From 81e255747c1e27905d4c4f0a124bd5b9cbfba1e6 Mon Sep 17 00:00:00 2001
From: workpc <liurui_test@163.com>
Date: Mon, 23 Dec 2024 17:12:13 +0800
Subject: [PATCH] =?UTF-8?q?aup=E6=8E=A5=E5=8F=A3=E6=9B=B4=E6=94=B9?=
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---
 aisenzhecode/沥青/定性模型数据项12-11.xls     |  Bin 166400 -> 166400 bytes
 aisenzhecode/沥青/日度价格预测_最佳模型.pkl   |  Bin 689255 -> 712105 bytes
 .../沥青/沥青定性模型每日推送-ytj.ipynb       |   11 +-
 .../沥青/沥青定量价格预测每日推送-ytj.ipynb   |   99 +-
 aisenzhecode/沥青/沥青数据项.xls              |  Bin 513024 -> 513024 bytes
 auptest.py                                    |   49 +-
 原油价格预测准确率计算.ipynb                  | 1351 ++++++++++++++---
 7 files changed, 1221 insertions(+), 289 deletions(-)

diff --git a/aisenzhecode/沥青/定性模型数据项12-11.xls b/aisenzhecode/沥青/定性模型数据项12-11.xls
index a7e4b8b4dc5eed5bf762fc4d4a9b9979a8632642..8a5346d7ca02e6bd34dc955c6bf2f73067b31add 100644
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diff --git a/aisenzhecode/沥青/日度价格预测_最佳模型.pkl b/aisenzhecode/沥青/日度价格预测_最佳模型.pkl
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diff --git a/aisenzhecode/沥青/沥青定性模型每日推送-ytj.ipynb b/aisenzhecode/沥青/沥青定性模型每日推送-ytj.ipynb
index ca9cba7..331f99e 100644
--- a/aisenzhecode/沥青/沥青定性模型每日推送-ytj.ipynb
+++ b/aisenzhecode/沥青/沥青定性模型每日推送-ytj.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -211,7 +211,6 @@
     "    \n",
     "    \n",
     "    \n",
-    "    \n",
     "def start_1():\n",
     "    workbook = xlrd.open_workbook(read_file_path_name)\n",
     "\n",
@@ -472,22 +471,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "20241209\n"
+      "20241217\n"
      ]
     }
    ],
    "source": [
     "from datetime import datetime, timedelta\n",
     "\n",
-    "start_date = datetime(2024, 12, 9)\n",
-    "end_date = datetime(2024, 12, 10)\n",
+    "start_date = datetime(2024, 12, 17)\n",
+    "end_date = datetime(2024, 12, 18)\n",
     "\n",
     "while start_date < end_date:\n",
     "    print(start_date.strftime('%Y%m%d'))\n",
diff --git a/aisenzhecode/沥青/沥青定量价格预测每日推送-ytj.ipynb b/aisenzhecode/沥青/沥青定量价格预测每日推送-ytj.ipynb
index 0d58135..1bc0950 100644
--- a/aisenzhecode/沥青/沥青定量价格预测每日推送-ytj.ipynb
+++ b/aisenzhecode/沥青/沥青定量价格预测每日推送-ytj.ipynb
@@ -795,14 +795,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "20241212\n"
+      "20241217\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19760\\2239815117.py:299: UserWarning:\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_4500\\2239815117.py:299: 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"
@@ -812,7 +812,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Using matplotlib backend: <object object at 0x0000015D1F0FF090>\n",
+      "Using matplotlib backend: <object object at 0x0000017F4168F090>\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"
@@ -824,7 +824,7 @@
      "text": [
       "d:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\magics\\pylab.py:162: UserWarning:\n",
       "\n",
-      "pylab import has clobbered these variables: ['datetime', 'plot', 'random', '__version__']\n",
+      "pylab import has clobbered these variables: ['__version__', 'plot', 'random', 'datetime']\n",
       "`%matplotlib` prevents importing * from pylab and numpy\n",
       "\n"
      ]
@@ -844,108 +844,33 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19760\\2239815117.py:239: UserWarning:\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_4500\\2239815117.py:239: 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": [
-      "日期\n",
-      "2024-12-12    3552.045898\n",
-      "Name: 日度预测价格, dtype: float32\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19760\\2239815117.py:273: FutureWarning:\n",
+      "\n",
+      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_4500\\2239815117.py:273: 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": [
-      "{\"confirmFlg\":false,\"status\":true}\n",
-      "新增数据： ['2024-12-12', 7957.0, 7066.0, 0.1, 0.0, 3650.0, 0.9, 0.0, 0.0, 3540.0, 7.9, 0.2, 0.2, 3500.0, 0.6, '', 3500.0, 71.05, 73.53, '', 3510.0, 29.5977, '', '', '', '', 229522.1, 11025.3, 3426.4568, '', '', 42263.29278, 6647.44, 3970.0]\n",
-      "20241213\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19760\\2239815117.py:299: 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",
-      "Best score: 0.997\n",
-      "Best parameters set:\n",
-      "\tlearning_rate: 0.1\n",
-      "\tmax_depth: 8\n",
-      "\tn_estimators: 100\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19760\\2239815117.py:239: 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": [
       "日期\n",
-      "2024-12-13    3504.912354\n",
-      "Name: 日度预测价格, dtype: float32\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_19760\\2239815117.py:273: 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": [
+      "2024-12-17    3501.835693\n",
+      "Name: 日度预测价格, dtype: float32\n",
       "{\"confirmFlg\":false,\"status\":true}\n",
-      "新增数据： ['2024-12-13', 7957.0, 7066.0, 0.1, 0.0, 3650.0, 0.55, 0.0, 0.0, 3540.0, 7.9, 0.2, 0.2, 3600.0, 0.6, '', 3500.0, 71.05, 73.41, '', 3512.0, 29.5977, '', '', '', '', 229522.1, 8091.12, 3417.4442, '', '', 41436.2654696, 6913.5165, '']\n"
+      "新增数据： ['2024-12-17', 7957.0, 6984.0, 0.0, 0.25, 3650.0, 0.55, 0.0, 0.0, 3520.0, 7.9, 0.2, 0.2, 3500.0, 0.75, '', 3500.0, 74.35, 72.69, '', 3522.0, 28.8998, '', '', '', 13.58990112, 229522.1, 7722.02, 3511.1707, '', '', 40514.8218813, 7088.86, '']\n"
      ]
     }
    ],
    "source": [
     "from datetime import datetime, timedelta\n",
     "\n",
-    "start_date = datetime(2024, 12, 12)\n",
-    "end_date = datetime(2024, 12, 14)\n",
+    "start_date = datetime(2024, 12, 17)\n",
+    "end_date = datetime(2024, 12, 18)\n",
     "\n",
     "while start_date < end_date:\n",
     "    print(start_date.strftime('%Y%m%d'))\n",
diff --git a/aisenzhecode/沥青/沥青数据项.xls b/aisenzhecode/沥青/沥青数据项.xls
index ce5e7e69cd22f63dd0fe37668f5f8e75e6f676a1..c00897922acfb3e2a107fc958800f4ec73e6f12d 100644
GIT binary patch
delta 1273
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diff --git a/auptest.py b/auptest.py
index 543054e..da53b5a 100644
--- a/auptest.py
+++ b/auptest.py
@@ -34,14 +34,15 @@ auth = HttpNtlmAuth(f'{graphql_username}', f'{graphql_password}')
 
 # 请求头设置
 headers = {'content-type': 'application/json;charset=UTF-8'}
-
 def insert_api_log(request_time, request_url, request_method, request_params, response_content, response_time):
     '''
     请求日志表 v_tbl_aup_api_log 写入
     '''
     try:
         # 建立数据库连接
-        cnx = mysql.connector.connect(**config)
+        global cnx
+        if cnx is None:
+            cnx = mysql.connector.connect(**config)
         cursor = cnx.cursor()
         # 先查询表中已有记录的数量，用于生成新记录的ID
         # count_query = "SELECT max(ID) FROM v_tbl_aup_api_log"
@@ -70,12 +71,14 @@ def insert_api_log(request_time, request_url, request_method, request_params, re
         print(f"Error: {err}")
     finally:
         # 关闭游标和连接
-        if cursor:
-            cursor.close()
-        if cnx:
-            cnx.close()
+        try:
+            if cursor:
+                cursor.close()
+        except UnboundLocalError:
+            pass
 
 
+cnx = None
 
 
 tags_metadata = [
@@ -369,8 +372,7 @@ async def generate_graphql_query(
         full_path = str(request.url.path)
         session = requests.Session()
         try:
-            response = await session.post(url=url, headers=headers, json=payload_json, auth=auth, verify=False, timeout=300)
-            print(type(response))
+            response = session.post(url=url, headers=headers, json=payload_json, auth=auth, verify=False, timeout=300)
         except requests.exceptions.ConnectTimeout as e:
           # 构造符合错误情况的响应数据字典
           error_response_data = {
@@ -408,12 +410,13 @@ async def generate_graphql_query(
 
         if response.status_code!= 200:
             raise HTTPException(status_code=response.status_code, detail=response.text)
+        print(response.json())
         return response.json()
     except TypeError as e:
         return {"error": str(e)}
 
 @app.get("/get_cases",tags=['get_cases'])
-async def post_cases_query_async(request: Request):
+async def get_cases_query_async(request: Request):
     payload_json2 = {
         "query": templates.case_qurey
     }
@@ -421,7 +424,12 @@ async def post_cases_query_async(request: Request):
     request_time = datetime.now()
     session = requests.Session()
     try:
-        response = await session.post(url=url, headers=headers, json=payload_json2, auth=auth, verify=False)
+        response = session.post(url=url, headers=headers, json=payload_json2, auth=auth, verify=False)
+        # 将JSON字符串解析为Python字典对象
+        res = response.json()
+        # # 提取name列表
+        # name_list = [item["name"] for item in res["data"]["cases"]["items"]]
+        # res['name_list'] = name_list
     except requests.exceptions.ConnectTimeout as e:
           # 构造符合错误情况的响应数据字典
           error_response_data = {
@@ -429,8 +437,8 @@ async def post_cases_query_async(request: Request):
               "data": {},
               "status_code": 503  # 使用合适的状态码，如503表示服务暂时不可用，可根据具体错误类型调整
           }
-          response = error_response_data
-          raise HTTPException(status_code=503, detail=response)  # 抛出合适状态码的HTTPException
+          res = error_response_data
+          raise HTTPException(status_code=503, detail=res)  # 抛出合适状态码的HTTPException
     except requests.exceptions.RequestException as e:
         # 捕获其他请求相关的异常，统一处理
         error_response_data = {
@@ -439,14 +447,10 @@ async def post_cases_query_async(request: Request):
             "status_code": 500
         }
         
-        response = error_response_data
-        raise HTTPException(status_code=500, detail=response)
+        res = error_response_data
+        raise HTTPException(status_code=500, detail=res)
     finally:
         response_time = datetime.now()
-        try:
-            res = response.json()
-        except (UnboundLocalError,AttributeError):
-            res = response
         # 调用插入日志的函数，将相关信息记录到数据库中（假设insert_api_log函数已正确定义且可访问）
         insert_api_log(
             request_time,
@@ -460,16 +464,11 @@ async def post_cases_query_async(request: Request):
     if response.status_code!= 200:
         raise HTTPException(status_code=response.status_code, detail=response.text)
     
-    # 将JSON字符串解析为Python字典对象
-    data_dict = response.json()
-    # 提取name列表
-    name_list = [item["name"] for item in data_dict["data"]["cases"]["items"]]
-    data_dict['name_lsit'] = name_list
-    return json.dumps(data_dict)
+    return res
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="127.0.0.1", port=8003)
+    uvicorn.run(app, host="0.0.0.0", port=8003)
 
 
 # query = """
diff --git a/原油价格预测准确率计算.ipynb b/原油价格预测准确率计算.ipynb
index e024d65..3b669f3 100644
--- a/原油价格预测准确率计算.ipynb
+++ b/原油价格预测准确率计算.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 41,
    "id": "9daadf20-caa6-4b25-901c-6cc3ef563f58",
    "metadata": {},
    "outputs": [
@@ -126,19 +126,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 79,
    "id": "0d77ab7d",
    "metadata": {},
    "outputs": [],
    "source": [
     "# 模型评估前五均值      \n",
-    "df['min_price'] = df.iloc[:,1:6].mean(axis=1) -1.5\n",
-    "df['max_price'] = df.iloc[:,1:6].mean(axis=1) +1.5"
+    "df['min_price'] = df.iloc[:,1:11].mean(axis=1) -1\n",
+    "df['max_price'] = df.iloc[:,1:11].mean(axis=1) +1"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 80,
    "id": "e51c3fd0-6bff-45de-b8b6-971e7986c7a7",
    "metadata": {},
    "outputs": [
@@ -146,114 +146,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "         开始日期        结束日期  准确率\n",
-      "0  2024-09-27  2024-10-04    0\n",
-      "         开始日期        结束日期  准确率\n",
-      "0  2024-09-27  2024-10-04    0\n",
-      "         开始日期        结束日期  准确率\n",
-      "0  2024-09-27  2024-10-04    0\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "         开始日期        结束日期  准确率\n",
-      "0  2024-09-27  2024-10-04    0\n",
-      "         开始日期        结束日期  准确率\n",
-      "0  2024-09-27  2024-10-04    0\n",
       "         开始日期        结束日期       准确率\n",
-      "0  2024-10-04  2024-10-11  0.433988\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-04  2024-10-11  0.433988\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-04  2024-10-11  0.433988\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-04  2024-10-11  0.433988\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-04  2024-10-11  0.433988\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-11  2024-10-18  0.367557\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-11  2024-10-18  0.367557\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-11  2024-10-18  0.367557\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-11  2024-10-18  0.367557\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-11  2024-10-18  0.367557\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-18  2024-10-25  0.342808\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-18  2024-10-25  0.342808\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-18  2024-10-25  0.342808\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-18  2024-10-25  0.342808\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-18  2024-10-25  0.342808\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-25  2024-11-01  0.397058\n",
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-      "0  2024-10-25  2024-11-01  0.397058\n",
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-      "0  2024-10-25  2024-11-01  0.397058\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-25  2024-11-01  0.397058\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-10-25  2024-11-01  0.397058\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-01  2024-11-08  0.666605\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-01  2024-11-08  0.666605\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-01  2024-11-08  0.666605\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-01  2024-11-08  0.666605\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-01  2024-11-08  0.666605\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-08  2024-11-15  0.805488\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-08  2024-11-15  0.805488\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-08  2024-11-15  0.805488\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-08  2024-11-15  0.805488\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-08  2024-11-15  0.805488\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-15  2024-11-22  0.744558\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-15  2024-11-22  0.744558\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-15  2024-11-22  0.744558\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-15  2024-11-22  0.744558\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-15  2024-11-22  0.744558\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-22  2024-11-29  0.351228\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-22  2024-11-29  0.351228\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-22  2024-11-29  0.351228\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-22  2024-11-29  0.351228\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-22  2024-11-29  0.351228\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-29  2024-12-06  0.727334\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-29  2024-12-06  0.727334\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-29  2024-12-06  0.727334\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-29  2024-12-06  0.727334\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-11-29  2024-12-06  0.727334\n",
