diff --git a/aisenzhecode/液化石油气/日度价格预测_液化气最佳模型.pkl b/aisenzhecode/液化石油气/日度价格预测_液化气最佳模型.pkl
index 27f0f01..0699717 100644
Binary files a/aisenzhecode/液化石油气/日度价格预测_液化气最佳模型.pkl and b/aisenzhecode/液化石油气/日度价格预测_液化气最佳模型.pkl differ
diff --git a/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb b/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb
index aa07da2..02a48b9 100644
--- a/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb
+++ b/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb
@@ -6,12 +6,10 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\Administrator\\Anaconda3\\lib\\site-packages\\statsmodels\\compat\\pandas.py:49: FutureWarning:\n",
-      "\n",
-      "The Panel class is removed from pandas. Accessing it from the top-level namespace will also be removed in the next version\n",
+      "WARNING:tensorflow:From C:\\Users\\EDY\\AppData\\Roaming\\Python\\Python311\\site-packages\\keras\\src\\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.\n",
       "\n"
      ]
     },
@@ -20,12 +18,12 @@
       "text/html": [
        "        <script type=\"text/javascript\">\n",
        "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
-       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
        "        if (typeof require !== 'undefined') {\n",
        "        require.undef(\"plotly\");\n",
        "        requirejs.config({\n",
        "            paths: {\n",
-       "                'plotly': ['https://cdn.plot.ly/plotly-2.2.0.min']\n",
+       "                'plotly': ['https://cdn.plot.ly/plotly-2.12.1.min']\n",
        "            }\n",
        "        });\n",
        "        require(['plotly'], function(Plotly) {\n",
@@ -566,15 +564,17 @@
     "    # write_xls(data_list)\n",
     "\n",
     "def getNow(date='',offset=0):\n",
+    "    from datetime import datetime\n",
     "    if date == '':\n",
-    "        from datetime import datetime\n",
     "        now = datetime.now() - timedelta(days=offset)\n",
     "    else:\n",
     "        try:\n",
     "            date = datetime.strptime(date, \"%Y-%m-%d\")\n",
     "        except:\n",
     "            date = datetime.strptime(date, \"%Y%m%d\")\n",
+    "        pass\n",
     "        now = date\n",
+    "        print(now,type(now))\n",
     "\n",
     "    year = now.year\n",
     "    month = now.month\n",
@@ -724,84 +724,87 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {
     "scrolled": true
    },
+   "outputs": [],
+   "source": [
+    "\n",
+    "# if __name__ == \"__main__\":\n",
+    "#     print('运行中')\n",
+    "#     # 需要单独运行放开\n",
+    "# #     start()\n",
+    "# #     start_1(date='2025-01-22')\n",
+    "# #     start_1()\n",
+    "\n",
+    "#     # 每天定时12点运行\n",
+    "#     while True:\n",
+    "#         try:\n",
+    "#             # 获取当前时间\n",
+    "#             current_time = time.strftime(\"%H:%M:%S\", time.localtime())\n",
+    "#             current_time_1 = time.strftime(\"%H:%M:%S\", time.localtime())\n",
+    "# #             print(current_time_1)\n",
+    "\n",
+    "#             # 判断当前时间是否为执行任务的时间点\n",
+    "#             if current_time == \"09:15:00\":\n",
+    "#                 print(\"执行定时任务\")\n",
+    "#                 start()\n",
+    "\n",
+    "#                 # 休眠1秒钟，避免过多占用CPU资源\n",
+    "#                 time.sleep(1)\n",
+    "\n",
+    "#             elif current_time_1 == \"20:00:00\":\n",
+    "#                 print(\"更新数据\")\n",
+    "#                 start_1()\n",
+    "#                 time.sleep(1)\n",
+    "#         except:\n",
+    "#             print('执行错误')\n",
+    "#         time.sleep(1)\n",
+    "\n",
+    "\n",
+    "#     # 检测数据准确性, 需要检测放开\n",
+    "#     # check_data(\"100028098|LISTING_PRICE\")\n",
+    "#     # check_data(\"9137070016544622XB|DAY_Yield\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "运行中\n",
-      "13:38:57\n",
-      "13:38:58\n",
-      "13:38:59\n",
-      "13:39:00\n",
-      "13:39:01\n",
-      "13:39:02\n",
-      "13:39:03\n",
-      "13:39:04\n",
-      "13:39:05\n",
-      "13:39:06\n",
-      "13:39:07\n",
-      "13:39:08\n",
-      "13:39:09\n",
-      "13:39:10\n",
-      "13:39:11\n",
-      "13:39:12\n",
-      "13:39:13\n",
-      "13:39:14\n",
-      "13:39:15\n",
-      "13:39:16\n",
-      "13:39:17\n",
-      "13:39:18\n",
-      "13:39:19\n",
-      "13:39:20\n",
-      "13:39:21\n",
-      "13:39:22\n",
-      "13:39:23\n",
-      "13:39:24\n",
-      "13:39:25\n",
-      "13:39:26\n",
-      "13:39:27\n",
-      "13:39:28\n",
-      "13:39:29\n",
-      "13:39:30\n",
-      "13:39:31\n",
-      "13:39:32\n",
-      "13:39:33\n",
-      "13:39:34\n",
-      "13:39:35\n",
-      "13:39:36\n",
-      "13:39:37\n",
-      "13:39:38\n",
-      "13:39:39\n",
-      "13:39:40\n",
-      "13:39:41\n",
-      "13:39:42\n",
-      "13:39:43\n",
-      "13:39:44\n",
-      "13:39:45\n",
-      "13:39:46\n",
-      "13:39:47\n",
-      "13:39:48\n",
-      "13:39:49\n",
-      "13:39:50\n",
-      "13:39:51\n",
-      "13:39:52\n",
-      "13:39:53\n",
-      "13:39:54\n",
-      "13:39:55\n",
-      "13:39:56\n",
-      "13:39:57\n",
-      "13:39:58\n",
-      "13:39:59\n",
-      "13:40:00\n",
-      "执行定时任务\n",
-      "{'data': {'date': '20250123', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
-      "[{'dataDate': '20250123', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250123', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250123', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5430.0}, {'dataDate': '20250123', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5535.0}]\n",
-      "Using matplotlib backend: Qt5Agg\n",
+      "20250204 <class 'str'>\n",
+      "2025-02-04 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250204', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250204', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8905.0}, {'dataDate': '20250204', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250204', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250204', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250204', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5000.0}, {'dataDate': '20250204', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 4900.0}, {'dataDate': '20250204', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4690.0}, {'dataDate': '20250204', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5050.0}, {'dataDate': '20250204', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250204', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250204', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250204', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250204', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250204', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5400.0}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 105.9453}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -150.0}, {'dataDate': '20250204', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250204', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250204', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6900.0}]\n",
