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     "end_time": "2026-01-30T09:27:59.557746200Z",
     "start_time": "2026-01-30T09:27:59.437881100Z"
    }
   },
   "source": [
    "import pandas as pd\n",
    "\n",
    "# 假设你的 DataFrame 名为 df，包含以下列：\n",
    "# 'material_code': 材料编码\n",
    "# 'in_qty': 入库数量\n",
    "# 'in_cost': 入库成本（总金额，不是单价）\n",
    "df = pd.read_excel(fr\"C:\\Users\\hp_z66\\OneDrive\\Desktop\\材料成本明细表核对.xlsx\",sheet_name='Sheet1')\n",
    "# 1. 按材料编码分组，计算总入库数量和总入库成本\n",
    "summary = df.groupby('材料编码').agg(\n",
    "    total_in_qty=('数量', 'sum'),\n",
    "    total_in_cost=(' 除税成本', 'sum')\n",
    ").reset_index()\n",
    "\n",
    "print(summary)\n",
    "summary.to_csv(fr\"C:\\Users\\hp_z66\\OneDrive\\Desktop\\材料成本明细表核对sheet1.csv\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          材料编码  total_in_qty  total_in_cost\n",
      "0    CL0003899             8         184.07\n",
      "1    CL0004029           300          92.92\n",
      "2    CL0004193           100         176.99\n",
      "3    CL0005552            -1       -4250.04\n",
      "4    CL0005554             2        2268.78\n",
      "..         ...           ...            ...\n",
      "461  CL0007466             1         800.00\n",
      "462  CL0007467             1         800.00\n",
      "463  CL0007468             1         500.00\n",
      "464  CL0007469             1         500.00\n",
      "465  CL0007470             1         500.00\n",
      "\n",
      "[466 rows x 3 columns]\n"
     ]
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-01-30T09:28:27.291489100Z",
     "start_time": "2026-01-30T09:28:27.188359600Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pandas as pd\n",
    "\n",
    "# 假设你的 DataFrame 名为 df，包含以下列：\n",
    "# 'material_code': 材料编码\n",
    "# 'in_qty': 入库数量\n",
    "# 'in_cost': 入库成本（总金额，不是单价）\n",
    "df = pd.read_excel(fr\"C:\\Users\\hp_z66\\OneDrive\\Desktop\\材料成本明细表核对.xlsx\",sheet_name='Sheet2')\n",
    "# 1. 按材料编码分组，计算总入库数量和总入库成本\n",
    "summary = df.groupby('材料编码').agg(\n",
    "    total_in_qty=('采购入库数量', 'sum'),\n",
    "    total_in_cost=('采购入库成本（除税）', 'sum')\n",
    ").reset_index()\n",
    "\n",
    "print(summary)\n",
    "summary.to_csv(fr\"C:\\Users\\hp_z66\\OneDrive\\Desktop\\材料成本明细表核对sheet2.csv\")"
   ],
   "id": "fcb775d7ed25bd85",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          材料编码  total_in_qty  total_in_cost\n",
      "0    CL0003899             8     184.070800\n",
      "1    CL0004029           300      92.920500\n",
      "2    CL0004193           100     176.991200\n",
      "3    CL0005552            -1   -4250.044248\n",
      "4    CL0005554             2    2268.778762\n",
      "..         ...           ...            ...\n",
      "459  CL0007466             1     800.000000\n",
      "460  CL0007467             1     800.000000\n",
      "461  CL0007468             1     500.000000\n",
      "462  CL0007469             1     500.000000\n",
      "463  CL0007470             1     500.000000\n",
      "\n",
      "[464 rows x 3 columns]\n"
     ]
    }
   ],
   "execution_count": 5
  }
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