-      "         开始日期        结束日期       准确率\n",
-      "0  2024-12-06  2024-12-13  0.835391\n"
+      "0  2024-09-30  2024-10-04         0\n",
+      "0  2024-10-07  2024-10-11  0.509306\n",
+      "0  2024-10-14  2024-10-18  0.498337\n",
+      "0  2024-10-21  2024-10-25  0.437821\n",
+      "0  2024-10-28  2024-11-01  0.436979\n",
+      "0  2024-11-04  2024-11-08  0.482764\n",
+      "0  2024-11-11  2024-11-15  0.682747\n",
+      "0  2024-11-18  2024-11-22  0.694599\n",
+      "0  2024-11-25  2024-11-29  0.380507\n",
+      "0  2024-12-02  2024-12-06  0.732552\n",
+      "0  2024-12-09  2024-12-13  0.559709\n"
      ]
     }
    ],
@@ -288,40 +192,50 @@
     "    endtime = end_time\n",
     "    endtimeweek = datetime.datetime.strptime(endtime, '%Y-%m-%d')\n",
     "    up_week = endtimeweek - datetime.timedelta(days=endtimeweek.weekday() + 14)\n",
-    "    up_week_dates = [up_week + datetime.timedelta(days=i) for i in range(14)][4:-2]\n",
-    "    up_week_dates = [date.strftime('%Y-%m-%d') for date in up_week_dates]\n",
-    "    return up_week_dates\n",
+    "    up_week_dates = [up_week + datetime.timedelta(days=i) for i in range(14)]\n",
+    "    create_dates = [date.strftime('%Y-%m-%d') for date in up_week_dates[4:-3]]\n",
+    "    ds_dates = [date.strftime('%Y-%m-%d') for date in up_week_dates[-7:-2]]\n",
+    "    return create_dates,ds_dates\n",
     "\n",
     "# 计算准确率并保存结果\n",
-    "def _get_accuracy_rate(df,up_week_dates,endtime):\n",
+    "def _get_accuracy_rate(df,create_dates,ds_dates,endtime):\n",
     "    df3 = df.copy()\n",
-    "    df3 = df3[df3['CREAT_DATE'].isin(up_week_dates)]\n",
-    "    df3 = df3[df3['ds'].isin(up_week_dates)]\n",
+    "    df3 = df3[df3['CREAT_DATE'].isin(create_dates)]\n",
+    "    df3 = df3[df3['ds'].isin(ds_dates)]\n",
     "    accuracy_rote = 0\n",
-    "    for i,group in df3.groupby('ds'):\n",
+    "    for i,group in df3.groupby('CREAT_DATE'):\n",
+    "        # print('日期：',i)\n",
+    "        # print(group)\n",
     "        # print('权重：',weight_dict[len(group)-1])\n",
     "        # print('准确率：',(group['ACCURACY'].sum()/len(group))*weight_dict[len(group)-1])\n",
     "        accuracy_rote += (group['ACCURACY'].sum()/len(group))*weight_dict[len(group)-1]\n",
     "    df3.to_csv(os.path.join(dataset,f'accuracy_{endtime}.csv'),index=False)\n",
     "    df4 = pd.DataFrame(columns=['开始日期','结束日期','准确率'])\n",
-    "    df4.loc[len(df4)] = {'开始日期':up_week_dates[0],'结束日期':up_week_dates[-1],'准确率':accuracy_rote}\n",
+    "    df4.loc[len(df4)] = {'开始日期':ds_dates[0],'结束日期':ds_dates[-1],'准确率':accuracy_rote}\n",
     "    df4.to_csv(os.path.join(dataset,f'accuracy_rote_{endtime}.csv'),index=False)\n",
-    "    print(df4)\n",
+    "    # print(df4)\n",
+    "    return df4\n",
     "    # df4.to_sql(\"accuracy_rote\",  con=sqlitedb.connection, if_exists='append', index=False)\n",
     "\n",
     "\n",
     "end_times = df['CREAT_DATE'].unique()\n",
+    "df7 = pd.DataFrame(columns=['开始日期','结束日期','准确率'])\n",
     "for endtime in end_times:\n",
-    "    up_week_dates = get_week_date(endtime)\n",
-    "    _get_accuracy_rate(df,up_week_dates,endtime)\n",
-    "\n",
+    "    create_dates,ds_dates = get_week_date(endtime)\n",
+    "    df8 = _get_accuracy_rate(df,create_dates,ds_dates,endtime)\n",
+    "    df7 = pd.concat([df7,df8],axis=0)\n",
+    "df7.to_csv(os.path.join(dataset,f'accuracy_rote_all.csv'),index=False)\n",
+    "# print(df7)\n",
+    "# df7去重\n",
+    "df7 = df7.drop_duplicates()\n",
+    "print(df7)\n",
     "# 打印结果\n",
-    "\n"
+    " \n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 62,
    "id": "0f942c69",
    "metadata": {},
    "outputs": [
@@ -330,18 +244,48 @@
      "output_type": "stream",
      "text": [
       "(255, 6)\n",
-      "          ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
-      "0 2024-10-08  78.172055  81.172055      76.36      76.36  2024-10-07\n",
-      "1 2024-10-09  78.017734  81.017734      75.15      75.15  2024-10-07\n",
-      "2 2024-10-10  78.196563  81.196563      76.72      76.72  2024-10-07\n",
-      "3 2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
-      "4 2024-10-14  78.448240  81.448240      74.86      74.86  2024-10-07\n",
-      "5 2024-10-09  75.442758  78.442758      75.15      75.15  2024-10-08\n",
-      "6 2024-10-10  75.684414  78.684414      76.72      76.72  2024-10-08\n",
-      "7 2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
-      "8 2024-10-14  75.819379  78.819379      74.86      74.86  2024-10-08\n",
-      "9 2024-10-15  75.830953  78.830953      73.34      73.34  2024-10-08\n",
-      "['2024-10-07', '2024-10-08', '2024-10-09', '2024-10-10', '2024-10-11', '2024-10-12', '2024-10-13']\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "0  2024-10-08  78.172055  81.172055      76.36      76.36  2024-10-07\n",
+      "1  2024-10-09  78.017734  81.017734      75.15      75.15  2024-10-07\n",
+      "2  2024-10-10  78.196563  81.196563      76.72      76.72  2024-10-07\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "4  2024-10-14  78.448240  81.448240      74.86      74.86  2024-10-07\n",
+      "5  2024-10-09  75.442758  78.442758      75.15      75.15  2024-10-08\n",
+      "6  2024-10-10  75.684414  78.684414      76.72      76.72  2024-10-08\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "8  2024-10-14  75.819379  78.819379      74.86      74.86  2024-10-08\n",
+      "9  2024-10-15  75.830953  78.830953      73.34      73.34  2024-10-08\n",
+      "10 2024-10-10  75.439643  78.439643      76.72      76.72  2024-10-09\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "12 2024-10-14  75.775363  78.775363      74.86      74.86  2024-10-09\n",
+      "13 2024-10-15  75.869936  78.869936      73.34      73.34  2024-10-09\n",
+      "14 2024-10-16  76.203067  79.203067      73.42      73.42  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "16 2024-10-14  77.326639  80.326639      74.86      74.86  2024-10-10\n",
+      "17 2024-10-15  77.711800  80.711800      73.34      73.34  2024-10-10\n",
+      "18 2024-10-16  78.129062  81.129062      73.42      73.42  2024-10-10\n",
+      "19 2024-10-17  78.237173  81.237173      73.26      73.26  2024-10-10\n",
+      "['2024-09-27', '2024-09-28', '2024-09-29', '2024-09-30', '2024-10-01', '2024-10-02', '2024-10-03', '2024-10-04']\n",
+      "(0, 6)\n",
+      "Empty DataFrame\n",
+      "Columns: [ds, min_price, max_price, LOW_PRICE, LOW_PRICE, CREAT_DATE]\n",
+      "Index: []\n",
+      "['2024-09-27', '2024-09-28', '2024-09-29', '2024-09-30', '2024-10-01', '2024-10-02', '2024-10-03', '2024-10-04']\n",
+      "(0, 6)\n",
+      "Empty DataFrame\n",
+      "Columns: [ds, min_price, max_price, LOW_PRICE, LOW_PRICE, CREAT_DATE]\n",
+      "Index: []\n",
+      "['2024-09-27', '2024-09-28', '2024-09-29', '2024-09-30', '2024-10-01', '2024-10-02', '2024-10-03', '2024-10-04']\n",
+      "(0, 6)\n",
+      "Empty DataFrame\n",
+      "Columns: [ds, min_price, max_price, LOW_PRICE, LOW_PRICE, CREAT_DATE]\n",
+      "Index: []\n",
+      "['2024-09-27', '2024-09-28', '2024-09-29', '2024-09-30', '2024-10-01', '2024-10-02', '2024-10-03', '2024-10-04']\n",
+      "(0, 6)\n",
+      "Empty DataFrame\n",
+      "Columns: [ds, min_price, max_price, LOW_PRICE, LOW_PRICE, CREAT_DATE]\n",
+      "Index: []\n",
+      "['2024-10-04', '2024-10-05', '2024-10-06', '2024-10-07', '2024-10-08', '2024-10-09', '2024-10-10', '2024-10-11']\n",
       "(10, 6)\n",
       "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
       "0  2024-10-08  78.172055  81.172055      76.36      76.36  2024-10-07\n",
@@ -353,34 +297,1100 @@
       "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
       "10 2024-10-10  75.439643  78.439643      76.72      76.72  2024-10-09\n",
       "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
-      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n"
-     ]
-    },
-    {
-     "ename": "ValueError",
-     "evalue": "Per-column arrays must each be 1-dimensional",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[31], line 33\u001b[0m\n\u001b[0;32m     31\u001b[0m sns\u001b[38;5;241m.\u001b[39mscatterplot(x\u001b[38;5;241m=\u001b[39mdf6\u001b[38;5;241m.\u001b[39mindex,y\u001b[38;5;241m=\u001b[39mdf6[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmin_price\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues,data\u001b[38;5;241m=\u001b[39mdf6)\n\u001b[0;32m     32\u001b[0m sns\u001b[38;5;241m.\u001b[39mscatterplot(x\u001b[38;5;241m=\u001b[39mdf6\u001b[38;5;241m.\u001b[39mindex,y\u001b[38;5;241m=\u001b[39mdf6[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmax_price\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues,data\u001b[38;5;241m=\u001b[39mdf6)\n\u001b[1;32m---> 33\u001b[0m sns\u001b[38;5;241m.\u001b[39mscatterplot(x\u001b[38;5;241m=\u001b[39mdf6\u001b[38;5;241m.\u001b[39mindex,y\u001b[38;5;241m=\u001b[39mdf6[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mLOW_PRICE\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues,data\u001b[38;5;241m=\u001b[39mdf6)\n\u001b[0;32m     34\u001b[0m sns\u001b[38;5;241m.\u001b[39mscatterplot(x\u001b[38;5;241m=\u001b[39mdf6\u001b[38;5;241m.\u001b[39mindex,y\u001b[38;5;241m=\u001b[39mdf6[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mHIGH_PRICE\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues,data\u001b[38;5;241m=\u001b[39mdf6)\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\seaborn\\relational.py:742\u001b[0m, in \u001b[0;36mscatterplot\u001b[1;34m(data, x, y, hue, size, style, palette, hue_order, hue_norm, sizes, size_order, size_norm, markers, style_order, legend, ax, **kwargs)\u001b[0m\n\u001b[0;32m    732\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mscatterplot\u001b[39m(\n\u001b[0;32m    733\u001b[0m     data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m,\n\u001b[0;32m    734\u001b[0m     x\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, y\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, hue\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, size\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, style\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    738\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs\n\u001b[0;32m    739\u001b[0m ):\n\u001b[0;32m    741\u001b[0m     variables \u001b[38;5;241m=\u001b[39m _ScatterPlotter\u001b[38;5;241m.\u001b[39mget_semantics(\u001b[38;5;28mlocals\u001b[39m())\n\u001b[1;32m--> 742\u001b[0m     p \u001b[38;5;241m=\u001b[39m _ScatterPlotter(data\u001b[38;5;241m=\u001b[39mdata, variables\u001b[38;5;241m=\u001b[39mvariables, legend\u001b[38;5;241m=\u001b[39mlegend)\n\u001b[0;32m    744\u001b[0m     p\u001b[38;5;241m.\u001b[39mmap_hue(palette\u001b[38;5;241m=\u001b[39mpalette, order\u001b[38;5;241m=\u001b[39mhue_order, norm\u001b[38;5;241m=\u001b[39mhue_norm)\n\u001b[0;32m    745\u001b[0m     p\u001b[38;5;241m.\u001b[39mmap_size(sizes\u001b[38;5;241m=\u001b[39msizes, order\u001b[38;5;241m=\u001b[39msize_order, norm\u001b[38;5;241m=\u001b[39msize_norm)\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\seaborn\\relational.py:538\u001b[0m, in \u001b[0;36m_ScatterPlotter.__init__\u001b[1;34m(self, data, variables, legend)\u001b[0m\n\u001b[0;32m    529\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, variables\u001b[38;5;241m=\u001b[39m{}, legend\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m    530\u001b[0m \n\u001b[0;32m    531\u001b[0m     \u001b[38;5;66;03m# TODO this is messy, we want the mapping to be agnostic about\u001b[39;00m\n\u001b[0;32m    532\u001b[0m     \u001b[38;5;66;03m# the kind of plot to draw, but for the time being we need to set\u001b[39;00m\n\u001b[0;32m    533\u001b[0m     \u001b[38;5;66;03m# this information so the SizeMapping can use it\u001b[39;00m\n\u001b[0;32m    534\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_default_size_range \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m    535\u001b[0m         np\u001b[38;5;241m.\u001b[39mr_[\u001b[38;5;241m.5\u001b[39m, \u001b[38;5;241m2\u001b[39m] \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39msquare(mpl\u001b[38;5;241m.\u001b[39mrcParams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlines.markersize\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m    536\u001b[0m     )\n\u001b[1;32m--> 538\u001b[0m     \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__init__\u001b[39m(data\u001b[38;5;241m=\u001b[39mdata, variables\u001b[38;5;241m=\u001b[39mvariables)\n\u001b[0;32m    540\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlegend \u001b[38;5;241m=\u001b[39m legend\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\seaborn\\_oldcore.py:640\u001b[0m, in \u001b[0;36mVectorPlotter.__init__\u001b[1;34m(self, data, variables)\u001b[0m\n\u001b[0;32m    635\u001b[0m \u001b[38;5;66;03m# var_ordered is relevant only for categorical axis variables, and may\u001b[39;00m\n\u001b[0;32m    636\u001b[0m \u001b[38;5;66;03m# be better handled by an internal axis information object that tracks\u001b[39;00m\n\u001b[0;32m    637\u001b[0m \u001b[38;5;66;03m# such information and is set up by the scale_* methods. The analogous\u001b[39;00m\n\u001b[0;32m    638\u001b[0m \u001b[38;5;66;03m# information for numeric axes would be information about log scales.\u001b[39;00m\n\u001b[0;32m    639\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_var_ordered \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mFalse\u001b[39;00m}  \u001b[38;5;66;03m# alt., used DefaultDict\u001b[39;00m\n\u001b[1;32m--> 640\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39massign_variables(data, variables)\n\u001b[0;32m    642\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m var, \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_semantic_mappings\u001b[38;5;241m.