+      "{'dataDate': '20250204', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250204', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: <object object at 0x000001C1300CF310>\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
       "Populating the interactive namespace from numpy and matplotlib\n",
       "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
      ]
@@ -810,10 +813,22 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\Administrator\\Anaconda3\\lib\\site-packages\\IPython\\core\\magics\\pylab.py:160: UserWarning:\n",
+      "d:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\magics\\pylab.py:162: UserWarning:\n",
       "\n",
-      "pylab import has clobbered these variables: ['datetime', 'random', 'plot', '__version__']\n",
+      "pylab import has clobbered these variables: ['__version__', 'random', 'plot', 'datetime']\n",
       "`%matplotlib` prevents importing * from pylab and numpy\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
       "\n"
      ]
     },
@@ -822,344 +837,1163 @@
      "output_type": "stream",
      "text": [
       "Date\n",
-      "2025-01-23    5399.734863\n",
+      "2025-02-04    5410.651855\n",
       "Name: 日度预测价格, dtype: float32\n",
-      "13:40:46\n",
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-      "更新数据\n",
-      "{'data': {'date': '20250123', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
-      "[{'dataDate': '20250123', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250123', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250123', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5430.0}, {'dataDate': '20250123', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5535.0}]\n",
-      "13:45:04\n",
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+      "20250205 <class 'str'>\n",
+      "2025-02-05 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250205', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250205', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8956.0}, {'dataDate': '20250205', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250205', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5140.0}, {'dataDate': '20250205', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250205', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250205', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250205', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5050.0}, {'dataDate': '20250205', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4790.0}, {'dataDate': '20250205', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250205', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5680.0}, {'dataDate': '20250205', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5530.0}, {'dataDate': '20250205', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250205', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5638.0}, {'dataDate': '20250205', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250205', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5635.0}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 81.2796}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -150.0}, {'dataDate': '20250205', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250205', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5050.0}, {'dataDate': '20250205', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250205', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8800.0}, {'dataDate': '20250205', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6200.0}]\n",
+      "{'dataDate': '20250205', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250205', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-05    5494.333496\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250206 <class 'str'>\n",
+      "2025-02-06 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250206', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250206', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8956.0}, {'dataDate': '20250206', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250206', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5160.0}, {'dataDate': '20250206', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250206', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250206', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250206', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250206', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4870.0}, {'dataDate': '20250206', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250206', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250206', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5630.0}, {'dataDate': '20250206', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250206', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5678.0}, {'dataDate': '20250206', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250206', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5655.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 152.4238}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 0.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -150.0}, {'dataDate': '20250206', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250206', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5070.0}, {'dataDate': '20250206', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250206', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8800.0}, {'dataDate': '20250206', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6200.0}]\n",
+      "{'dataDate': '20250206', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-06    5552.835938\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250207 <class 'str'>\n",
+      "2025-02-07 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250207', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250207', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8921.0}, {'dataDate': '20250207', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250207', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5160.0}, {'dataDate': '20250207', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250207', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250207', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250207', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250207', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4870.0}, {'dataDate': '20250207', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250207', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250207', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5630.0}, {'dataDate': '20250207', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250207', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5678.0}, {'dataDate': '20250207', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250207', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5655.0}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5550.0}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': -7.6913}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -150.0}, {'dataDate': '20250207', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250207', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5110.0}, {'dataDate': '20250207', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250207', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8700.0}, {'dataDate': '20250207', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6150.0}]\n",
