm_format(minutes):
+    """
+    将分钟数转换为 "xx天xx小时xx分钟" 的字符串格式
+    
+    Args:
+        minutes: 分钟数（浮点数）
+    
+    Returns:
+        格式化的字符串，例如："2天5小时30分钟"
+    """
+    if pd.isna(minutes) or not isinstance(minutes, (int, float)):
+        return "0分钟"
+    
+    total_minutes = int(round(minutes))
+    
+    days = total_minutes // (24 * 60)
+    remaining = total_minutes % (24 * 60)
+    hours = remaining // 60
+    mins = remaining % 60
+    
+    parts = []
+    if days > 0:
+        parts.append(f"{days}天")
+    if hours > 0:
+        parts.append(f"{hours}小时")
+    if mins > 0 or len(parts) == 0:  # 如果没有天和小时，至少显示分钟
+        parts.append(f"{mins}分钟")
+    
+    return "".join(parts)
+
+
 def save_df_to_excel(df, output_file_path):
     df.to_excel(output_file_path, index=False)
 
@@ -345,7 +376,8 @@ def build_prediction_dataframe(df: pd.DataFrame) -> pd.DataFrame:
 
     total_row = {col: np.nan for col in df_without_last.columns}
     total_row["序号"] = "总计"
-    total_row["焊接工时"] = df_without_last["焊接工时"].sum()
+    total_minutes = df_without_last["焊接工时"].sum()
+    total_row["焊接工时"] = minutes_to_dhm_format(total_minutes)
 
     result_df = pd.concat([df_without_last, pd.DataFrame([total_row])], ignore_index=True)
     return result_df