\u001b[39mitems():\n\u001b[0;32m    643\u001b[0m \n\u001b[0;32m    644\u001b[0m     \u001b[38;5;66;03m# Create the mapping function\u001b[39;00m\n\u001b[0;32m    645\u001b[0m     map_func \u001b[38;5;241m=\u001b[39m partial(\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mmap, plotter\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m)\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\seaborn\\_oldcore.py:701\u001b[0m, in \u001b[0;36mVectorPlotter.assign_variables\u001b[1;34m(self, data, variables)\u001b[0m\n\u001b[0;32m    699\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    700\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minput_format \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlong\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m--> 701\u001b[0m     plot_data, variables \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_assign_variables_longform(\n\u001b[0;32m    702\u001b[0m         data, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mvariables,\n\u001b[0;32m    703\u001b[0m     )\n\u001b[0;32m    705\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mplot_data \u001b[38;5;241m=\u001b[39m plot_data\n\u001b[0;32m    706\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvariables \u001b[38;5;241m=\u001b[39m variables\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\seaborn\\_oldcore.py:962\u001b[0m, in \u001b[0;36mVectorPlotter._assign_variables_longform\u001b[1;34m(self, data, **kwargs)\u001b[0m\n\u001b[0;32m    958\u001b[0m         variables[key] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(val, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m    960\u001b[0m \u001b[38;5;66;03m# Construct a tidy plot DataFrame. This will convert a number of\u001b[39;00m\n\u001b[0;32m    961\u001b[0m \u001b[38;5;66;03m# types automatically, aligning on index in case of pandas objects\u001b[39;00m\n\u001b[1;32m--> 962\u001b[0m plot_data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(plot_data)\n\u001b[0;32m    964\u001b[0m \u001b[38;5;66;03m# Reduce the variables dictionary to fields with valid data\u001b[39;00m\n\u001b[0;32m    965\u001b[0m variables \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m    966\u001b[0m     var: name\n\u001b[0;32m    967\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m var, name \u001b[38;5;129;01min\u001b[39;00m variables\u001b[38;5;241m.\u001b[39mitems()\n\u001b[0;32m    968\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m plot_data[var]\u001b[38;5;241m.\u001b[39mnotnull()\u001b[38;5;241m.\u001b[39many()\n\u001b[0;32m    969\u001b[0m }\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\pandas\\core\\frame.py:733\u001b[0m, in \u001b[0;36mDataFrame.__init__\u001b[1;34m(self, data, index, columns, dtype, copy)\u001b[0m\n\u001b[0;32m    727\u001b[0m     mgr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_init_mgr(\n\u001b[0;32m    728\u001b[0m         data, axes\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mindex\u001b[39m\u001b[38;5;124m\"\u001b[39m: index, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcolumns\u001b[39m\u001b[38;5;124m\"\u001b[39m: columns}, dtype\u001b[38;5;241m=\u001b[39mdtype, copy\u001b[38;5;241m=\u001b[39mcopy\n\u001b[0;32m    729\u001b[0m     )\n\u001b[0;32m    731\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data, \u001b[38;5;28mdict\u001b[39m):\n\u001b[0;32m    732\u001b[0m     \u001b[38;5;66;03m# GH#38939 de facto copy defaults to False only in non-dict cases\u001b[39;00m\n\u001b[1;32m--> 733\u001b[0m     mgr \u001b[38;5;241m=\u001b[39m dict_to_mgr(data, index, columns, dtype\u001b[38;5;241m=\u001b[39mdtype, copy\u001b[38;5;241m=\u001b[39mcopy, typ\u001b[38;5;241m=\u001b[39mmanager)\n\u001b[0;32m    734\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data, ma\u001b[38;5;241m.\u001b[39mMaskedArray):\n\u001b[0;32m    735\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mma\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m mrecords\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\pandas\\core\\internals\\construction.py:503\u001b[0m, in \u001b[0;36mdict_to_mgr\u001b[1;34m(data, index, columns, dtype, typ, copy)\u001b[0m\n\u001b[0;32m    499\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    500\u001b[0m         \u001b[38;5;66;03m# dtype check to exclude e.g. range objects, scalars\u001b[39;00m\n\u001b[0;32m    501\u001b[0m         arrays \u001b[38;5;241m=\u001b[39m [x\u001b[38;5;241m.\u001b[39mcopy() \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(x, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdtype\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01melse\u001b[39;00m x \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m arrays]\n\u001b[1;32m--> 503\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m arrays_to_mgr(arrays, columns, index, dtype\u001b[38;5;241m=\u001b[39mdtype, typ\u001b[38;5;241m=\u001b[39mtyp, consolidate\u001b[38;5;241m=\u001b[39mcopy)\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\pandas\\core\\internals\\construction.py:114\u001b[0m, in \u001b[0;36marrays_to_mgr\u001b[1;34m(arrays, columns, index, dtype, verify_integrity, typ, consolidate)\u001b[0m\n\u001b[0;32m    111\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m verify_integrity:\n\u001b[0;32m    112\u001b[0m     \u001b[38;5;66;03m# figure out the index, if necessary\u001b[39;00m\n\u001b[0;32m    113\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m index \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m--> 114\u001b[0m         index \u001b[38;5;241m=\u001b[39m _extract_index(arrays)\n\u001b[0;32m    115\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    116\u001b[0m         index \u001b[38;5;241m=\u001b[39m ensure_index(index)\n",
-      "File \u001b[1;32md:\\ProgramData\\anaconda3\\Lib\\site-packages\\pandas\\core\\internals\\construction.py:664\u001b[0m, in \u001b[0;36m_extract_index\u001b[1;34m(data)\u001b[0m\n\u001b[0;32m    662\u001b[0m         raw_lengths\u001b[38;5;241m.\u001b[39mappend(\u001b[38;5;28mlen\u001b[39m(val))\n\u001b[0;32m    663\u001b[0m     \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(val, np\u001b[38;5;241m.\u001b[39mndarray) \u001b[38;5;129;01mand\u001b[39;00m val\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m--> 664\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPer-column arrays must each be 1-dimensional\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    666\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m indexes \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m raw_lengths:\n\u001b[0;32m    667\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIf using all scalar values, you must pass an index\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
-      "\u001b[1;31mValueError\u001b[0m: Per-column arrays must each be 1-dimensional"
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "['2024-10-04', '2024-10-05', '2024-10-06', '2024-10-07', '2024-10-08', '2024-10-09', '2024-10-10', '2024-10-11']\n",
+      "(10, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "0  2024-10-08  78.172055  81.172055      76.36      76.36  2024-10-07\n",
+      "1  2024-10-09  78.017734  81.017734      75.15      75.15  2024-10-07\n",
+      "2  2024-10-10  78.196563  81.196563      76.72      76.72  2024-10-07\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "5  2024-10-09  75.442758  78.442758      75.15      75.15  2024-10-08\n",
+      "6  2024-10-10  75.684414  78.684414      76.72      76.72  2024-10-08\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "10 2024-10-10  75.439643  78.439643      76.72      76.72  2024-10-09\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "['2024-10-04', '2024-10-05', '2024-10-06', '2024-10-07', '2024-10-08', '2024-10-09', '2024-10-10', '2024-10-11']\n",
+      "(10, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "0  2024-10-08  78.172055  81.172055      76.36      76.36  2024-10-07\n",
+      "1  2024-10-09  78.017734  81.017734      75.15      75.15  2024-10-07\n",
+      "2  2024-10-10  78.196563  81.196563      76.72      76.72  2024-10-07\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "5  2024-10-09  75.442758  78.442758      75.15      75.15  2024-10-08\n",
+      "6  2024-10-10  75.684414  78.684414      76.72      76.72  2024-10-08\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "10 2024-10-10  75.439643  78.439643      76.72      76.72  2024-10-09\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "['2024-10-04', '2024-10-05', '2024-10-06', '2024-10-07', '2024-10-08', '2024-10-09', '2024-10-10', '2024-10-11']\n",
+      "(10, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "0  2024-10-08  78.172055  81.172055      76.36      76.36  2024-10-07\n",
+      "1  2024-10-09  78.017734  81.017734      75.15      75.15  2024-10-07\n",
+      "2  2024-10-10  78.196563  81.196563      76.72      76.72  2024-10-07\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "5  2024-10-09  75.442758  78.442758      75.15      75.15  2024-10-08\n",
+      "6  2024-10-10  75.684414  78.684414      76.72      76.72  2024-10-08\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "10 2024-10-10  75.439643  78.439643      76.72      76.72  2024-10-09\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "['2024-10-04', '2024-10-05', '2024-10-06', '2024-10-07', '2024-10-08', '2024-10-09', '2024-10-10', '2024-10-11']\n",
+      "(10, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "0  2024-10-08  78.172055  81.172055      76.36      76.36  2024-10-07\n",
+      "1  2024-10-09  78.017734  81.017734      75.15      75.15  2024-10-07\n",
+      "2  2024-10-10  78.196563  81.196563      76.72      76.72  2024-10-07\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "5  2024-10-09  75.442758  78.442758      75.15      75.15  2024-10-08\n",
+      "6  2024-10-10  75.684414  78.684414      76.72      76.72  2024-10-08\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "10 2024-10-10  75.439643  78.439643      76.72      76.72  2024-10-09\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "['2024-10-11', '2024-10-12', '2024-10-13', '2024-10-14', '2024-10-15', '2024-10-16', '2024-10-17', '2024-10-18']\n",
+      "(29, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "4  2024-10-14  78.448240  81.448240      74.86      74.86  2024-10-07\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "8  2024-10-14  75.819379  78.819379      74.86      74.86  2024-10-08\n",
+      "9  2024-10-15  75.830953  78.830953      73.34      73.34  2024-10-08\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "12 2024-10-14  75.775363  78.775363      74.86      74.86  2024-10-09\n",
+      "13 2024-10-15  75.869936  78.869936      73.34      73.34  2024-10-09\n",
+      "14 2024-10-16  76.203067  79.203067      73.42      73.42  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "16 2024-10-14  77.326639  80.326639      74.86      74.86  2024-10-10\n",
+      "17 2024-10-15  77.711800  80.711800      73.34      73.34  2024-10-10\n",
+      "18 2024-10-16  78.129062  81.129062      73.42      73.42  2024-10-10\n",
+      "19 2024-10-17  78.237173  81.237173      73.26      73.26  2024-10-10\n",
+      "20 2024-10-14  77.103294  80.103294      74.86      74.86  2024-10-11\n",
+      "21 2024-10-15  77.561999  80.561999      73.34      73.34  2024-10-11\n",
+      "22 2024-10-16  77.827442  80.827442      73.42      73.42  2024-10-11\n",
+      "23 2024-10-17  77.831231  80.831231      73.26      73.26  2024-10-11\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "25 2024-10-15  76.526668  79.526668      73.34      73.34  2024-10-14\n",
+      "['2024-10-11', '2024-10-12', '2024-10-13', '2024-10-14', '2024-10-15', '2024-10-16', '2024-10-17', '2024-10-18']\n",
+      "(29, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "4  2024-10-14  78.448240  81.448240      74.86      74.86  2024-10-07\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "8  2024-10-14  75.819379  78.819379      74.86      74.86  2024-10-08\n",
+      "9  2024-10-15  75.830953  78.830953      73.34      73.34  2024-10-08\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "12 2024-10-14  75.775363  78.775363      74.86      74.86  2024-10-09\n",
+      "13 2024-10-15  75.869936  78.869936      73.34      73.34  2024-10-09\n",
+      "14 2024-10-16  76.203067  79.203067      73.42      73.42  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "16 2024-10-14  77.326639  80.326639      74.86      74.86  2024-10-10\n",
+      "17 2024-10-15  77.711800  80.711800      73.34      73.34  2024-10-10\n",
+      "18 2024-10-16  78.129062  81.129062      73.42      73.42  2024-10-10\n",
+      "19 2024-10-17  78.237173  81.237173      73.26      73.26  2024-10-10\n",
+      "20 2024-10-14  77.103294  80.103294      74.86      74.86  2024-10-11\n",
+      "21 2024-10-15  77.561999  80.561999      73.34      73.34  2024-10-11\n",
+      "22 2024-10-16  77.827442  80.827442      73.42      73.42  2024-10-11\n",
+      "23 2024-10-17  77.831231  80.831231      73.26      73.26  2024-10-11\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "25 2024-10-15  76.526668  79.526668      73.34      73.34  2024-10-14\n",
+      "['2024-10-11', '2024-10-12', '2024-10-13', '2024-10-14', '2024-10-15', '2024-10-16', '2024-10-17', '2024-10-18']\n",
+      "(29, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "4  2024-10-14  78.448240  81.448240      74.86      74.86  2024-10-07\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "8  2024-10-14  75.819379  78.819379      74.86      74.86  2024-10-08\n",
+      "9  2024-10-15  75.830953  78.830953      73.34      73.34  2024-10-08\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "12 2024-10-14  75.775363  78.775363      74.86      74.86  2024-10-09\n",
+      "13 2024-10-15  75.869936  78.869936      73.34      73.34  2024-10-09\n",
+      "14 2024-10-16  76.203067  79.203067      73.42      73.42  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "16 2024-10-14  77.326639  80.326639      74.86      74.86  2024-10-10\n",
+      "17 2024-10-15  77.711800  80.711800      73.34      73.34  2024-10-10\n",
+      "18 2024-10-16  78.129062  81.129062      73.42      73.42  2024-10-10\n",
+      "19 2024-10-17  78.237173  81.237173      73.26      73.26  2024-10-10\n",
+      "20 2024-10-14  77.103294  80.103294      74.86      74.86  2024-10-11\n",
+      "21 2024-10-15  77.561999  80.561999      73.34      73.34  2024-10-11\n",
+      "22 2024-10-16  77.827442  80.827442      73.42      73.42  2024-10-11\n",
+      "23 2024-10-17  77.831231  80.831231      73.26      73.26  2024-10-11\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "25 2024-10-15  76.526668  79.526668      73.34      73.34  2024-10-14\n",
+      "['2024-10-11', '2024-10-12', '2024-10-13', '2024-10-14', '2024-10-15', '2024-10-16', '2024-10-17', '2024-10-18']\n",