+      "{'dataDate': '20250207', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250207', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-07    5574.327637\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250208 <class 'str'>\n",
+      "2025-02-08 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250208', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250208', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8866.0}, {'dataDate': '20250208', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250208', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5220.0}, {'dataDate': '20250208', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250208', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE', 'dataValue': 0.0}, {'dataDate': '20250208', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250208', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250208', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4870.0}, {'dataDate': '20250208', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250208', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250208', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250208', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250208', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5578.0}, {'dataDate': '20250208', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250208', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5450.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 153.4345}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 0.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250208', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250208', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5130.0}, {'dataDate': '20250208', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250208', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8700.0}, {'dataDate': '20250208', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6100.0}]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-08    5400.607422\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250209 <class 'str'>\n",
+      "2025-02-09 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250209', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250209', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8875.0}, {'dataDate': '20250209', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250209', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250209', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250209', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250209', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250209', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4870.0}, {'dataDate': '20250209', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250209', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250209', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5470.0}, {'dataDate': '20250209', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250209', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5558.0}, {'dataDate': '20250209', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250209', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 231.5606}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250209', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250209', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250209', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 7000.0}]\n",
+      "{'dataDate': '20250209', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250209', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-09    5392.519043\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250210 <class 'str'>\n",
+      "2025-02-10 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250210', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250210', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8875.0}, {'dataDate': '20250210', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250210', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250210', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250210', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250210', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250210', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250210', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4820.0}, {'dataDate': '20250210', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250210', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250210', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5470.0}, {'dataDate': '20250210', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250210', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5558.0}, {'dataDate': '20250210', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250210', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 236.8478}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250210', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250210', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5160.0}, {'dataDate': '20250210', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250210', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8600.0}, {'dataDate': '20250210', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6000.0}]\n",
+      "{'dataDate': '20250210', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250210', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-10    5405.626465\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250211 <class 'str'>\n",
+      "2025-02-11 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250211', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250211', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8875.0}, {'dataDate': '20250211', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5420.0}, {'dataDate': '20250211', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5280.0}, {'dataDate': '20250211', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250211', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250211', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250211', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250211', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4820.0}, {'dataDate': '20250211', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250211', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250211', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5490.0}, {'dataDate': '20250211', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250211', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250211', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250211', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5420.0}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5420.0}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 263.0919}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250211', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250211', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250211', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250211', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8550.0}, {'dataDate': '20250211', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5700.0}]\n",