+      "(29, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "4  2024-10-14  78.448240  81.448240      74.86      74.86  2024-10-07\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "8  2024-10-14  75.819379  78.819379      74.86      74.86  2024-10-08\n",
+      "9  2024-10-15  75.830953  78.830953      73.34      73.34  2024-10-08\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "12 2024-10-14  75.775363  78.775363      74.86      74.86  2024-10-09\n",
+      "13 2024-10-15  75.869936  78.869936      73.34      73.34  2024-10-09\n",
+      "14 2024-10-16  76.203067  79.203067      73.42      73.42  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "16 2024-10-14  77.326639  80.326639      74.86      74.86  2024-10-10\n",
+      "17 2024-10-15  77.711800  80.711800      73.34      73.34  2024-10-10\n",
+      "18 2024-10-16  78.129062  81.129062      73.42      73.42  2024-10-10\n",
+      "19 2024-10-17  78.237173  81.237173      73.26      73.26  2024-10-10\n",
+      "20 2024-10-14  77.103294  80.103294      74.86      74.86  2024-10-11\n",
+      "21 2024-10-15  77.561999  80.561999      73.34      73.34  2024-10-11\n",
+      "22 2024-10-16  77.827442  80.827442      73.42      73.42  2024-10-11\n",
+      "23 2024-10-17  77.831231  80.831231      73.26      73.26  2024-10-11\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "25 2024-10-15  76.526668  79.526668      73.34      73.34  2024-10-14\n",
+      "['2024-10-11', '2024-10-12', '2024-10-13', '2024-10-14', '2024-10-15', '2024-10-16', '2024-10-17', '2024-10-18']\n",
+      "(29, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "3  2024-10-11  78.244970  81.244970      78.04      78.04  2024-10-07\n",
+      "4  2024-10-14  78.448240  81.448240      74.86      74.86  2024-10-07\n",
+      "7  2024-10-11  75.675482  78.675482      78.04      78.04  2024-10-08\n",
+      "8  2024-10-14  75.819379  78.819379      74.86      74.86  2024-10-08\n",
+      "9  2024-10-15  75.830953  78.830953      73.34      73.34  2024-10-08\n",
+      "11 2024-10-11  75.214194  78.214194      78.04      78.04  2024-10-09\n",
+      "12 2024-10-14  75.775363  78.775363      74.86      74.86  2024-10-09\n",
+      "13 2024-10-15  75.869936  78.869936      73.34      73.34  2024-10-09\n",
+      "14 2024-10-16  76.203067  79.203067      73.42      73.42  2024-10-09\n",
+      "15 2024-10-11  77.558740  80.558740      78.04      78.04  2024-10-10\n",
+      "16 2024-10-14  77.326639  80.326639      74.86      74.86  2024-10-10\n",
+      "17 2024-10-15  77.711800  80.711800      73.34      73.34  2024-10-10\n",
+      "18 2024-10-16  78.129062  81.129062      73.42      73.42  2024-10-10\n",
+      "19 2024-10-17  78.237173  81.237173      73.26      73.26  2024-10-10\n",
+      "20 2024-10-14  77.103294  80.103294      74.86      74.86  2024-10-11\n",
+      "21 2024-10-15  77.561999  80.561999      73.34      73.34  2024-10-11\n",
+      "22 2024-10-16  77.827442  80.827442      73.42      73.42  2024-10-11\n",
+      "23 2024-10-17  77.831231  80.831231      73.26      73.26  2024-10-11\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "25 2024-10-15  76.526668  79.526668      73.34      73.34  2024-10-14\n",
+      "['2024-10-18', '2024-10-19', '2024-10-20', '2024-10-21', '2024-10-22', '2024-10-23', '2024-10-24', '2024-10-25']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "28 2024-10-18  77.135056  80.135056      72.50      72.50  2024-10-14\n",
+      "29 2024-10-21  77.530344  80.530344      72.80      72.80  2024-10-14\n",
+      "32 2024-10-18  73.482573  76.482573      72.50      72.50  2024-10-15\n",
+      "33 2024-10-21  73.144924  76.144924      72.80      72.80  2024-10-15\n",
+      "34 2024-10-22  73.877058  76.877058      73.57      73.57  2024-10-15\n",
+      "36 2024-10-18  72.624883  75.624883      72.50      72.50  2024-10-16\n",
+      "37 2024-10-21  72.775239  75.775239      72.80      72.80  2024-10-16\n",
+      "38 2024-10-22  72.379754  75.379754      73.57      73.57  2024-10-16\n",
+      "39 2024-10-23  72.447762  75.447762      74.42      74.42  2024-10-16\n",
+      "40 2024-10-18  71.980603  74.980603      72.50      72.50  2024-10-17\n",
+      "41 2024-10-21  71.915474  74.915474      72.80      72.80  2024-10-17\n",
+      "42 2024-10-22  71.445161  74.445161      73.57      73.57  2024-10-17\n",
+      "43 2024-10-23  70.993233  73.993233      74.42      74.42  2024-10-17\n",
+      "44 2024-10-24  71.050194  74.050194      74.00      74.00  2024-10-17\n",
+      "45 2024-10-21  70.300023  73.300023      72.80      72.80  2024-10-18\n",
+      "46 2024-10-22  70.269711  73.269711      73.57      73.57  2024-10-18\n",
+      "47 2024-10-23  69.892138  72.892138      74.42      74.42  2024-10-18\n",
+      "48 2024-10-24  69.531043  72.531043      74.00      74.00  2024-10-18\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "['2024-10-18', '2024-10-19', '2024-10-20', '2024-10-21', '2024-10-22', '2024-10-23', '2024-10-24', '2024-10-25']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "28 2024-10-18  77.135056  80.135056      72.50      72.50  2024-10-14\n",
+      "29 2024-10-21  77.530344  80.530344      72.80      72.80  2024-10-14\n",
+      "32 2024-10-18  73.482573  76.482573      72.50      72.50  2024-10-15\n",
+      "33 2024-10-21  73.144924  76.144924      72.80      72.80  2024-10-15\n",
+      "34 2024-10-22  73.877058  76.877058      73.57      73.57  2024-10-15\n",
+      "36 2024-10-18  72.624883  75.624883      72.50      72.50  2024-10-16\n",
+      "37 2024-10-21  72.775239  75.775239      72.80      72.80  2024-10-16\n",
+      "38 2024-10-22  72.379754  75.379754      73.57      73.57  2024-10-16\n",
+      "39 2024-10-23  72.447762  75.447762      74.42      74.42  2024-10-16\n",
+      "40 2024-10-18  71.980603  74.980603      72.50      72.50  2024-10-17\n",
+      "41 2024-10-21  71.915474  74.915474      72.80      72.80  2024-10-17\n",
+      "42 2024-10-22  71.445161  74.445161      73.57      73.57  2024-10-17\n",
+      "43 2024-10-23  70.993233  73.993233      74.42      74.42  2024-10-17\n",
+      "44 2024-10-24  71.050194  74.050194      74.00      74.00  2024-10-17\n",
+      "45 2024-10-21  70.300023  73.300023      72.80      72.80  2024-10-18\n",
+      "46 2024-10-22  70.269711  73.269711      73.57      73.57  2024-10-18\n",
+      "47 2024-10-23  69.892138  72.892138      74.42      74.42  2024-10-18\n",
+      "48 2024-10-24  69.531043  72.531043      74.00      74.00  2024-10-18\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "['2024-10-18', '2024-10-19', '2024-10-20', '2024-10-21', '2024-10-22', '2024-10-23', '2024-10-24', '2024-10-25']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "28 2024-10-18  77.135056  80.135056      72.50      72.50  2024-10-14\n",
+      "29 2024-10-21  77.530344  80.530344      72.80      72.80  2024-10-14\n",
+      "32 2024-10-18  73.482573  76.482573      72.50      72.50  2024-10-15\n",
+      "33 2024-10-21  73.144924  76.144924      72.80      72.80  2024-10-15\n",
+      "34 2024-10-22  73.877058  76.877058      73.57      73.57  2024-10-15\n",
+      "36 2024-10-18  72.624883  75.624883      72.50      72.50  2024-10-16\n",
+      "37 2024-10-21  72.775239  75.775239      72.80      72.80  2024-10-16\n",
+      "38 2024-10-22  72.379754  75.379754      73.57      73.57  2024-10-16\n",
+      "39 2024-10-23  72.447762  75.447762      74.42      74.42  2024-10-16\n",
+      "40 2024-10-18  71.980603  74.980603      72.50      72.50  2024-10-17\n",
+      "41 2024-10-21  71.915474  74.915474      72.80      72.80  2024-10-17\n",
+      "42 2024-10-22  71.445161  74.445161      73.57      73.57  2024-10-17\n",
+      "43 2024-10-23  70.993233  73.993233      74.42      74.42  2024-10-17\n",
+      "44 2024-10-24  71.050194  74.050194      74.00      74.00  2024-10-17\n",
+      "45 2024-10-21  70.300023  73.300023      72.80      72.80  2024-10-18\n",
+      "46 2024-10-22  70.269711  73.269711      73.57      73.57  2024-10-18\n",
+      "47 2024-10-23  69.892138  72.892138      74.42      74.42  2024-10-18\n",
+      "48 2024-10-24  69.531043  72.531043      74.00      74.00  2024-10-18\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "['2024-10-18', '2024-10-19', '2024-10-20', '2024-10-21', '2024-10-22', '2024-10-23', '2024-10-24', '2024-10-25']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "28 2024-10-18  77.135056  80.135056      72.50      72.50  2024-10-14\n",
+      "29 2024-10-21  77.530344  80.530344      72.80      72.80  2024-10-14\n",
+      "32 2024-10-18  73.482573  76.482573      72.50      72.50  2024-10-15\n",
+      "33 2024-10-21  73.144924  76.144924      72.80      72.80  2024-10-15\n",
+      "34 2024-10-22  73.877058  76.877058      73.57      73.57  2024-10-15\n",
+      "36 2024-10-18  72.624883  75.624883      72.50      72.50  2024-10-16\n",
+      "37 2024-10-21  72.775239  75.775239      72.80      72.80  2024-10-16\n",
+      "38 2024-10-22  72.379754  75.379754      73.57      73.57  2024-10-16\n",
+      "39 2024-10-23  72.447762  75.447762      74.42      74.42  2024-10-16\n",
+      "40 2024-10-18  71.980603  74.980603      72.50      72.50  2024-10-17\n",
+      "41 2024-10-21  71.915474  74.915474      72.80      72.80  2024-10-17\n",
+      "42 2024-10-22  71.445161  74.445161      73.57      73.57  2024-10-17\n",
+      "43 2024-10-23  70.993233  73.993233      74.42      74.42  2024-10-17\n",
+      "44 2024-10-24  71.050194  74.050194      74.00      74.00  2024-10-17\n",
+      "45 2024-10-21  70.300023  73.300023      72.80      72.80  2024-10-18\n",
+      "46 2024-10-22  70.269711  73.269711      73.57      73.57  2024-10-18\n",
+      "47 2024-10-23  69.892138  72.892138      74.42      74.42  2024-10-18\n",
+      "48 2024-10-24  69.531043  72.531043      74.00      74.00  2024-10-18\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "['2024-10-18', '2024-10-19', '2024-10-20', '2024-10-21', '2024-10-22', '2024-10-23', '2024-10-24', '2024-10-25']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "24 2024-10-18  78.024951  81.024951      72.50      72.50  2024-10-11\n",
+      "28 2024-10-18  77.135056  80.135056      72.50      72.50  2024-10-14\n",
+      "29 2024-10-21  77.530344  80.530344      72.80      72.80  2024-10-14\n",
+      "32 2024-10-18  73.482573  76.482573      72.50      72.50  2024-10-15\n",
+      "33 2024-10-21  73.144924  76.144924      72.80      72.80  2024-10-15\n",
+      "34 2024-10-22  73.877058  76.877058      73.57      73.57  2024-10-15\n",
+      "36 2024-10-18  72.624883  75.624883      72.50      72.50  2024-10-16\n",
+      "37 2024-10-21  72.775239  75.775239      72.80      72.80  2024-10-16\n",
+      "38 2024-10-22  72.379754  75.379754      73.57      73.57  2024-10-16\n",
+      "39 2024-10-23  72.447762  75.447762      74.42      74.42  2024-10-16\n",
+      "40 2024-10-18  71.980603  74.980603      72.50      72.50  2024-10-17\n",
+      "41 2024-10-21  71.915474  74.915474      72.80      72.80  2024-10-17\n",
+      "42 2024-10-22  71.445161  74.445161      73.57      73.57  2024-10-17\n",
+      "43 2024-10-23  70.993233  73.993233      74.42      74.42  2024-10-17\n",
+      "44 2024-10-24  71.050194  74.050194      74.00      74.00  2024-10-17\n",
+      "45 2024-10-21  70.300023  73.300023      72.80      72.80  2024-10-18\n",
+      "46 2024-10-22  70.269711  73.269711      73.57      73.57  2024-10-18\n",
+      "47 2024-10-23  69.892138  72.892138      74.42      74.42  2024-10-18\n",
+      "48 2024-10-24  69.531043  72.531043      74.00      74.00  2024-10-18\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "['2024-10-25', '2024-10-26', '2024-10-27', '2024-10-28', '2024-10-29', '2024-10-30', '2024-10-31', '2024-11-01']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "53 2024-10-25  71.284130  74.284130      74.17      74.17  2024-10-21\n",
+      "54 2024-10-28  71.130199  74.130199      70.82      70.82  2024-10-21\n",
+      "57 2024-10-25  72.849289  75.849289      74.17      74.17  2024-10-22\n",
+      "58 2024-10-28  72.846420  75.846420      70.82      70.82  2024-10-22\n",
+      "59 2024-10-29  73.135881  76.135881      70.28      70.28  2024-10-22\n",
+      "61 2024-10-25  72.576628  75.576628      74.17      74.17  2024-10-23\n",
+      "62 2024-10-28  72.523148  75.523148      70.82      70.82  2024-10-23\n",
+      "63 2024-10-29  72.996282  75.996282      70.28      70.28  2024-10-23\n",
+      "64 2024-10-30  73.612846  76.612846      70.71      70.71  2024-10-23\n",
+      "65 2024-10-25  72.725321  75.725321      74.17      74.17  2024-10-24\n",
+      "66 2024-10-28  73.117595  76.117595      70.82      70.82  2024-10-24\n",
+      "67 2024-10-29  73.842996  76.842996      70.28      70.28  2024-10-24\n",
+      "68 2024-10-30  73.879968  76.879968      70.71      70.71  2024-10-24\n",
+      "69 2024-10-31  73.636574  76.636574      71.82      71.82  2024-10-24\n",
+      "70 2024-10-28  74.114556  77.114556      70.82      70.82  2024-10-25\n",
+      "71 2024-10-29  74.218034  77.218034      70.28      70.28  2024-10-25\n",
+      "72 2024-10-30  74.565620  77.565620      70.71      70.71  2024-10-25\n",
+      "73 2024-10-31  73.995926  76.995926      71.82      71.82  2024-10-25\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "['2024-10-25', '2024-10-26', '2024-10-27', '2024-10-28', '2024-10-29', '2024-10-30', '2024-10-31', '2024-11-01']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "53 2024-10-25  71.284130  74.284130      74.17      74.17  2024-10-21\n",
+      "54 2024-10-28  71.130199  74.130199      70.82      70.82  2024-10-21\n",
+      "57 2024-10-25  72.849289  75.849289      74.17      74.17  2024-10-22\n",
+      "58 2024-10-28  72.846420  75.846420      70.82      70.82  2024-10-22\n",
+      "59 2024-10-29  73.135881  76.135881      70.28      70.28  2024-10-22\n",
+      "61 2024-10-25  72.576628  75.576628      74.17      74.17  2024-10-23\n",
+      "62 2024-10-28  72.523148  75.523148      70.82      70.82  2024-10-23\n",
+      "63 2024-10-29  72.996282  75.996282      70.28      70.28  2024-10-23\n",
+      "64 2024-10-30  73.612846  76.612846      70.71      70.71  2024-10-23\n",
+      "65 2024-10-25  72.725321  75.725321      74.17      74.17  2024-10-24\n",
+      "66 2024-10-28  73.117595  76.117595      70.82      70.82  2024-10-24\n",
+      "67 2024-10-29  73.842996  76.842996      70.28      70.28  2024-10-24\n",
+      "68 2024-10-30  73.879968  76.879968      70.71      70.71  2024-10-24\n",
+      "69 2024-10-31  73.636574  76.636574      71.82      71.82  2024-10-24\n",
+      "70 2024-10-28  74.114556  77.114556      70.82      70.82  2024-10-25\n",
+      "71 2024-10-29  74.218034  77.218034      70.28      70.28  2024-10-25\n",
+      "72 2024-10-30  74.565620  77.565620      70.71      70.71  2024-10-25\n",
+      "73 2024-10-31  73.995926  76.995926      71.82      71.82  2024-10-25\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "['2024-10-25', '2024-10-26', '2024-10-27', '2024-10-28', '2024-10-29', '2024-10-30', '2024-10-31', '2024-11-01']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "53 2024-10-25  71.284130  74.284130      74.17      74.17  2024-10-21\n",
+      "54 2024-10-28  71.130199  74.130199      70.82      70.82  2024-10-21\n",
+      "57 2024-10-25  72.849289  75.849289      74.17      74.17  2024-10-22\n",
+      "58 2024-10-28  72.846420  75.846420      70.82      70.82  2024-10-22\n",
+      "59 2024-10-29  73.135881  76.135881      70.28      70.28  2024-10-22\n",
+      "61 2024-10-25  72.576628  75.576628      74.17      74.17  2024-10-23\n",
+      "62 2024-10-28  72.523148  75.523148      70.82      70.82  2024-10-23\n",
+      "63 2024-10-29  72.996282  75.996282      70.28      70.28  2024-10-23\n",
+      "64 2024-10-30  73.612846  76.612846      70.71      70.71  2024-10-23\n",
+      "65 2024-10-25  72.725321  75.725321      74.17      74.17  2024-10-24\n",
+      "66 2024-10-28  73.117595  76.117595      70.82      70.82  2024-10-24\n",
+      "67 2024-10-29  73.842996  76.842996      70.28      70.28  2024-10-24\n",
+      "68 2024-10-30  73.879968  76.879968      70.71      70.71  2024-10-24\n",
+      "69 2024-10-31  73.636574  76.636574      71.82      71.82  2024-10-24\n",
+      "70 2024-10-28  74.114556  77.114556      70.82      70.82  2024-10-25\n",
+      "71 2024-10-29  74.218034  77.218034      70.28      70.28  2024-10-25\n",
+      "72 2024-10-30  74.565620  77.565620      70.71      70.71  2024-10-25\n",
+      "73 2024-10-31  73.995926  76.995926      71.82      71.82  2024-10-25\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "['2024-10-25', '2024-10-26', '2024-10-27', '2024-10-28', '2024-10-29', '2024-10-30', '2024-10-31', '2024-11-01']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "53 2024-10-25  71.284130  74.284130      74.17      74.17  2024-10-21\n",
+      "54 2024-10-28  71.130199  74.130199      70.82      70.82  2024-10-21\n",
+      "57 2024-10-25  72.849289  75.849289      74.17      74.17  2024-10-22\n",
+      "58 2024-10-28  72.846420  75.846420      70.82      70.82  2024-10-22\n",
+      "59 2024-10-29  73.135881  76.135881      70.28      70.28  2024-10-22\n",
+      "61 2024-10-25  72.576628  75.576628      74.17      74.17  2024-10-23\n",
+      "62 2024-10-28  72.523148  75.523148      70.82      70.82  2024-10-23\n",
+      "63 2024-10-29  72.996282  75.996282      70.28      70.28  2024-10-23\n",
+      "64 2024-10-30  73.612846  76.612846      70.71      70.71  2024-10-23\n",
+      "65 2024-10-25  72.725321  75.725321      74.17      74.17  2024-10-24\n",
+      "66 2024-10-28  73.117595  76.117595      70.82      70.82  2024-10-24\n",
+      "67 2024-10-29  73.842996  76.842996      70.28      70.28  2024-10-24\n",
+      "68 2024-10-30  73.879968  76.879968      70.71      70.71  2024-10-24\n",
+      "69 2024-10-31  73.636574  76.636574      71.82      71.82  2024-10-24\n",
+      "70 2024-10-28  74.114556  77.114556      70.82      70.82  2024-10-25\n",
+      "71 2024-10-29  74.218034  77.218034      70.28      70.28  2024-10-25\n",
+      "72 2024-10-30  74.565620  77.565620      70.71      70.71  2024-10-25\n",
+      "73 2024-10-31  73.995926  76.995926      71.82      71.82  2024-10-25\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "['2024-10-25', '2024-10-26', '2024-10-27', '2024-10-28', '2024-10-29', '2024-10-30', '2024-10-31', '2024-11-01']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "49 2024-10-25  69.305193  72.305193      74.17      74.17  2024-10-18\n",
+      "53 2024-10-25  71.284130  74.284130      74.17      74.17  2024-10-21\n",
+      "54 2024-10-28  71.130199  74.130199      70.82      70.82  2024-10-21\n",
+      "57 2024-10-25  72.849289  75.849289      74.17      74.17  2024-10-22\n",
+      "58 2024-10-28  72.846420  75.846420      70.82      70.82  2024-10-22\n",
+      "59 2024-10-29  73.135881  76.135881      70.28      70.28  2024-10-22\n",
+      "61 2024-10-25  72.576628  75.576628      74.17      74.17  2024-10-23\n",
+      "62 2024-10-28  72.523148  75.523148      70.82      70.82  2024-10-23\n",
+      "63 2024-10-29  72.996282  75.996282      70.28      70.28  2024-10-23\n",
+      "64 2024-10-30  73.612846  76.612846      70.71      70.71  2024-10-23\n",
+      "65 2024-10-25  72.725321  75.725321      74.17      74.17  2024-10-24\n",
+      "66 2024-10-28  73.117595  76.117595      70.82      70.82  2024-10-24\n",
+      "67 2024-10-29  73.842996  76.842996      70.28      70.28  2024-10-24\n",
+      "68 2024-10-30  73.879968  76.879968      70.71      70.71  2024-10-24\n",
+      "69 2024-10-31  73.636574  76.636574      71.82      71.82  2024-10-24\n",
+      "70 2024-10-28  74.114556  77.114556      70.82      70.82  2024-10-25\n",
+      "71 2024-10-29  74.218034  77.218034      70.28      70.28  2024-10-25\n",
+      "72 2024-10-30  74.565620  77.565620      70.71      70.71  2024-10-25\n",
+      "73 2024-10-31  73.995926  76.995926      71.82      71.82  2024-10-25\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "['2024-11-01', '2024-11-02', '2024-11-03', '2024-11-04', '2024-11-05', '2024-11-06', '2024-11-07', '2024-11-08']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "78 2024-11-01  71.585668  74.585668      72.89      72.89  2024-10-28\n",
+      "79 2024-11-04  72.056366  75.056366      73.88      73.88  2024-10-28\n",
+      "82 2024-11-01  71.468451  74.468451      72.89      72.89  2024-10-29\n",
+      "83 2024-11-04  71.871874  74.871874      73.88      73.88  2024-10-29\n",
+      "84 2024-11-05  72.078893  75.078893      73.52      73.52  2024-10-29\n",
+      "86 2024-11-01  72.094280  75.094280      72.89      72.89  2024-10-30\n",
+      "87 2024-11-04  72.038187  75.038187      73.88      73.88  2024-10-30\n",
+      "88 2024-11-05  72.291321  75.291321      73.52      73.52  2024-10-30\n",
+      "89 2024-11-06  72.141546  75.141546      73.34      73.34  2024-10-30\n",
+      "90 2024-11-01  71.938575  74.938575      72.89      72.89  2024-10-31\n",
+      "91 2024-11-04  72.103529  75.103529      73.88      73.88  2024-10-31\n",
+      "92 2024-11-05  72.012638  75.012638      73.52      73.52  2024-10-31\n",
+      "93 2024-11-06  71.676658  74.676658      73.34      73.34  2024-10-31\n",
+      "94 2024-11-07  72.012166  75.012166      74.02      74.02  2024-10-31\n",
+      "95 2024-11-04  71.952961  74.952961      73.88      73.88  2024-11-01\n",
+      "96 2024-11-05  72.000069  75.000069      73.52      73.52  2024-11-01\n",
+      "97 2024-11-06  71.373926  74.373926      73.34      73.34  2024-11-01\n",
+      "98 2024-11-07  71.456712  74.456712      74.02      74.02  2024-11-01\n",
+      "99 2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "['2024-11-01', '2024-11-02', '2024-11-03', '2024-11-04', '2024-11-05', '2024-11-06', '2024-11-07', '2024-11-08']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "78 2024-11-01  71.585668  74.585668      72.89      72.89  2024-10-28\n",
+      "79 2024-11-04  72.056366  75.056366      73.88      73.88  2024-10-28\n",
+      "82 2024-11-01  71.468451  74.468451      72.89      72.89  2024-10-29\n",
+      "83 2024-11-04  71.871874  74.871874      73.88      73.88  2024-10-29\n",
+      "84 2024-11-05  72.078893  75.078893      73.52      73.52  2024-10-29\n",
+      "86 2024-11-01  72.094280  75.094280      72.89      72.89  2024-10-30\n",
+      "87 2024-11-04  72.038187  75.038187      73.88      73.88  2024-10-30\n",
+      "88 2024-11-05  72.291321  75.291321      73.52      73.52  2024-10-30\n",
+      "89 2024-11-06  72.141546  75.141546      73.34      73.34  2024-10-30\n",
+      "90 2024-11-01  71.938575  74.938575      72.89      72.89  2024-10-31\n",
+      "91 2024-11-04  72.103529  75.103529      73.88      73.88  2024-10-31\n",
+      "92 2024-11-05  72.012638  75.012638      73.52      73.52  2024-10-31\n",
+      "93 2024-11-06  71.676658  74.676658      73.34      73.34  2024-10-31\n",
+      "94 2024-11-07  72.012166  75.012166      74.02      74.02  2024-10-31\n",
+      "95 2024-11-04  71.952961  74.952961      73.88      73.88  2024-11-01\n",
+      "96 2024-11-05  72.000069  75.000069      73.52      73.52  2024-11-01\n",
+      "97 2024-11-06  71.373926  74.373926      73.34      73.34  2024-11-01\n",
+      "98 2024-11-07  71.456712  74.456712      74.02      74.02  2024-11-01\n",
+      "99 2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "['2024-11-01', '2024-11-02', '2024-11-03', '2024-11-04', '2024-11-05', '2024-11-06', '2024-11-07', '2024-11-08']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "78 2024-11-01  71.585668  74.585668      72.89      72.89  2024-10-28\n",
+      "79 2024-11-04  72.056366  75.056366      73.88      73.88  2024-10-28\n",
+      "82 2024-11-01  71.468451  74.468451      72.89      72.89  2024-10-29\n",
+      "83 2024-11-04  71.871874  74.871874      73.88      73.88  2024-10-29\n",
+      "84 2024-11-05  72.078893  75.078893      73.52      73.52  2024-10-29\n",
+      "86 2024-11-01  72.094280  75.094280      72.89      72.89  2024-10-30\n",
+      "87 2024-11-04  72.038187  75.038187      73.88      73.88  2024-10-30\n",
+      "88 2024-11-05  72.291321  75.291321      73.52      73.52  2024-10-30\n",
+      "89 2024-11-06  72.141546  75.141546      73.34      73.34  2024-10-30\n",
+      "90 2024-11-01  71.938575  74.938575      72.89      72.89  2024-10-31\n",
+      "91 2024-11-04  72.103529  75.103529      73.88      73.88  2024-10-31\n",
+      "92 2024-11-05  72.012638  75.012638      73.52      73.52  2024-10-31\n",
+      "93 2024-11-06  71.676658  74.676658      73.34      73.34  2024-10-31\n",
+      "94 2024-11-07  72.012166  75.012166      74.02      74.02  2024-10-31\n",
+      "95 2024-11-04  71.952961  74.952961      73.88      73.88  2024-11-01\n",
+      "96 2024-11-05  72.000069  75.000069      73.52      73.52  2024-11-01\n",
+      "97 2024-11-06  71.373926  74.373926      73.34      73.34  2024-11-01\n",
+      "98 2024-11-07  71.456712  74.456712      74.02      74.02  2024-11-01\n",
+      "99 2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "['2024-11-01', '2024-11-02', '2024-11-03', '2024-11-04', '2024-11-05', '2024-11-06', '2024-11-07', '2024-11-08']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "78 2024-11-01  71.585668  74.585668      72.89      72.89  2024-10-28\n",
+      "79 2024-11-04  72.056366  75.056366      73.88      73.88  2024-10-28\n",
+      "82 2024-11-01  71.468451  74.468451      72.89      72.89  2024-10-29\n",
+      "83 2024-11-04  71.871874  74.871874      73.88      73.88  2024-10-29\n",
+      "84 2024-11-05  72.078893  75.078893      73.52      73.52  2024-10-29\n",
+      "86 2024-11-01  72.094280  75.094280      72.89      72.89  2024-10-30\n",
+      "87 2024-11-04  72.038187  75.038187      73.88      73.88  2024-10-30\n",
+      "88 2024-11-05  72.291321  75.291321      73.52      73.52  2024-10-30\n",
+      "89 2024-11-06  72.141546  75.141546      73.34      73.34  2024-10-30\n",
+      "90 2024-11-01  71.938575  74.938575      72.89      72.89  2024-10-31\n",
+      "91 2024-11-04  72.103529  75.103529      73.88      73.88  2024-10-31\n",
+      "92 2024-11-05  72.012638  75.012638      73.52      73.52  2024-10-31\n",
+      "93 2024-11-06  71.676658  74.676658      73.34      73.34  2024-10-31\n",
+      "94 2024-11-07  72.012166  75.012166      74.02      74.02  2024-10-31\n",
+      "95 2024-11-04  71.952961  74.952961      73.88      73.88  2024-11-01\n",
+      "96 2024-11-05  72.000069  75.000069      73.52      73.52  2024-11-01\n",
+      "97 2024-11-06  71.373926  74.373926      73.34      73.34  2024-11-01\n",
+      "98 2024-11-07  71.456712  74.456712      74.02      74.02  2024-11-01\n",
+      "99 2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "['2024-11-01', '2024-11-02', '2024-11-03', '2024-11-04', '2024-11-05', '2024-11-06', '2024-11-07', '2024-11-08']\n",
+      "(30, 6)\n",
+      "           ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "74 2024-11-01  73.982739  76.982739      72.89      72.89  2024-10-25\n",
+      "78 2024-11-01  71.585668  74.585668      72.89      72.89  2024-10-28\n",
+      "79 2024-11-04  72.056366  75.056366      73.88      73.88  2024-10-28\n",
+      "82 2024-11-01  71.468451  74.468451      72.89      72.89  2024-10-29\n",
+      "83 2024-11-04  71.871874  74.871874      73.88      73.88  2024-10-29\n",
+      "84 2024-11-05  72.078893  75.078893      73.52      73.52  2024-10-29\n",
+      "86 2024-11-01  72.094280  75.094280      72.89      72.89  2024-10-30\n",
+      "87 2024-11-04  72.038187  75.038187      73.88      73.88  2024-10-30\n",
+      "88 2024-11-05  72.291321  75.291321      73.52      73.52  2024-10-30\n",
+      "89 2024-11-06  72.141546  75.141546      73.34      73.34  2024-10-30\n",
+      "90 2024-11-01  71.938575  74.938575      72.89      72.89  2024-10-31\n",
+      "91 2024-11-04  72.103529  75.103529      73.88      73.88  2024-10-31\n",
+      "92 2024-11-05  72.012638  75.012638      73.52      73.52  2024-10-31\n",
+      "93 2024-11-06  71.676658  74.676658      73.34      73.34  2024-10-31\n",
+      "94 2024-11-07  72.012166  75.012166      74.02      74.02  2024-10-31\n",
+      "95 2024-11-04  71.952961  74.952961      73.88      73.88  2024-11-01\n",
+      "96 2024-11-05  72.000069  75.000069      73.52      73.52  2024-11-01\n",
+      "97 2024-11-06  71.373926  74.373926      73.34      73.34  2024-11-01\n",
+      "98 2024-11-07  71.456712  74.456712      74.02      74.02  2024-11-01\n",
+      "99 2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "['2024-11-08', '2024-11-09', '2024-11-10', '2024-11-11', '2024-11-12', '2024-11-13', '2024-11-14', '2024-11-15']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "99  2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "103 2024-11-08  74.519317  77.519317      73.13      73.13  2024-11-04\n",
+      "104 2024-11-11  74.569906  77.569906      71.57      71.57  2024-11-04\n",
+      "107 2024-11-08  74.694136  77.694136      73.13      73.13  2024-11-05\n",
+      "108 2024-11-11  74.762773  77.762773      71.57      71.57  2024-11-05\n",
+      "109 2024-11-12  74.566135  77.566135      71.55      71.55  2024-11-05\n",
+      "111 2024-11-08  73.830986  76.830986      73.13      73.13  2024-11-06\n",
+      "112 2024-11-11  73.992468  76.992468      71.57      71.57  2024-11-06\n",
+      "113 2024-11-12  73.151260  76.151260      71.55      71.55  2024-11-06\n",
+      "114 2024-11-13  72.774085  75.774085      70.72      70.72  2024-11-06\n",
+      "115 2024-11-08  73.928146  76.928146      73.13      73.13  2024-11-07\n",