+      "{'dataDate': '20250211', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250211', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-11    5423.526855\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250212 <class 'str'>\n",
+      "2025-02-12 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250212', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250212', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8875.0}, {'dataDate': '20250212', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5480.0}, {'dataDate': '20250212', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5280.0}, {'dataDate': '20250212', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250212', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250212', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250212', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250212', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250212', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250212', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5750.0}, {'dataDate': '20250212', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250212', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250212', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5708.0}, {'dataDate': '20250212', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250212', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5705.0}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 332.637}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250212', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250212', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5100.0}, {'dataDate': '20250212', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250212', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8600.0}, {'dataDate': '20250212', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5675.0}]\n",
+      "{'dataDate': '20250212', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250212', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-12    5480.074707\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250213 <class 'str'>\n",
+      "2025-02-13 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250213', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250213', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8793.0}, {'dataDate': '20250213', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5420.0}, {'dataDate': '20250213', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5280.0}, {'dataDate': '20250213', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250213', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250213', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250213', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250213', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250213', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250213', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250213', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5470.0}, {'dataDate': '20250213', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250213', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5658.0}, {'dataDate': '20250213', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250213', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5625.0}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5420.0}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 229.5496}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250213', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250213', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5080.0}, {'dataDate': '20250213', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250213', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250213', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5800.0}]\n",
+      "{'dataDate': '20250213', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250213', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-13    5421.194336\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250214 <class 'str'>\n",
+      "2025-02-14 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250214', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250214', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8722.0}, {'dataDate': '20250214', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5370.0}, {'dataDate': '20250214', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5270.0}, {'dataDate': '20250214', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250214', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250214', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250214', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250214', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250214', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250214', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250214', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250214', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250214', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250214', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250214', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5370.0}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 322.7353}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250214', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250214', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5090.0}, {'dataDate': '20250214', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250214', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8300.0}, {'dataDate': '20250214', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5800.0}]\n",
+      "{'dataDate': '20250214', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250214', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-14    5389.237305\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250215 <class 'str'>\n",
+      "2025-02-15 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250215', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250215', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8722.0}, {'dataDate': '20250215', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250215', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250215', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250215', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250215', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250215', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250215', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250215', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250215', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250215', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250215', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5538.0}, {'dataDate': '20250215', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250215', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5505.0}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5300.0}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 461.3501}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250215', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250215', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250215', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6850.0}]\n",