+      "116 2024-11-11  73.889942  76.889942      71.57      71.57  2024-11-07\n",
+      "117 2024-11-12  74.026519  77.026519      71.55      71.55  2024-11-07\n",
+      "118 2024-11-13  73.767944  76.767944      70.72      70.72  2024-11-07\n",
+      "119 2024-11-14  73.642370  76.642370      71.79      71.79  2024-11-07\n",
+      "120 2024-11-11  72.042299  75.042299      71.57      71.57  2024-11-08\n",
+      "121 2024-11-12  72.238258  75.238258      71.55      71.55  2024-11-08\n",
+      "122 2024-11-13  71.867976  74.867976      70.72      70.72  2024-11-08\n",
+      "123 2024-11-14  71.615019  74.615019      71.79      71.79  2024-11-08\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "['2024-11-08', '2024-11-09', '2024-11-10', '2024-11-11', '2024-11-12', '2024-11-13', '2024-11-14', '2024-11-15']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "99  2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "103 2024-11-08  74.519317  77.519317      73.13      73.13  2024-11-04\n",
+      "104 2024-11-11  74.569906  77.569906      71.57      71.57  2024-11-04\n",
+      "107 2024-11-08  74.694136  77.694136      73.13      73.13  2024-11-05\n",
+      "108 2024-11-11  74.762773  77.762773      71.57      71.57  2024-11-05\n",
+      "109 2024-11-12  74.566135  77.566135      71.55      71.55  2024-11-05\n",
+      "111 2024-11-08  73.830986  76.830986      73.13      73.13  2024-11-06\n",
+      "112 2024-11-11  73.992468  76.992468      71.57      71.57  2024-11-06\n",
+      "113 2024-11-12  73.151260  76.151260      71.55      71.55  2024-11-06\n",
+      "114 2024-11-13  72.774085  75.774085      70.72      70.72  2024-11-06\n",
+      "115 2024-11-08  73.928146  76.928146      73.13      73.13  2024-11-07\n",
+      "116 2024-11-11  73.889942  76.889942      71.57      71.57  2024-11-07\n",
+      "117 2024-11-12  74.026519  77.026519      71.55      71.55  2024-11-07\n",
+      "118 2024-11-13  73.767944  76.767944      70.72      70.72  2024-11-07\n",
+      "119 2024-11-14  73.642370  76.642370      71.79      71.79  2024-11-07\n",
+      "120 2024-11-11  72.042299  75.042299      71.57      71.57  2024-11-08\n",
+      "121 2024-11-12  72.238258  75.238258      71.55      71.55  2024-11-08\n",
+      "122 2024-11-13  71.867976  74.867976      70.72      70.72  2024-11-08\n",
+      "123 2024-11-14  71.615019  74.615019      71.79      71.79  2024-11-08\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "['2024-11-08', '2024-11-09', '2024-11-10', '2024-11-11', '2024-11-12', '2024-11-13', '2024-11-14', '2024-11-15']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "99  2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "103 2024-11-08  74.519317  77.519317      73.13      73.13  2024-11-04\n",
+      "104 2024-11-11  74.569906  77.569906      71.57      71.57  2024-11-04\n",
+      "107 2024-11-08  74.694136  77.694136      73.13      73.13  2024-11-05\n",
+      "108 2024-11-11  74.762773  77.762773      71.57      71.57  2024-11-05\n",
+      "109 2024-11-12  74.566135  77.566135      71.55      71.55  2024-11-05\n",
+      "111 2024-11-08  73.830986  76.830986      73.13      73.13  2024-11-06\n",
+      "112 2024-11-11  73.992468  76.992468      71.57      71.57  2024-11-06\n",
+      "113 2024-11-12  73.151260  76.151260      71.55      71.55  2024-11-06\n",
+      "114 2024-11-13  72.774085  75.774085      70.72      70.72  2024-11-06\n",
+      "115 2024-11-08  73.928146  76.928146      73.13      73.13  2024-11-07\n",
+      "116 2024-11-11  73.889942  76.889942      71.57      71.57  2024-11-07\n",
+      "117 2024-11-12  74.026519  77.026519      71.55      71.55  2024-11-07\n",
+      "118 2024-11-13  73.767944  76.767944      70.72      70.72  2024-11-07\n",
+      "119 2024-11-14  73.642370  76.642370      71.79      71.79  2024-11-07\n",
+      "120 2024-11-11  72.042299  75.042299      71.57      71.57  2024-11-08\n",
+      "121 2024-11-12  72.238258  75.238258      71.55      71.55  2024-11-08\n",
+      "122 2024-11-13  71.867976  74.867976      70.72      70.72  2024-11-08\n",
+      "123 2024-11-14  71.615019  74.615019      71.79      71.79  2024-11-08\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "['2024-11-08', '2024-11-09', '2024-11-10', '2024-11-11', '2024-11-12', '2024-11-13', '2024-11-14', '2024-11-15']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "99  2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "103 2024-11-08  74.519317  77.519317      73.13      73.13  2024-11-04\n",
+      "104 2024-11-11  74.569906  77.569906      71.57      71.57  2024-11-04\n",
+      "107 2024-11-08  74.694136  77.694136      73.13      73.13  2024-11-05\n",
+      "108 2024-11-11  74.762773  77.762773      71.57      71.57  2024-11-05\n",
+      "109 2024-11-12  74.566135  77.566135      71.55      71.55  2024-11-05\n",
+      "111 2024-11-08  73.830986  76.830986      73.13      73.13  2024-11-06\n",
+      "112 2024-11-11  73.992468  76.992468      71.57      71.57  2024-11-06\n",
+      "113 2024-11-12  73.151260  76.151260      71.55      71.55  2024-11-06\n",
+      "114 2024-11-13  72.774085  75.774085      70.72      70.72  2024-11-06\n",
+      "115 2024-11-08  73.928146  76.928146      73.13      73.13  2024-11-07\n",
+      "116 2024-11-11  73.889942  76.889942      71.57      71.57  2024-11-07\n",
+      "117 2024-11-12  74.026519  77.026519      71.55      71.55  2024-11-07\n",
+      "118 2024-11-13  73.767944  76.767944      70.72      70.72  2024-11-07\n",
+      "119 2024-11-14  73.642370  76.642370      71.79      71.79  2024-11-07\n",
+      "120 2024-11-11  72.042299  75.042299      71.57      71.57  2024-11-08\n",
+      "121 2024-11-12  72.238258  75.238258      71.55      71.55  2024-11-08\n",
+      "122 2024-11-13  71.867976  74.867976      70.72      70.72  2024-11-08\n",
+      "123 2024-11-14  71.615019  74.615019      71.79      71.79  2024-11-08\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "['2024-11-08', '2024-11-09', '2024-11-10', '2024-11-11', '2024-11-12', '2024-11-13', '2024-11-14', '2024-11-15']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "99  2024-11-08  71.590162  74.590162      73.13      73.13  2024-11-01\n",
+      "103 2024-11-08  74.519317  77.519317      73.13      73.13  2024-11-04\n",
+      "104 2024-11-11  74.569906  77.569906      71.57      71.57  2024-11-04\n",
+      "107 2024-11-08  74.694136  77.694136      73.13      73.13  2024-11-05\n",
+      "108 2024-11-11  74.762773  77.762773      71.57      71.57  2024-11-05\n",
+      "109 2024-11-12  74.566135  77.566135      71.55      71.55  2024-11-05\n",
+      "111 2024-11-08  73.830986  76.830986      73.13      73.13  2024-11-06\n",
+      "112 2024-11-11  73.992468  76.992468      71.57      71.57  2024-11-06\n",
+      "113 2024-11-12  73.151260  76.151260      71.55      71.55  2024-11-06\n",
+      "114 2024-11-13  72.774085  75.774085      70.72      70.72  2024-11-06\n",
+      "115 2024-11-08  73.928146  76.928146      73.13      73.13  2024-11-07\n",
+      "116 2024-11-11  73.889942  76.889942      71.57      71.57  2024-11-07\n",
+      "117 2024-11-12  74.026519  77.026519      71.55      71.55  2024-11-07\n",
+      "118 2024-11-13  73.767944  76.767944      70.72      70.72  2024-11-07\n",
+      "119 2024-11-14  73.642370  76.642370      71.79      71.79  2024-11-07\n",
+      "120 2024-11-11  72.042299  75.042299      71.57      71.57  2024-11-08\n",
+      "121 2024-11-12  72.238258  75.238258      71.55      71.55  2024-11-08\n",
+      "122 2024-11-13  71.867976  74.867976      70.72      70.72  2024-11-08\n",
+      "123 2024-11-14  71.615019  74.615019      71.79      71.79  2024-11-08\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "['2024-11-15', '2024-11-16', '2024-11-17', '2024-11-18', '2024-11-19', '2024-11-20', '2024-11-21', '2024-11-22']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "128 2024-11-15  71.255264  74.255264      70.83      70.83  2024-11-11\n",
+      "129 2024-11-18  71.421794  74.421794      70.70      70.70  2024-11-11\n",
+      "132 2024-11-15  70.607036  73.607036      70.83      70.83  2024-11-12\n",
+      "133 2024-11-18  70.520069  73.520069      70.70      70.70  2024-11-12\n",
+      "134 2024-11-19  70.747882  73.747882      72.61      72.61  2024-11-12\n",
+      "136 2024-11-15  71.227759  74.227759      70.83      70.83  2024-11-13\n",
+      "137 2024-11-18  71.786118  74.786118      70.70      70.70  2024-11-13\n",
+      "138 2024-11-19  71.775379  74.775379      72.61      72.61  2024-11-13\n",
+      "139 2024-11-20  72.188313  75.188313      72.70      72.70  2024-11-13\n",
+      "140 2024-11-15  70.857173  73.857173      70.83      70.83  2024-11-14\n",
+      "141 2024-11-18  70.920734  73.920734      70.70      70.70  2024-11-14\n",
+      "142 2024-11-19  71.358757  74.358757      72.61      72.61  2024-11-14\n",
+      "143 2024-11-20  71.586167  74.586167      72.70      72.70  2024-11-14\n",
+      "144 2024-11-21  71.787274  74.787274      71.79      71.79  2024-11-14\n",
+      "145 2024-11-18  69.781442  72.781442      70.70      70.70  2024-11-15\n",
+      "146 2024-11-19  70.118789  73.118789      72.61      72.61  2024-11-15\n",
+      "147 2024-11-20  70.319890  73.319890      72.70      72.70  2024-11-15\n",
+      "148 2024-11-21  70.470192  73.470192      71.79      71.79  2024-11-15\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "['2024-11-15', '2024-11-16', '2024-11-17', '2024-11-18', '2024-11-19', '2024-11-20', '2024-11-21', '2024-11-22']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "128 2024-11-15  71.255264  74.255264      70.83      70.83  2024-11-11\n",
+      "129 2024-11-18  71.421794  74.421794      70.70      70.70  2024-11-11\n",
+      "132 2024-11-15  70.607036  73.607036      70.83      70.83  2024-11-12\n",
+      "133 2024-11-18  70.520069  73.520069      70.70      70.70  2024-11-12\n",
+      "134 2024-11-19  70.747882  73.747882      72.61      72.61  2024-11-12\n",
+      "136 2024-11-15  71.227759  74.227759      70.83      70.83  2024-11-13\n",
+      "137 2024-11-18  71.786118  74.786118      70.70      70.70  2024-11-13\n",
+      "138 2024-11-19  71.775379  74.775379      72.61      72.61  2024-11-13\n",
+      "139 2024-11-20  72.188313  75.188313      72.70      72.70  2024-11-13\n",
+      "140 2024-11-15  70.857173  73.857173      70.83      70.83  2024-11-14\n",
+      "141 2024-11-18  70.920734  73.920734      70.70      70.70  2024-11-14\n",
+      "142 2024-11-19  71.358757  74.358757      72.61      72.61  2024-11-14\n",
+      "143 2024-11-20  71.586167  74.586167      72.70      72.70  2024-11-14\n",
+      "144 2024-11-21  71.787274  74.787274      71.79      71.79  2024-11-14\n",
+      "145 2024-11-18  69.781442  72.781442      70.70      70.70  2024-11-15\n",
+      "146 2024-11-19  70.118789  73.118789      72.61      72.61  2024-11-15\n",
+      "147 2024-11-20  70.319890  73.319890      72.70      72.70  2024-11-15\n",
+      "148 2024-11-21  70.470192  73.470192      71.79      71.79  2024-11-15\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "['2024-11-15', '2024-11-16', '2024-11-17', '2024-11-18', '2024-11-19', '2024-11-20', '2024-11-21', '2024-11-22']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "128 2024-11-15  71.255264  74.255264      70.83      70.83  2024-11-11\n",
+      "129 2024-11-18  71.421794  74.421794      70.70      70.70  2024-11-11\n",
+      "132 2024-11-15  70.607036  73.607036      70.83      70.83  2024-11-12\n",
+      "133 2024-11-18  70.520069  73.520069      70.70      70.70  2024-11-12\n",
+      "134 2024-11-19  70.747882  73.747882      72.61      72.61  2024-11-12\n",
+      "136 2024-11-15  71.227759  74.227759      70.83      70.83  2024-11-13\n",
+      "137 2024-11-18  71.786118  74.786118      70.70      70.70  2024-11-13\n",
+      "138 2024-11-19  71.775379  74.775379      72.61      72.61  2024-11-13\n",
+      "139 2024-11-20  72.188313  75.188313      72.70      72.70  2024-11-13\n",
+      "140 2024-11-15  70.857173  73.857173      70.83      70.83  2024-11-14\n",
+      "141 2024-11-18  70.920734  73.920734      70.70      70.70  2024-11-14\n",
+      "142 2024-11-19  71.358757  74.358757      72.61      72.61  2024-11-14\n",
+      "143 2024-11-20  71.586167  74.586167      72.70      72.70  2024-11-14\n",
+      "144 2024-11-21  71.787274  74.787274      71.79      71.79  2024-11-14\n",
+      "145 2024-11-18  69.781442  72.781442      70.70      70.70  2024-11-15\n",
+      "146 2024-11-19  70.118789  73.118789      72.61      72.61  2024-11-15\n",
+      "147 2024-11-20  70.319890  73.319890      72.70      72.70  2024-11-15\n",
+      "148 2024-11-21  70.470192  73.470192      71.79      71.79  2024-11-15\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "['2024-11-15', '2024-11-16', '2024-11-17', '2024-11-18', '2024-11-19', '2024-11-20', '2024-11-21', '2024-11-22']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "128 2024-11-15  71.255264  74.255264      70.83      70.83  2024-11-11\n",
+      "129 2024-11-18  71.421794  74.421794      70.70      70.70  2024-11-11\n",
+      "132 2024-11-15  70.607036  73.607036      70.83      70.83  2024-11-12\n",
+      "133 2024-11-18  70.520069  73.520069      70.70      70.70  2024-11-12\n",
+      "134 2024-11-19  70.747882  73.747882      72.61      72.61  2024-11-12\n",
+      "136 2024-11-15  71.227759  74.227759      70.83      70.83  2024-11-13\n",
+      "137 2024-11-18  71.786118  74.786118      70.70      70.70  2024-11-13\n",
+      "138 2024-11-19  71.775379  74.775379      72.61      72.61  2024-11-13\n",
+      "139 2024-11-20  72.188313  75.188313      72.70      72.70  2024-11-13\n",
+      "140 2024-11-15  70.857173  73.857173      70.83      70.83  2024-11-14\n",
+      "141 2024-11-18  70.920734  73.920734      70.70      70.70  2024-11-14\n",
+      "142 2024-11-19  71.358757  74.358757      72.61      72.61  2024-11-14\n",
+      "143 2024-11-20  71.586167  74.586167      72.70      72.70  2024-11-14\n",
+      "144 2024-11-21  71.787274  74.787274      71.79      71.79  2024-11-14\n",
+      "145 2024-11-18  69.781442  72.781442      70.70      70.70  2024-11-15\n",
+      "146 2024-11-19  70.118789  73.118789      72.61      72.61  2024-11-15\n",
+      "147 2024-11-20  70.319890  73.319890      72.70      72.70  2024-11-15\n",
+      "148 2024-11-21  70.470192  73.470192      71.79      71.79  2024-11-15\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "['2024-11-15', '2024-11-16', '2024-11-17', '2024-11-18', '2024-11-19', '2024-11-20', '2024-11-21', '2024-11-22']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "124 2024-11-15  71.822586  74.822586      70.83      70.83  2024-11-08\n",