+      "{'dataDate': '20250215', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250215', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-15    5337.031738\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250216 <class 'str'>\n",
+      "2025-02-16 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250216', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250216', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250216', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250216', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250216', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250216', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250216', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250216', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250216', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5380.0}, {'dataDate': '20250216', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5538.0}, {'dataDate': '20250216', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5505.0}, {'dataDate': '20250216', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5300.0}, {'dataDate': '20250216', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 786.1007}, {'dataDate': '20250216', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-16    5371.679688\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250217 <class 'str'>\n",
+      "2025-02-17 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250217', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250217', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250217', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250217', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5270.0}, {'dataDate': '20250217', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250217', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250217', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250217', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250217', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250217', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250217', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5520.0}, {'dataDate': '20250217', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250217', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250217', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5538.0}, {'dataDate': '20250217', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250217', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5505.0}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5300.0}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1158.2119}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250217', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250217', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5180.0}, {'dataDate': '20250217', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250217', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8300.0}, {'dataDate': '20250217', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5800.0}]\n",
+      "{'dataDate': '20250217', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250217', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-17    5310.317383\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250218 <class 'str'>\n",
+      "2025-02-18 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250218', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250218', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250218', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5480.0}, {'dataDate': '20250218', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5270.0}, {'dataDate': '20250218', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250218', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250218', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250218', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250218', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4690.0}, {'dataDate': '20250218', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250218', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5630.0}, {'dataDate': '20250218', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250218', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250218', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5588.0}, {'dataDate': '20250218', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250218', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5585.0}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1308.9073}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250218', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250218', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5220.0}, {'dataDate': '20250218', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250218', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250218', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5775.0}]\n",
+      "{'dataDate': '20250218', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250218', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-18    5466.825195\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250219 <class 'str'>\n",
+      "2025-02-19 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250219', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250219', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250219', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250219', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250219', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250219', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250219', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250219', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4690.0}, {'dataDate': '20250219', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250219', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250219', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250219', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250219', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5668.0}, {'dataDate': '20250219', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250219', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5665.0}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5550.0}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1600.0196}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250219', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250219', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5220.0}, {'dataDate': '20250219', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250219', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250219', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5750.0}]\n",
+      "{'dataDate': '20250219', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250219', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-19    5479.943848\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250220 <class 'str'>\n",