+      "128 2024-11-15  71.255264  74.255264      70.83      70.83  2024-11-11\n",
+      "129 2024-11-18  71.421794  74.421794      70.70      70.70  2024-11-11\n",
+      "132 2024-11-15  70.607036  73.607036      70.83      70.83  2024-11-12\n",
+      "133 2024-11-18  70.520069  73.520069      70.70      70.70  2024-11-12\n",
+      "134 2024-11-19  70.747882  73.747882      72.61      72.61  2024-11-12\n",
+      "136 2024-11-15  71.227759  74.227759      70.83      70.83  2024-11-13\n",
+      "137 2024-11-18  71.786118  74.786118      70.70      70.70  2024-11-13\n",
+      "138 2024-11-19  71.775379  74.775379      72.61      72.61  2024-11-13\n",
+      "139 2024-11-20  72.188313  75.188313      72.70      72.70  2024-11-13\n",
+      "140 2024-11-15  70.857173  73.857173      70.83      70.83  2024-11-14\n",
+      "141 2024-11-18  70.920734  73.920734      70.70      70.70  2024-11-14\n",
+      "142 2024-11-19  71.358757  74.358757      72.61      72.61  2024-11-14\n",
+      "143 2024-11-20  71.586167  74.586167      72.70      72.70  2024-11-14\n",
+      "144 2024-11-21  71.787274  74.787274      71.79      71.79  2024-11-14\n",
+      "145 2024-11-18  69.781442  72.781442      70.70      70.70  2024-11-15\n",
+      "146 2024-11-19  70.118789  73.118789      72.61      72.61  2024-11-15\n",
+      "147 2024-11-20  70.319890  73.319890      72.70      72.70  2024-11-15\n",
+      "148 2024-11-21  70.470192  73.470192      71.79      71.79  2024-11-15\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "['2024-11-22', '2024-11-23', '2024-11-24', '2024-11-25', '2024-11-26', '2024-11-27', '2024-11-28', '2024-11-29']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "153 2024-11-22  72.701802  75.701802      73.43      73.43  2024-11-18\n",
+      "154 2024-11-25  72.861929  75.861929      72.30      72.30  2024-11-18\n",
+      "157 2024-11-22  72.350601  75.350601      73.43      73.43  2024-11-19\n",
+      "158 2024-11-25  72.403636  75.403636      72.30      72.30  2024-11-19\n",
+      "159 2024-11-26  72.408611  75.408611      71.63      71.63  2024-11-19\n",
+      "161 2024-11-22  71.625726  74.625726      73.43      73.43  2024-11-20\n",
+      "162 2024-11-25  71.746366  74.746366      72.30      72.30  2024-11-20\n",
+      "163 2024-11-26  71.802204  74.802204      71.63      71.63  2024-11-20\n",
+      "164 2024-11-27  71.483702  74.483702      71.71      71.71  2024-11-20\n",
+      "165 2024-11-22  73.542202  76.542202      73.43      73.43  2024-11-21\n",
+      "166 2024-11-25  73.833649  76.833649      72.30      72.30  2024-11-21\n",
+      "167 2024-11-26  73.836256  76.836256      71.63      71.63  2024-11-21\n",
+      "168 2024-11-27  74.010098  77.010098      71.71      71.71  2024-11-21\n",
+      "169 2024-11-28  74.079505  77.079505      71.85      71.85  2024-11-21\n",
+      "170 2024-11-25  74.152900  77.152900      72.30      72.30  2024-11-22\n",
+      "171 2024-11-26  74.268427  77.268427      71.63      71.63  2024-11-22\n",
+      "172 2024-11-27  74.185521  77.185521      71.71      71.71  2024-11-22\n",
+      "173 2024-11-28  74.473107  77.473107      71.85      71.85  2024-11-22\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "['2024-11-22', '2024-11-23', '2024-11-24', '2024-11-25', '2024-11-26', '2024-11-27', '2024-11-28', '2024-11-29']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "153 2024-11-22  72.701802  75.701802      73.43      73.43  2024-11-18\n",
+      "154 2024-11-25  72.861929  75.861929      72.30      72.30  2024-11-18\n",
+      "157 2024-11-22  72.350601  75.350601      73.43      73.43  2024-11-19\n",
+      "158 2024-11-25  72.403636  75.403636      72.30      72.30  2024-11-19\n",
+      "159 2024-11-26  72.408611  75.408611      71.63      71.63  2024-11-19\n",
+      "161 2024-11-22  71.625726  74.625726      73.43      73.43  2024-11-20\n",
+      "162 2024-11-25  71.746366  74.746366      72.30      72.30  2024-11-20\n",
+      "163 2024-11-26  71.802204  74.802204      71.63      71.63  2024-11-20\n",
+      "164 2024-11-27  71.483702  74.483702      71.71      71.71  2024-11-20\n",
+      "165 2024-11-22  73.542202  76.542202      73.43      73.43  2024-11-21\n",
+      "166 2024-11-25  73.833649  76.833649      72.30      72.30  2024-11-21\n",
+      "167 2024-11-26  73.836256  76.836256      71.63      71.63  2024-11-21\n",
+      "168 2024-11-27  74.010098  77.010098      71.71      71.71  2024-11-21\n",
+      "169 2024-11-28  74.079505  77.079505      71.85      71.85  2024-11-21\n",
+      "170 2024-11-25  74.152900  77.152900      72.30      72.30  2024-11-22\n",
+      "171 2024-11-26  74.268427  77.268427      71.63      71.63  2024-11-22\n",
+      "172 2024-11-27  74.185521  77.185521      71.71      71.71  2024-11-22\n",
+      "173 2024-11-28  74.473107  77.473107      71.85      71.85  2024-11-22\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "['2024-11-22', '2024-11-23', '2024-11-24', '2024-11-25', '2024-11-26', '2024-11-27', '2024-11-28', '2024-11-29']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "153 2024-11-22  72.701802  75.701802      73.43      73.43  2024-11-18\n",
+      "154 2024-11-25  72.861929  75.861929      72.30      72.30  2024-11-18\n",
+      "157 2024-11-22  72.350601  75.350601      73.43      73.43  2024-11-19\n",
+      "158 2024-11-25  72.403636  75.403636      72.30      72.30  2024-11-19\n",
+      "159 2024-11-26  72.408611  75.408611      71.63      71.63  2024-11-19\n",
+      "161 2024-11-22  71.625726  74.625726      73.43      73.43  2024-11-20\n",
+      "162 2024-11-25  71.746366  74.746366      72.30      72.30  2024-11-20\n",
+      "163 2024-11-26  71.802204  74.802204      71.63      71.63  2024-11-20\n",
+      "164 2024-11-27  71.483702  74.483702      71.71      71.71  2024-11-20\n",
+      "165 2024-11-22  73.542202  76.542202      73.43      73.43  2024-11-21\n",
+      "166 2024-11-25  73.833649  76.833649      72.30      72.30  2024-11-21\n",
+      "167 2024-11-26  73.836256  76.836256      71.63      71.63  2024-11-21\n",
+      "168 2024-11-27  74.010098  77.010098      71.71      71.71  2024-11-21\n",
+      "169 2024-11-28  74.079505  77.079505      71.85      71.85  2024-11-21\n",
+      "170 2024-11-25  74.152900  77.152900      72.30      72.30  2024-11-22\n",
+      "171 2024-11-26  74.268427  77.268427      71.63      71.63  2024-11-22\n",
+      "172 2024-11-27  74.185521  77.185521      71.71      71.71  2024-11-22\n",
+      "173 2024-11-28  74.473107  77.473107      71.85      71.85  2024-11-22\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "['2024-11-22', '2024-11-23', '2024-11-24', '2024-11-25', '2024-11-26', '2024-11-27', '2024-11-28', '2024-11-29']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "153 2024-11-22  72.701802  75.701802      73.43      73.43  2024-11-18\n",
+      "154 2024-11-25  72.861929  75.861929      72.30      72.30  2024-11-18\n",
+      "157 2024-11-22  72.350601  75.350601      73.43      73.43  2024-11-19\n",
+      "158 2024-11-25  72.403636  75.403636      72.30      72.30  2024-11-19\n",
+      "159 2024-11-26  72.408611  75.408611      71.63      71.63  2024-11-19\n",
+      "161 2024-11-22  71.625726  74.625726      73.43      73.43  2024-11-20\n",
+      "162 2024-11-25  71.746366  74.746366      72.30      72.30  2024-11-20\n",
+      "163 2024-11-26  71.802204  74.802204      71.63      71.63  2024-11-20\n",
+      "164 2024-11-27  71.483702  74.483702      71.71      71.71  2024-11-20\n",
+      "165 2024-11-22  73.542202  76.542202      73.43      73.43  2024-11-21\n",
+      "166 2024-11-25  73.833649  76.833649      72.30      72.30  2024-11-21\n",
+      "167 2024-11-26  73.836256  76.836256      71.63      71.63  2024-11-21\n",
+      "168 2024-11-27  74.010098  77.010098      71.71      71.71  2024-11-21\n",
+      "169 2024-11-28  74.079505  77.079505      71.85      71.85  2024-11-21\n",
+      "170 2024-11-25  74.152900  77.152900      72.30      72.30  2024-11-22\n",
+      "171 2024-11-26  74.268427  77.268427      71.63      71.63  2024-11-22\n",
+      "172 2024-11-27  74.185521  77.185521      71.71      71.71  2024-11-22\n",
+      "173 2024-11-28  74.473107  77.473107      71.85      71.85  2024-11-22\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "['2024-11-22', '2024-11-23', '2024-11-24', '2024-11-25', '2024-11-26', '2024-11-27', '2024-11-28', '2024-11-29']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "149 2024-11-22  70.457320  73.457320      73.43      73.43  2024-11-15\n",
+      "153 2024-11-22  72.701802  75.701802      73.43      73.43  2024-11-18\n",
+      "154 2024-11-25  72.861929  75.861929      72.30      72.30  2024-11-18\n",
+      "157 2024-11-22  72.350601  75.350601      73.43      73.43  2024-11-19\n",
+      "158 2024-11-25  72.403636  75.403636      72.30      72.30  2024-11-19\n",
+      "159 2024-11-26  72.408611  75.408611      71.63      71.63  2024-11-19\n",
+      "161 2024-11-22  71.625726  74.625726      73.43      73.43  2024-11-20\n",
+      "162 2024-11-25  71.746366  74.746366      72.30      72.30  2024-11-20\n",
+      "163 2024-11-26  71.802204  74.802204      71.63      71.63  2024-11-20\n",
+      "164 2024-11-27  71.483702  74.483702      71.71      71.71  2024-11-20\n",
+      "165 2024-11-22  73.542202  76.542202      73.43      73.43  2024-11-21\n",
+      "166 2024-11-25  73.833649  76.833649      72.30      72.30  2024-11-21\n",
+      "167 2024-11-26  73.836256  76.836256      71.63      71.63  2024-11-21\n",
+      "168 2024-11-27  74.010098  77.010098      71.71      71.71  2024-11-21\n",
+      "169 2024-11-28  74.079505  77.079505      71.85      71.85  2024-11-21\n",
+      "170 2024-11-25  74.152900  77.152900      72.30      72.30  2024-11-22\n",
+      "171 2024-11-26  74.268427  77.268427      71.63      71.63  2024-11-22\n",
+      "172 2024-11-27  74.185521  77.185521      71.71      71.71  2024-11-22\n",
+      "173 2024-11-28  74.473107  77.473107      71.85      71.85  2024-11-22\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "['2024-11-29', '2024-11-30', '2024-12-01', '2024-12-02', '2024-12-03', '2024-12-04', '2024-12-05', '2024-12-06']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "178 2024-11-29  72.833511  75.833511      71.75      71.75  2024-11-25\n",
+      "179 2024-12-02  72.992029  75.992029      71.52      71.52  2024-11-25\n",
+      "182 2024-11-29  72.366704  75.366704      71.75      71.75  2024-11-26\n",
+      "183 2024-12-02  72.674196  75.674196      71.52      71.52  2024-11-26\n",
+      "184 2024-12-03  72.549176  75.549176      71.68      71.68  2024-11-26\n",
+      "186 2024-11-29  72.706763  75.706763      71.75      71.75  2024-11-27\n",
+      "187 2024-12-02  72.719974  75.719974      71.52      71.52  2024-11-27\n",
+      "188 2024-12-03  73.250393  76.250393      71.68      71.68  2024-11-27\n",
+      "189 2024-12-04  73.279968  76.279968      72.25      72.25  2024-11-27\n",
+      "190 2024-11-29  72.307409  75.307409      71.75      71.75  2024-11-28\n",
+      "191 2024-12-02  72.440306  75.440306      71.52      71.52  2024-11-28\n",
+      "192 2024-12-03  72.684748  75.684748      71.68      71.68  2024-11-28\n",
+      "193 2024-12-04  72.904345  75.904345      72.25      72.25  2024-11-28\n",
+      "194 2024-12-05  73.119072  76.119072      71.80      71.80  2024-11-28\n",
+      "195 2024-12-02  71.978429  74.978429      71.52      71.52  2024-11-29\n",
+      "196 2024-12-03  72.177397  75.177397      71.68      71.68  2024-11-29\n",
+      "197 2024-12-04  72.111895  75.111895      72.25      72.25  2024-11-29\n",
+      "198 2024-12-05  71.917178  74.917178      71.80      71.80  2024-11-29\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "['2024-11-29', '2024-11-30', '2024-12-01', '2024-12-02', '2024-12-03', '2024-12-04', '2024-12-05', '2024-12-06']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "178 2024-11-29  72.833511  75.833511      71.75      71.75  2024-11-25\n",
+      "179 2024-12-02  72.992029  75.992029      71.52      71.52  2024-11-25\n",
+      "182 2024-11-29  72.366704  75.366704      71.75      71.75  2024-11-26\n",
+      "183 2024-12-02  72.674196  75.674196      71.52      71.52  2024-11-26\n",
+      "184 2024-12-03  72.549176  75.549176      71.68      71.68  2024-11-26\n",
+      "186 2024-11-29  72.706763  75.706763      71.75      71.75  2024-11-27\n",
+      "187 2024-12-02  72.719974  75.719974      71.52      71.52  2024-11-27\n",
+      "188 2024-12-03  73.250393  76.250393      71.68      71.68  2024-11-27\n",
+      "189 2024-12-04  73.279968  76.279968      72.25      72.25  2024-11-27\n",
+      "190 2024-11-29  72.307409  75.307409      71.75      71.75  2024-11-28\n",
+      "191 2024-12-02  72.440306  75.440306      71.52      71.52  2024-11-28\n",
+      "192 2024-12-03  72.684748  75.684748      71.68      71.68  2024-11-28\n",
+      "193 2024-12-04  72.904345  75.904345      72.25      72.25  2024-11-28\n",
+      "194 2024-12-05  73.119072  76.119072      71.80      71.80  2024-11-28\n",
+      "195 2024-12-02  71.978429  74.978429      71.52      71.52  2024-11-29\n",
+      "196 2024-12-03  72.177397  75.177397      71.68      71.68  2024-11-29\n",
+      "197 2024-12-04  72.111895  75.111895      72.25      72.25  2024-11-29\n",
+      "198 2024-12-05  71.917178  74.917178      71.80      71.80  2024-11-29\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "['2024-11-29', '2024-11-30', '2024-12-01', '2024-12-02', '2024-12-03', '2024-12-04', '2024-12-05', '2024-12-06']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "178 2024-11-29  72.833511  75.833511      71.75      71.75  2024-11-25\n",
+      "179 2024-12-02  72.992029  75.992029      71.52      71.52  2024-11-25\n",
+      "182 2024-11-29  72.366704  75.366704      71.75      71.75  2024-11-26\n",
+      "183 2024-12-02  72.674196  75.674196      71.52      71.52  2024-11-26\n",
+      "184 2024-12-03  72.549176  75.549176      71.68      71.68  2024-11-26\n",
+      "186 2024-11-29  72.706763  75.706763      71.75      71.75  2024-11-27\n",
+      "187 2024-12-02  72.719974  75.719974      71.52      71.52  2024-11-27\n",
+      "188 2024-12-03  73.250393  76.250393      71.68      71.68  2024-11-27\n",
+      "189 2024-12-04  73.279968  76.279968      72.25      72.25  2024-11-27\n",
+      "190 2024-11-29  72.307409  75.307409      71.75      71.75  2024-11-28\n",
+      "191 2024-12-02  72.440306  75.440306      71.52      71.52  2024-11-28\n",
+      "192 2024-12-03  72.684748  75.684748      71.68      71.68  2024-11-28\n",
+      "193 2024-12-04  72.904345  75.904345      72.25      72.25  2024-11-28\n",
+      "194 2024-12-05  73.119072  76.119072      71.80      71.80  2024-11-28\n",
+      "195 2024-12-02  71.978429  74.978429      71.52      71.52  2024-11-29\n",
+      "196 2024-12-03  72.177397  75.177397      71.68      71.68  2024-11-29\n",
+      "197 2024-12-04  72.111895  75.111895      72.25      72.25  2024-11-29\n",
+      "198 2024-12-05  71.917178  74.917178      71.80      71.80  2024-11-29\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "['2024-11-29', '2024-11-30', '2024-12-01', '2024-12-02', '2024-12-03', '2024-12-04', '2024-12-05', '2024-12-06']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "178 2024-11-29  72.833511  75.833511      71.75      71.75  2024-11-25\n",
+      "179 2024-12-02  72.992029  75.992029      71.52      71.52  2024-11-25\n",
+      "182 2024-11-29  72.366704  75.366704      71.75      71.75  2024-11-26\n",
+      "183 2024-12-02  72.674196  75.674196      71.52      71.52  2024-11-26\n",
+      "184 2024-12-03  72.549176  75.549176      71.68      71.68  2024-11-26\n",
+      "186 2024-11-29  72.706763  75.706763      71.75      71.75  2024-11-27\n",
+      "187 2024-12-02  72.719974  75.719974      71.52      71.52  2024-11-27\n",
+      "188 2024-12-03  73.250393  76.250393      71.68      71.68  2024-11-27\n",
+      "189 2024-12-04  73.279968  76.279968      72.25      72.25  2024-11-27\n",
+      "190 2024-11-29  72.307409  75.307409      71.75      71.75  2024-11-28\n",
+      "191 2024-12-02  72.440306  75.440306      71.52      71.52  2024-11-28\n",
+      "192 2024-12-03  72.684748  75.684748      71.68      71.68  2024-11-28\n",
+      "193 2024-12-04  72.904345  75.904345      72.25      72.25  2024-11-28\n",
+      "194 2024-12-05  73.119072  76.119072      71.80      71.80  2024-11-28\n",
+      "195 2024-12-02  71.978429  74.978429      71.52      71.52  2024-11-29\n",
+      "196 2024-12-03  72.177397  75.177397      71.68      71.68  2024-11-29\n",
+      "197 2024-12-04  72.111895  75.111895      72.25      72.25  2024-11-29\n",
+      "198 2024-12-05  71.917178  74.917178      71.80      71.80  2024-11-29\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "['2024-11-29', '2024-11-30', '2024-12-01', '2024-12-02', '2024-12-03', '2024-12-04', '2024-12-05', '2024-12-06']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "174 2024-11-29  74.723802  77.723802      71.75      71.75  2024-11-22\n",
+      "178 2024-11-29  72.833511  75.833511      71.75      71.75  2024-11-25\n",
+      "179 2024-12-02  72.992029  75.992029      71.52      71.52  2024-11-25\n",
+      "182 2024-11-29  72.366704  75.366704      71.75      71.75  2024-11-26\n",
+      "183 2024-12-02  72.674196  75.674196      71.52      71.52  2024-11-26\n",
+      "184 2024-12-03  72.549176  75.549176      71.68      71.68  2024-11-26\n",
+      "186 2024-11-29  72.706763  75.706763      71.75      71.75  2024-11-27\n",
+      "187 2024-12-02  72.719974  75.719974      71.52      71.52  2024-11-27\n",
+      "188 2024-12-03  73.250393  76.250393      71.68      71.68  2024-11-27\n",
+      "189 2024-12-04  73.279968  76.279968      72.25      72.25  2024-11-27\n",
+      "190 2024-11-29  72.307409  75.307409      71.75      71.75  2024-11-28\n",
+      "191 2024-12-02  72.440306  75.440306      71.52      71.52  2024-11-28\n",
+      "192 2024-12-03  72.684748  75.684748      71.68      71.68  2024-11-28\n",
+      "193 2024-12-04  72.904345  75.904345      72.25      72.25  2024-11-28\n",
+      "194 2024-12-05  73.119072  76.119072      71.80      71.80  2024-11-28\n",
+      "195 2024-12-02  71.978429  74.978429      71.52      71.52  2024-11-29\n",
+      "196 2024-12-03  72.177397  75.177397      71.68      71.68  2024-11-29\n",
+      "197 2024-12-04  72.111895  75.111895      72.25      72.25  2024-11-29\n",
+      "198 2024-12-05  71.917178  74.917178      71.80      71.80  2024-11-29\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "['2024-12-06', '2024-12-07', '2024-12-08', '2024-12-09', '2024-12-10', '2024-12-11', '2024-12-12', '2024-12-13']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "203 2024-12-06  71.060380  74.060380      70.85      70.85  2024-12-02\n",
+      "204 2024-12-09  71.344403  74.344403      70.92      70.92  2024-12-02\n",
+      "207 2024-12-06  72.125730  75.125730      70.85      70.85  2024-12-03\n",
+      "208 2024-12-09  72.220322  75.220322      70.92      70.92  2024-12-03\n",
+      "209 2024-12-10  72.069719  75.069719      70.73      70.73  2024-12-03\n",
+      "211 2024-12-06  70.098060  73.098060      70.85      70.85  2024-12-04\n",
+      "212 2024-12-09  70.214520  73.214520      70.92      70.92  2024-12-04\n",
+      "213 2024-12-10  70.193227  73.193227      70.73      70.73  2024-12-04\n",
+      "214 2024-12-11  70.352228  73.352228      72.15      72.15  2024-12-04\n",
+      "215 2024-12-06  69.842873  72.842873      70.85      70.85  2024-12-05\n",
+      "216 2024-12-09  70.212922  73.212922      70.92      70.92  2024-12-05\n",
+      "217 2024-12-10  70.203988  73.203988      70.73      70.73  2024-12-05\n",
+      "218 2024-12-11  70.258084  73.258084      72.15      72.15  2024-12-05\n",
+      "219 2024-12-12  70.810124  73.810124      72.42      72.42  2024-12-05\n",
+      "220 2024-12-09  69.482207  72.482207      70.92      70.92  2024-12-06\n",
+      "221 2024-12-10  69.475770  72.475770      70.73      70.73  2024-12-06\n",
+      "222 2024-12-11  69.875355  72.875355      72.15      72.15  2024-12-06\n",
+      "223 2024-12-12  70.133042  73.133042      72.42      72.42  2024-12-06\n",
+      "224 2024-12-13  70.209316  73.209316      73.30      73.30  2024-12-06\n",
+      "['2024-12-06', '2024-12-07', '2024-12-08', '2024-12-09', '2024-12-10', '2024-12-11', '2024-12-12', '2024-12-13']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "203 2024-12-06  71.060380  74.060380      70.85      70.85  2024-12-02\n",
+      "204 2024-12-09  71.344403  74.344403      70.92      70.92  2024-12-02\n",
+      "207 2024-12-06  72.125730  75.125730      70.85      70.85  2024-12-03\n",
+      "208 2024-12-09  72.220322  75.220322      70.92      70.92  2024-12-03\n",
+      "209 2024-12-10  72.069719  75.069719      70.73      70.73  2024-12-03\n",
+      "211 2024-12-06  70.098060  73.098060      70.85      70.85  2024-12-04\n",
+      "212 2024-12-09  70.214520  73.214520      70.92      70.92  2024-12-04\n",
+      "213 2024-12-10  70.193227  73.193227      70.73      70.73  2024-12-04\n",
+      "214 2024-12-11  70.352228  73.352228      72.15      72.15  2024-12-04\n",
+      "215 2024-12-06  69.842873  72.842873      70.85      70.85  2024-12-05\n",
+      "216 2024-12-09  70.212922  73.212922      70.92      70.92  2024-12-05\n",
+      "217 2024-12-10  70.203988  73.203988      70.73      70.73  2024-12-05\n",
+      "218 2024-12-11  70.258084  73.258084      72.15      72.15  2024-12-05\n",
+      "219 2024-12-12  70.810124  73.810124      72.42      72.42  2024-12-05\n",
+      "220 2024-12-09  69.482207  72.482207      70.92      70.92  2024-12-06\n",
+      "221 2024-12-10  69.475770  72.475770      70.73      70.73  2024-12-06\n",
+      "222 2024-12-11  69.875355  72.875355      72.15      72.15  2024-12-06\n",
+      "223 2024-12-12  70.133042  73.133042      72.42      72.42  2024-12-06\n",
+      "224 2024-12-13  70.209316  73.209316      73.30      73.30  2024-12-06\n",
+      "['2024-12-06', '2024-12-07', '2024-12-08', '2024-12-09', '2024-12-10', '2024-12-11', '2024-12-12', '2024-12-13']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "203 2024-12-06  71.060380  74.060380      70.85      70.85  2024-12-02\n",
+      "204 2024-12-09  71.344403  74.344403      70.92      70.92  2024-12-02\n",
+      "207 2024-12-06  72.125730  75.125730      70.85      70.85  2024-12-03\n",
+      "208 2024-12-09  72.220322  75.220322      70.92      70.92  2024-12-03\n",
+      "209 2024-12-10  72.069719  75.069719      70.73      70.73  2024-12-03\n",
+      "211 2024-12-06  70.098060  73.098060      70.85      70.85  2024-12-04\n",
+      "212 2024-12-09  70.214520  73.214520      70.92      70.92  2024-12-04\n",
+      "213 2024-12-10  70.193227  73.193227      70.73      70.73  2024-12-04\n",
+      "214 2024-12-11  70.352228  73.352228      72.15      72.15  2024-12-04\n",
+      "215 2024-12-06  69.842873  72.842873      70.85      70.85  2024-12-05\n",
+      "216 2024-12-09  70.212922  73.212922      70.92      70.92  2024-12-05\n",
+      "217 2024-12-10  70.203988  73.203988      70.73      70.73  2024-12-05\n",
+      "218 2024-12-11  70.258084  73.258084      72.15      72.15  2024-12-05\n",
+      "219 2024-12-12  70.810124  73.810124      72.42      72.42  2024-12-05\n",
+      "220 2024-12-09  69.482207  72.482207      70.92      70.92  2024-12-06\n",
+      "221 2024-12-10  69.475770  72.475770      70.73      70.73  2024-12-06\n",
+      "222 2024-12-11  69.875355  72.875355      72.15      72.15  2024-12-06\n",
+      "223 2024-12-12  70.133042  73.133042      72.42      72.42  2024-12-06\n",
+      "224 2024-12-13  70.209316  73.209316      73.30      73.30  2024-12-06\n",
+      "['2024-12-06', '2024-12-07', '2024-12-08', '2024-12-09', '2024-12-10', '2024-12-11', '2024-12-12', '2024-12-13']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "203 2024-12-06  71.060380  74.060380      70.85      70.85  2024-12-02\n",
+      "204 2024-12-09  71.344403  74.344403      70.92      70.92  2024-12-02\n",
+      "207 2024-12-06  72.125730  75.125730      70.85      70.85  2024-12-03\n",
+      "208 2024-12-09  72.220322  75.220322      70.92      70.92  2024-12-03\n",
+      "209 2024-12-10  72.069719  75.069719      70.73      70.73  2024-12-03\n",
+      "211 2024-12-06  70.098060  73.098060      70.85      70.85  2024-12-04\n",
+      "212 2024-12-09  70.214520  73.214520      70.92      70.92  2024-12-04\n",
+      "213 2024-12-10  70.193227  73.193227      70.73      70.73  2024-12-04\n",
+      "214 2024-12-11  70.352228  73.352228      72.15      72.15  2024-12-04\n",
+      "215 2024-12-06  69.842873  72.842873      70.85      70.85  2024-12-05\n",
+      "216 2024-12-09  70.212922  73.212922      70.92      70.92  2024-12-05\n",
+      "217 2024-12-10  70.203988  73.203988      70.73      70.73  2024-12-05\n",
+      "218 2024-12-11  70.258084  73.258084      72.15      72.15  2024-12-05\n",
+      "219 2024-12-12  70.810124  73.810124      72.42      72.42  2024-12-05\n",
+      "220 2024-12-09  69.482207  72.482207      70.92      70.92  2024-12-06\n",
+      "221 2024-12-10  69.475770  72.475770      70.73      70.73  2024-12-06\n",
+      "222 2024-12-11  69.875355  72.875355      72.15      72.15  2024-12-06\n",
+      "223 2024-12-12  70.133042  73.133042      72.42      72.42  2024-12-06\n",
+      "224 2024-12-13  70.209316  73.209316      73.30      73.30  2024-12-06\n",
+      "['2024-12-06', '2024-12-07', '2024-12-08', '2024-12-09', '2024-12-10', '2024-12-11', '2024-12-12', '2024-12-13']\n",
+      "(30, 6)\n",
+      "            ds  min_price  max_price  LOW_PRICE  LOW_PRICE  CREAT_DATE\n",
+      "199 2024-12-06  71.973777  74.973777      70.85      70.85  2024-11-29\n",
+      "203 2024-12-06  71.060380  74.060380      70.85      70.85  2024-12-02\n",
+      "204 2024-12-09  71.344403  74.344403      70.92      70.92  2024-12-02\n",
+      "207 2024-12-06  72.125730  75.125730      70.85      70.85  2024-12-03\n",
+      "208 2024-12-09  72.220322  75.220322      70.92      70.92  2024-12-03\n",
+      "209 2024-12-10  72.069719  75.069719      70.73      70.73  2024-12-03\n",
+      "211 2024-12-06  70.098060  73.098060      70.85      70.85  2024-12-04\n",
+      "212 2024-12-09  70.214520  73.214520      70.92      70.92  2024-12-04\n",
+      "213 2024-12-10  70.193227  73.193227      70.73      70.73  2024-12-04\n",
+      "214 2024-12-11  70.352228  73.352228      72.15      72.15  2024-12-04\n",
+      "215 2024-12-06  69.842873  72.842873      70.85      70.85  2024-12-05\n",
+      "216 2024-12-09  70.212922  73.212922      70.92      70.92  2024-12-05\n",
+      "217 2024-12-10  70.203988  73.203988      70.73      70.73  2024-12-05\n",
+      "218 2024-12-11  70.258084  73.258084      72.15      72.15  2024-12-05\n",
+      "219 2024-12-12  70.810124  73.810124      72.42      72.42  2024-12-05\n",
+      "220 2024-12-09  69.482207  72.482207      70.92      70.92  2024-12-06\n",
+      "221 2024-12-10  69.475770  72.475770      70.73      70.73  2024-12-06\n",
+      "222 2024-12-11  69.875355  72.875355      72.15      72.15  2024-12-06\n",
+      "223 2024-12-12  70.133042  73.133042      72.42      72.42  2024-12-06\n",
+      "224 2024-12-13  70.209316  73.209316      73.30      73.30  2024-12-06\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 1600x1000 with 1 Axes>"
+       "<Figure size 1600x1000 with 0 Axes>"
       ]
      },
      "metadata": {},
@@ -396,7 +1406,7 @@
     "df5 = df5[['ds','min_price','max_price','LOW_PRICE','LOW_PRICE','CREAT_DATE']]\n",
     "\n",
     "print(df5.shape)\n",
-    "print(df5.head(10))\n",
+    "print(df5.head(20))\n",
     "# 画图配置\n",
     "plt.figure(figsize=(16,10))\n",
     "\n",
@@ -404,11 +1414,10 @@
     "    endtime = end_time\n",
     "    # endtimeweek = datetime.datetime.strptime(endtime, '%Y-%m-%d')\n",
     "    endtimeweek = endtime\n",
-    "    up_week = endtimeweek - datetime.timedelta(days=endtimeweek.weekday() )\n",
-    "    up_week_dates = [up_week + datetime.timedelta(days=i) for i in range(7)]\n",
+    "    up_week = endtimeweek - datetime.timedelta(days=endtimeweek.weekday() + 14)\n",
+    "    up_week_dates = [up_week + datetime.timedelta(days=i) for i in range(14)][4:-2]\n",
     "    up_week_dates = [date.strftime('%Y-%m-%d') for date in up_week_dates]\n",
     "    return up_week_dates\n",
-    "\n",
     "# ds分组\n",
     "end_times = df['ds'].unique()\n",
     "for endtime in end_times:\n",
@@ -416,13 +1425,13 @@
     "    print(up_week_dates)\n",
     "    df6 = df5[df5['ds'].isin(up_week_dates)]\n",
     "    print(df6.shape)\n",
-    "    print(df6.head(10))\n",
+    "    print(df6.head(20))\n",
     "    # sns画散点图\n",
-    "    sns.scatterplot(x=df6.index,y=df6['min_price'].values,data=df6)\n",
-    "    sns.scatterplot(x=df6.index,y=df6['max_price'].values,data=df6)\n",
-    "    sns.scatterplot(x=df6.index,y=df6['LOW_PRICE'].values,data=df6)\n",
-    "    sns.scatterplot(x=df6.index,y=df6['HIGH_PRICE'].values,data=df6)\n",
-    "    sns.scatterplot(x=df6.index,y=df6['HIGH_PRICE'].values,data=df6)"
+    "    # sns.scatterplot(x=df6.index,y=df6['min_price'].values,data=df6)\n",
+    "    # sns.scatterplot(x=df6.index,y=df6['max_price'].values,data=df6)\n",
+    "    # sns.scatterplot(x=df6.index,y=df6['LOW_PRICE'].values,data=df6)\n",
+    "    # sns.scatterplot(x=df6.index,y=df6['HIGH_PRICE'].values,data=df6)\n",
+    "    # sns.scatterplot(x=df6.index,y=df6['HIGH_PRICE'].values,data=df6)"
    ]
   },
   {