+      "2025-02-20 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250220', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250220', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250220', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5340.0}, {'dataDate': '20250220', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250220', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250220', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250220', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250220', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4770.0}, {'dataDate': '20250220', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250220', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250220', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250220', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250220', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5668.0}, {'dataDate': '20250220', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250220', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5665.0}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5550.0}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1471.9223}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250220', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250220', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5230.0}, {'dataDate': '20250220', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250220', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8500.0}, {'dataDate': '20250220', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5750.0}]\n",
+      "{'dataDate': '20250220', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250220', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-20    5478.131348\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250221 <class 'str'>\n",
+      "2025-02-21 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250221', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250221', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250221', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5340.0}, {'dataDate': '20250221', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250221', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250221', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250221', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250221', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4770.0}, {'dataDate': '20250221', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250221', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250221', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250221', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250221', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5668.0}, {'dataDate': '20250221', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250221', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5665.0}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1313.0783}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250221', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250221', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5240.0}, {'dataDate': '20250221', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250221', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250221', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5875.0}]\n",
+      "{'dataDate': '20250221', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n",
+      "{'dataDate': '20250221', 'dataItemNo': 'C01100008|PLAN_SALE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-21    5482.609375\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250222 <class 'str'>\n",
+      "2025-02-22 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250222', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250222', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8593.0}, {'dataDate': '20250222', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250222', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE', 'dataValue': 0.0}, {'dataDate': '20250222', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250222', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250222', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4770.0}, {'dataDate': '20250222', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250222', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250222', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250222', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250222', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5618.0}, {'dataDate': '20250222', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250222', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1043.6716}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 700.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250222', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250222', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250222', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6850.0}]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-22    5422.866211\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250223 <class 'str'>\n",
+      "2025-02-23 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250223', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250223', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8513.0}, {'dataDate': '20250223', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250223', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250223', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250223', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250223', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4770.0}, {'dataDate': '20250223', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250223', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250223', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250223', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250223', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5568.0}, {'dataDate': '20250223', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250223', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5400.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1127.7162}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 400.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250223', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250223', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250223', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6850.0}]\n",
+      "{'dataDate': '20250223', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-23    5481.371094\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "20250224 <class 'str'>\n",
+      "2025-02-24 00:00:00 <class 'datetime.datetime'>\n",
+      "{'data': {'date': '20250224', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n",
+      "[{'dataDate': '20250224', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8513.0}, {'dataDate': '20250224', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250224', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250224', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250224', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250224', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250224', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4670.0}, {'dataDate': '20250224', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250224', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250224', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250224', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250224', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5488.0}, {'dataDate': '20250224', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250224', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5455.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5400.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1218.5774}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 400.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250224', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250224', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250224', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250224', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8300.0}, {'dataDate': '20250224', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5900.0}]\n",
+      "{'dataDate': '20250224', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using matplotlib backend: QtAgg\n",
+      "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n",
+      "Populating the interactive namespace from numpy and matplotlib\n",
+      "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n",
+      "\n",
+      "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n",
+      "\n",
+      "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date\n",
+      "2025-02-24    5480.000488\n",
+      "Name: 日度预测价格, dtype: float32\n",
+      "[5410.65, 5494.33, 5552.84, 5574.33, 5400.61, 5392.52, 5405.63, 5423.53, 5480.07, 5421.19, 5389.24, 5337.03, 5371.68, 5310.32, 5466.83, 5479.94, 5478.13, 5482.61, 5422.87, 5481.37, 5480.0]\n"
      ]
     }
    ],
    "source": [
+    "start_date = datetime(2025, 2, 4)\n",
+    "end_date = datetime(2025, 2, 25)\n",
     "\n",
-    "if __name__ == \"__main__\":\n",
-    "    print('运行中')\n",
-    "    # 需要单独运行放开\n",
-    "#     start()\n",
-    "#     start_1(date='2025-01-22')\n",
-    "#     start_1()\n",
+    "while start_date < end_date:\n",
+    "    date = start_date.strftime('%Y%m%d')\n",
+    "    print(date,type(date))\n",
+    "    start(date)\n",
+    "    time.sleep(1)\n",
+    "    # start_2(start_date)\n",
+    "    start_date += timedelta(days=1)\n",
+    "    time.sleep(5)\n",
     "\n",
-    "    # 每天定时12点运行\n",
-    "    while True:\n",
-    "        try:\n",
-    "            # 获取当前时间\n",
-    "            current_time = time.strftime(\"%H:%M:%S\", time.localtime())\n",
-    "            current_time_1 = time.strftime(\"%H:%M:%S\", time.localtime())\n",
-    "#             print(current_time_1)\n",
-    "\n",
-    "            # 判断当前时间是否为执行任务的时间点\n",
-    "            if current_time == \"09:15:00\":\n",
-    "                print(\"执行定时任务\")\n",
-    "                start()\n",
-    "\n",
-    "                # 休眠1秒钟，避免过多占用CPU资源\n",
-    "                time.sleep(1)\n",
-    "\n",
-    "            elif current_time_1 == \"20:00:00\":\n",
-    "                print(\"更新数据\")\n",
-    "                start_1()\n",
-    "                time.sleep(1)\n",
-    "        except:\n",
-    "            print('执行错误')\n",
-    "        time.sleep(1)\n",
-    "\n",
-    "\n",
-    "    # 检测数据准确性, 需要检测放开\n",
-    "    # check_data(\"100028098|LISTING_PRICE\")\n",
-    "    # check_data(\"9137070016544622XB|DAY_Yield\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# from datetime import datetime, timedelta\n",
-    "\n",
-    "# start_date = datetime(2025, 1, 21)\n",
-    "# end_date = datetime(2025, 1, 23)\n",
-    "\n",
-    "# while start_date < end_date:\n",
-    "#     print(start_date.strftime('%Y%m%d'))\n",
-    "#     start(start_date)\n",
-    "#     # time.sleep(1)\n",
-    "#     # start_2(start_date)\n",
-    "#     start_date += timedelta(days=1)\n",
-    "#     time.sleep(5)\n",
-    "\n",
-    "# print(price_list)"
+    "print(price_list)"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "base",
    "language": "python",
    "name": "python3"
   },
@@ -1173,7 +2007,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.0"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,
diff --git a/aisenzhecode/液化石油气/液化气数据.xls b/aisenzhecode/液化石油气/液化气数据.xls
index 23df85d..cf91e1c 100644
Binary files a/aisenzhecode/液化石油气/液化气数据.xls and b/aisenzhecode/液化石油气/液化气数据.xls differ
diff --git a/config_jingbo_zhoudu.py b/config_jingbo_zhoudu.py
index 2cd60d1..5b24d69 100644
--- a/config_jingbo_zhoudu.py
+++ b/config_jingbo_zhoudu.py
@@ -160,7 +160,7 @@ table_name = 'v_tbl_crude_oil_warning'
 
 ### 开关
 is_train = False # 是否训练
-is_debug = False # 是否调试
+is_debug = True # 是否调试
 is_eta = False # 是否使用eta接口
 is_market = True # 是否通过市场信息平台获取特征 ,在is_eta 为true 的情况下生效
 is_timefurture = True # 是否使用时间特征
@@ -182,7 +182,7 @@ print("数据库连接成功",host,dbname,dbusername)
 
 
 # 数据截取日期
-start_year = 2020 # 数据开始年份
+start_year = 2017 # 数据开始年份
 end_time = '' # 数据截取日期
 freq = 'W'  # 时间频率，"D": 天 "W": 周"M": 月"Q": 季度"A": 年 "H": 小时 "T": 分钟 "S": 秒 "B": 工作日
 delweekenday = True if freq == 'B' else False # 是否删除周末数据
@@ -193,7 +193,7 @@ if add_kdj and is_edbnamelist:
 
 ### 模型参数  
 y = 'Brent连1合约价格' # 原油指标数据的目标变量  Brent连1合约价格   Brent活跃合约
-horizon =4 # 预测的步长
+horizon =2 # 预测的步长
 input_size = 12  # 输入序列长度
 train_steps = 50 if is_debug else 1000 # 训练步数,用来限定epoch次数
 val_check_steps = 30  # 评估频率
diff --git a/lib/dataread.py b/lib/dataread.py
index 2d4f838..7d82d18 100644
--- a/lib/dataread.py
+++ b/lib/dataread.py
@@ -42,9 +42,9 @@ plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
 
 # from config_jingbo_pro import *
 # from config_jingbo import *
-# from config_jingbo_zhoudu import *
+from config_jingbo_zhoudu import *
 # from config_yongan import *
-from config_juxiting import *
+# from config_juxiting import *
 # from config_juxiting_zhoudu import *
 # from config_juxiting_pro import *
 
diff --git a/models/nerulforcastmodels.py b/models/nerulforcastmodels.py
index 3fa05a9..5202155 100644
--- a/models/nerulforcastmodels.py
+++ b/models/nerulforcastmodels.py
@@ -197,7 +197,8 @@ def ex_Model(df,horizon,input_size,train_steps,val_check_steps,early_stop_patien
     #进行未来时间预测
     df_predict=nf.predict(df_test).reset_index()
     # 去掉index列
-    df_predict.drop(columns=['index'], inplace=True)
+    if 'index' in df_predict.columns:
+        df_predict.drop(columns=['index'], inplace=True)
     df_predict.astype({col: 'float32' for col in df_predict.columns if col not in ['ds'] })
     
     # 添加预测时间
@@ -859,7 +860,7 @@ def model_losss(sqlitedb,end_time):
     # 然后筛选出那些 cutoff 等于 max_cutoff 的行，这样就得到了每个分组中 cutoff 最大的行，并保留了其他列
     df_combined = df_combined[df_combined['CREAT_DATE'] == df_combined['max_cutoff']]
     # 删除模型生成的cutoff列
-    df_combined.drop(columns=['CREAT_DATE', 'max_cutoff','created_dt','min_within_quantile','max_within_quantile','id','min_price','max_price','LOW_PRICE','HIGH_PRICE','mean'], inplace=True,errors='ignore') 
+    df_combined.drop(columns=['CREAT_DATE', 'max_cutoff','created_dt','min_within_quantile','max_within_quantile','id','min_price','max_price','LOW_PRICE','HIGH_PRICE'], inplace=True,errors='ignore') 
     # 获取模型名称
     modelnames  = df_combined.columns.to_list()[1:] 
     if 'y' in modelnames: