From d4187e8c1ee4f26559c0dfbc3c5c1d66bcefac74 Mon Sep 17 00:00:00 2001 From: workpc Date: Mon, 10 Mar 2025 17:00:07 +0800 Subject: [PATCH] =?UTF-8?q?=E6=B6=B2=E5=8C=96=E7=9F=B3=E6=B2=B9=E6=B0=94?= =?UTF-8?q?=E6=95=B0=E6=8D=AE=E6=9B=B4=E6=96=B0=E5=88=B02.28=EF=BC=9B?= =?UTF-8?q?=E8=81=9A=E7=83=AF=E7=83=83=E6=95=B0=E6=8D=AE=E8=8E=B7=E5=8F=96?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../液化石油气/液化气价格预测ytj.ipynb | 1237 +---------------- aisenzhecode/液化石油气/液化气数据.xls | Bin 186880 -> 186880 bytes config_jingbo_yuedu.py | 2 +- config_juxiting.py | 329 +++-- lib/dataread.py | 14 +- main_juxiting.py | 350 +++-- main_yuanyou_yuedu.py | 17 +- 7 files changed, 428 insertions(+), 1521 deletions(-) diff --git a/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb b/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb index 02a48b9..c18db50 100644 --- a/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb +++ b/aisenzhecode/液化石油气/液化气价格预测ytj.ipynb @@ -2,17 +2,9 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING:tensorflow:From C:\\Users\\EDY\\AppData\\Roaming\\Python\\Python311\\site-packages\\keras\\src\\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.\n", - "\n" - ] - }, { "data": { "text/html": [ @@ -555,8 +547,8 @@ " else:\n", " append_rows.append(\"\")\n", " save_xls(append_rows)\n", - " optimize_Model()\n", - " upload_data_to_system(token_push,cur_time)\n", + " # optimize_Model()\n", + " # upload_data_to_system(token_push,cur_time)\n", " \n", " \n", " \n", @@ -724,7 +716,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": { "scrolled": true }, @@ -770,1213 +762,40 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "20250204 \n", - "2025-02-04 00:00:00 \n", - "{'data': {'date': '20250204', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250204', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8905.0}, {'dataDate': '20250204', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250204', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250204', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250204', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5000.0}, {'dataDate': '20250204', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 4900.0}, {'dataDate': '20250204', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4690.0}, {'dataDate': '20250204', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5050.0}, {'dataDate': '20250204', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250204', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250204', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250204', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250204', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250204', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5400.0}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 105.9453}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250204', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -150.0}, {'dataDate': '20250204', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250204', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250204', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6900.0}]\n", - "{'dataDate': '20250204', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250204', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: \n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "d:\\ProgramData\\anaconda3\\Lib\\site-packages\\IPython\\core\\magics\\pylab.py:162: UserWarning:\n", - "\n", - "pylab import has clobbered these variables: ['__version__', 'random', 'plot', 'datetime']\n", - "`%matplotlib` prevents importing * from pylab and numpy\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-04 5410.651855\n", - "Name: 日度预测价格, dtype: float32\n", - "20250205 \n", - "2025-02-05 00:00:00 \n", - "{'data': {'date': '20250205', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250205', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8956.0}, {'dataDate': '20250205', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250205', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5140.0}, {'dataDate': '20250205', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250205', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250205', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250205', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5050.0}, {'dataDate': '20250205', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4790.0}, {'dataDate': '20250205', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250205', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5680.0}, {'dataDate': '20250205', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5530.0}, {'dataDate': '20250205', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250205', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5638.0}, {'dataDate': '20250205', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250205', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5635.0}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 81.2796}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250205', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -150.0}, {'dataDate': '20250205', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250205', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5050.0}, {'dataDate': '20250205', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250205', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8800.0}, {'dataDate': '20250205', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6200.0}]\n", - "{'dataDate': '20250205', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250205', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-05 5494.333496\n", - "Name: 日度预测价格, dtype: float32\n", - "20250206 \n", - "2025-02-06 00:00:00 \n", - "{'data': {'date': '20250206', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250206', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8956.0}, {'dataDate': '20250206', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250206', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5160.0}, {'dataDate': '20250206', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250206', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250206', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250206', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250206', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4870.0}, {'dataDate': '20250206', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250206', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250206', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5630.0}, {'dataDate': '20250206', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250206', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5678.0}, {'dataDate': '20250206', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250206', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5655.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 152.4238}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 0.0}, {'dataDate': '20250206', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -150.0}, {'dataDate': '20250206', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250206', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5070.0}, {'dataDate': '20250206', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250206', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8800.0}, {'dataDate': '20250206', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6200.0}]\n", - "{'dataDate': '20250206', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-06 5552.835938\n", - "Name: 日度预测价格, dtype: float32\n", - "20250207 \n", - "2025-02-07 00:00:00 \n", - "{'data': {'date': '20250207', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250207', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8921.0}, {'dataDate': '20250207', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250207', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5160.0}, {'dataDate': '20250207', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250207', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250207', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250207', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250207', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4870.0}, {'dataDate': '20250207', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250207', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250207', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5630.0}, {'dataDate': '20250207', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250207', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5678.0}, {'dataDate': '20250207', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250207', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5655.0}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5550.0}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': -7.6913}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250207', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -150.0}, {'dataDate': '20250207', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250207', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5110.0}, {'dataDate': '20250207', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250207', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8700.0}, {'dataDate': '20250207', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6150.0}]\n", - "{'dataDate': '20250207', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250207', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-07 5574.327637\n", - "Name: 日度预测价格, dtype: float32\n", - "20250208 \n", - "2025-02-08 00:00:00 \n", - "{'data': {'date': '20250208', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250208', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8866.0}, {'dataDate': '20250208', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250208', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5220.0}, {'dataDate': '20250208', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250208', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE', 'dataValue': 0.0}, {'dataDate': '20250208', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250208', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250208', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4870.0}, {'dataDate': '20250208', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250208', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250208', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250208', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250208', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5578.0}, {'dataDate': '20250208', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250208', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5450.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 153.4345}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 0.0}, {'dataDate': '20250208', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250208', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250208', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5130.0}, {'dataDate': '20250208', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250208', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8700.0}, {'dataDate': '20250208', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6100.0}]\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-08 5400.607422\n", - "Name: 日度预测价格, dtype: float32\n", - "20250209 \n", - "2025-02-09 00:00:00 \n", - "{'data': {'date': '20250209', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250209', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8875.0}, {'dataDate': '20250209', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250209', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250209', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250209', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250209', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250209', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4870.0}, {'dataDate': '20250209', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250209', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250209', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5470.0}, {'dataDate': '20250209', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250209', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5558.0}, {'dataDate': '20250209', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250209', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 231.5606}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250209', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250209', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250209', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250209', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 7000.0}]\n", - "{'dataDate': '20250209', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250209', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-09 5392.519043\n", - "Name: 日度预测价格, dtype: float32\n", - "20250210 \n", - "2025-02-10 00:00:00 \n", - "{'data': {'date': '20250210', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250210', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8875.0}, {'dataDate': '20250210', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250210', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250210', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250210', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250210', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250210', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250210', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4820.0}, {'dataDate': '20250210', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250210', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250210', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5470.0}, {'dataDate': '20250210', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250210', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5558.0}, {'dataDate': '20250210', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250210', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 236.8478}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250210', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250210', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250210', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5160.0}, {'dataDate': '20250210', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250210', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8600.0}, {'dataDate': '20250210', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6000.0}]\n", - "{'dataDate': '20250210', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250210', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-10 5405.626465\n", - "Name: 日度预测价格, dtype: float32\n", - "20250211 \n", - "2025-02-11 00:00:00 \n", - "{'data': {'date': '20250211', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250211', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8875.0}, {'dataDate': '20250211', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5420.0}, {'dataDate': '20250211', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5280.0}, {'dataDate': '20250211', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250211', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250211', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250211', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250211', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4820.0}, {'dataDate': '20250211', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250211', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250211', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5490.0}, {'dataDate': '20250211', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250211', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250211', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250211', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5420.0}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5420.0}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 263.0919}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250211', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250211', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250211', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250211', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250211', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8550.0}, {'dataDate': '20250211', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5700.0}]\n", - "{'dataDate': '20250211', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250211', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-11 5423.526855\n", - "Name: 日度预测价格, dtype: float32\n", - "20250212 \n", - "2025-02-12 00:00:00 \n", - "{'data': {'date': '20250212', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250212', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8875.0}, {'dataDate': '20250212', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5480.0}, {'dataDate': '20250212', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5280.0}, {'dataDate': '20250212', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250212', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250212', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250212', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250212', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250212', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250212', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5750.0}, {'dataDate': '20250212', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250212', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250212', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5708.0}, {'dataDate': '20250212', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250212', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5705.0}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 332.637}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250212', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250212', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250212', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5100.0}, {'dataDate': '20250212', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250212', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8600.0}, {'dataDate': '20250212', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5675.0}]\n", - "{'dataDate': '20250212', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250212', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-12 5480.074707\n", - "Name: 日度预测价格, dtype: float32\n", - "20250213 \n", - "2025-02-13 00:00:00 \n", - "{'data': {'date': '20250213', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250213', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8793.0}, {'dataDate': '20250213', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5420.0}, {'dataDate': '20250213', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5280.0}, {'dataDate': '20250213', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250213', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250213', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250213', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250213', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250213', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250213', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250213', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5470.0}, {'dataDate': '20250213', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250213', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5658.0}, {'dataDate': '20250213', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250213', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5625.0}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5420.0}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 229.5496}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250213', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250213', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250213', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5080.0}, {'dataDate': '20250213', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250213', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250213', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5800.0}]\n", - "{'dataDate': '20250213', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250213', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-13 5421.194336\n", - "Name: 日度预测价格, dtype: float32\n", - "20250214 \n", - "2025-02-14 00:00:00 \n", - "{'data': {'date': '20250214', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250214', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8722.0}, {'dataDate': '20250214', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5370.0}, {'dataDate': '20250214', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5270.0}, {'dataDate': '20250214', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250214', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250214', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250214', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250214', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250214', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250214', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250214', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250214', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250214', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5608.0}, {'dataDate': '20250214', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250214', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5370.0}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 322.7353}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250214', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250214', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250214', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5090.0}, {'dataDate': '20250214', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250214', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8300.0}, {'dataDate': '20250214', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5800.0}]\n", - "{'dataDate': '20250214', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250214', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-14 5389.237305\n", - "Name: 日度预测价格, dtype: float32\n", - "20250215 \n", - "2025-02-15 00:00:00 \n", - "{'data': {'date': '20250215', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250215', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8722.0}, {'dataDate': '20250215', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250215', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250215', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250215', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250215', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250215', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250215', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250215', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250215', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250215', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250215', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5538.0}, {'dataDate': '20250215', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250215', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5505.0}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5300.0}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 461.3501}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250215', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250215', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250215', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250215', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6850.0}]\n", - "{'dataDate': '20250215', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250215', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-15 5337.031738\n", - "Name: 日度预测价格, dtype: float32\n", - "20250216 \n", - "2025-02-16 00:00:00 \n", - "{'data': {'date': '20250216', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250216', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250216', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250216', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250216', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250216', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250216', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250216', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250216', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5380.0}, {'dataDate': '20250216', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5538.0}, {'dataDate': '20250216', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5505.0}, {'dataDate': '20250216', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5300.0}, {'dataDate': '20250216', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 786.1007}, {'dataDate': '20250216', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}]\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-16 5371.679688\n", - "Name: 日度预测价格, dtype: float32\n", - "20250217 \n", - "2025-02-17 00:00:00 \n", - "{'data': {'date': '20250217', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250217', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250217', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250217', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5270.0}, {'dataDate': '20250217', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250217', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250217', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250217', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250217', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4720.0}, {'dataDate': '20250217', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250217', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5520.0}, {'dataDate': '20250217', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250217', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250217', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5538.0}, {'dataDate': '20250217', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250217', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5505.0}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5300.0}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1158.2119}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250217', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250217', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250217', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5180.0}, {'dataDate': '20250217', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250217', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8300.0}, {'dataDate': '20250217', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5800.0}]\n", - "{'dataDate': '20250217', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250217', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-17 5310.317383\n", - "Name: 日度预测价格, dtype: float32\n", - "20250218 \n", - "2025-02-18 00:00:00 \n", - "{'data': {'date': '20250218', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250218', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250218', 'dataItemNo': '251926669|STRIKE_PRICE', 'dataValue': 5480.0}, {'dataDate': '20250218', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5270.0}, {'dataDate': '20250218', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250218', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250218', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250218', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250218', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4690.0}, {'dataDate': '20250218', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250218', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5630.0}, {'dataDate': '20250218', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250218', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250218', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5588.0}, {'dataDate': '20250218', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250218', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5585.0}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1308.9073}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250218', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250218', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250218', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5220.0}, {'dataDate': '20250218', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250218', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250218', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5775.0}]\n", - "{'dataDate': '20250218', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250218', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-18 5466.825195\n", - "Name: 日度预测价格, dtype: float32\n", - "20250219 \n", - "2025-02-19 00:00:00 \n", - "{'data': {'date': '20250219', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250219', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250219', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250219', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250219', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250219', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250219', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250219', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4690.0}, {'dataDate': '20250219', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250219', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250219', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250219', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250219', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5668.0}, {'dataDate': '20250219', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250219', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5665.0}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5550.0}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1600.0196}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250219', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250219', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250219', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5220.0}, {'dataDate': '20250219', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250219', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250219', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5750.0}]\n", - "{'dataDate': '20250219', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250219', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-19 5479.943848\n", - "Name: 日度预测价格, dtype: float32\n", - "20250220 \n", - "2025-02-20 00:00:00 \n", - "{'data': {'date': '20250220', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250220', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250220', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5340.0}, {'dataDate': '20250220', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250220', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250220', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250220', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250220', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4770.0}, {'dataDate': '20250220', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250220', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250220', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250220', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250220', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5668.0}, {'dataDate': '20250220', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250220', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5665.0}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5550.0}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1471.9223}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250220', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250220', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250220', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5230.0}, {'dataDate': '20250220', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250220', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8500.0}, {'dataDate': '20250220', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5750.0}]\n", - "{'dataDate': '20250220', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250220', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-20 5478.131348\n", - "Name: 日度预测价格, dtype: float32\n", - "20250221 \n", - "2025-02-21 00:00:00 \n", - "{'data': {'date': '20250221', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250221', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8674.0}, {'dataDate': '20250221', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5340.0}, {'dataDate': '20250221', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250221', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250221', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250221', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250221', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4770.0}, {'dataDate': '20250221', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250221', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5700.0}, {'dataDate': '20250221', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5650.0}, {'dataDate': '20250221', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 300.0}, {'dataDate': '20250221', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5668.0}, {'dataDate': '20250221', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250221', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5665.0}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1313.0783}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|PLAN_SALE'}, {'dataDate': '20250221', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250221', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250221', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5240.0}, {'dataDate': '20250221', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250221', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250221', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5875.0}]\n", - "{'dataDate': '20250221', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", - "{'dataDate': '20250221', 'dataItemNo': 'C01100008|PLAN_SALE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-21 5482.609375\n", - "Name: 日度预测价格, dtype: float32\n", - "20250222 \n", - "2025-02-22 00:00:00 \n", - "{'data': {'date': '20250222', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250222', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8593.0}, {'dataDate': '20250222', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250222', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE', 'dataValue': 0.0}, {'dataDate': '20250222', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250222', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250222', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4770.0}, {'dataDate': '20250222', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250222', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250222', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250222', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250222', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5618.0}, {'dataDate': '20250222', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250222', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5605.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1043.6716}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 700.0}, {'dataDate': '20250222', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250222', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250222', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250222', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6850.0}]\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-22 5422.866211\n", - "Name: 日度预测价格, dtype: float32\n", - "20250223 \n", - "2025-02-23 00:00:00 \n", - "{'data': {'date': '20250223', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250223', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8513.0}, {'dataDate': '20250223', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250223', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250223', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5450.0}, {'dataDate': '20250223', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250223', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4770.0}, {'dataDate': '20250223', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250223', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250223', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5550.0}, {'dataDate': '20250223', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250223', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5568.0}, {'dataDate': '20250223', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250223', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5555.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5400.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1127.7162}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 400.0}, {'dataDate': '20250223', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250223', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250223', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250223', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 6850.0}]\n", - "{'dataDate': '20250223', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-23 5481.371094\n", - "Name: 日度预测价格, dtype: float32\n", - "20250224 \n", - "2025-02-24 00:00:00 \n", - "{'data': {'date': '20250224', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", - "[{'dataDate': '20250224', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8513.0}, {'dataDate': '20250224', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250224', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250224', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250224', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250224', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250224', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4670.0}, {'dataDate': '20250224', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250224', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250224', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250224', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250224', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5488.0}, {'dataDate': '20250224', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250224', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5455.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5400.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1218.5774}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 400.0}, {'dataDate': '20250224', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250224', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250224', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5200.0}, {'dataDate': '20250224', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250224', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8300.0}, {'dataDate': '20250224', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 5900.0}]\n", - "{'dataDate': '20250224', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:293: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:295: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using matplotlib backend: QtAgg\n", - "%pylab is deprecated, use %matplotlib inline and import the required libraries.\n", - "Populating the interactive namespace from numpy and matplotlib\n", - "Fitting 3 folds for each of 180 candidates, totalling 540 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:241: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:243: UserWarning:\n", - "\n", - "The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n", - "\n", - "C:\\Users\\EDY\\AppData\\Local\\Temp\\ipykernel_10368\\3326068263.py:275: FutureWarning:\n", - "\n", - "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Date\n", - "2025-02-24 5480.000488\n", - "Name: 日度预测价格, dtype: float32\n", - "[5410.65, 5494.33, 5552.84, 5574.33, 5400.61, 5392.52, 5405.63, 5423.53, 5480.07, 5421.19, 5389.24, 5337.03, 5371.68, 5310.32, 5466.83, 5479.94, 5478.13, 5482.61, 5422.87, 5481.37, 5480.0]\n" + "20250225 \n", + "2025-02-25 00:00:00 \n", + "{'data': {'date': '20250225', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", + "[{'dataDate': '20250225', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8513.0}, {'dataDate': '20250225', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250225', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250225', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250225', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250225', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250225', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4670.0}, {'dataDate': '20250225', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250225', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250225', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250225', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250225', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5488.0}, {'dataDate': '20250225', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250225', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5455.0}, {'dataDate': '20250225', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250225', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5400.0}, {'dataDate': '20250225', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 1102.7538}, {'dataDate': '20250225', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250225', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 400.0}, {'dataDate': '20250225', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250225', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250225', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5210.0}, {'dataDate': '20250225', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250225', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8350.0}, {'dataDate': '20250225', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6000.0}]\n", + "{'dataDate': '20250225', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", + "20250226 \n", + "2025-02-26 00:00:00 \n", + "{'data': {'date': '20250226', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", + "[{'dataDate': '20250226', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8513.0}, {'dataDate': '20250226', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250226', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250226', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250226', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250226', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250226', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4670.0}, {'dataDate': '20250226', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250226', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250226', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250226', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250226', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5488.0}, {'dataDate': '20250226', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250226', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5455.0}, {'dataDate': '20250226', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250226', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5400.0}, {'dataDate': '20250226', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 973.1879}, {'dataDate': '20250226', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250226', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 400.0}, {'dataDate': '20250226', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250226', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250226', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250226', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250226', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8300.0}, {'dataDate': '20250226', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6000.0}]\n", + "{'dataDate': '20250226', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", + "20250227 \n", + "2025-02-27 00:00:00 \n", + "{'data': {'date': '20250227', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", + "[{'dataDate': '20250227', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8441.0}, {'dataDate': '20250227', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5340.0}, {'dataDate': '20250227', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250227', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250227', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5350.0}, {'dataDate': '20250227', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250227', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4670.0}, {'dataDate': '20250227', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250227', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250227', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250227', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250227', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5488.0}, {'dataDate': '20250227', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250227', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5455.0}, {'dataDate': '20250227', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250227', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5480.0}, {'dataDate': '20250227', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': 698.2293}, {'dataDate': '20250227', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250227', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 600.0}, {'dataDate': '20250227', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250227', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250227', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250227', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250227', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8300.0}, {'dataDate': '20250227', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6000.0}]\n", + "{'dataDate': '20250227', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", + "20250228 \n", + "2025-02-28 00:00:00 \n", + "{'data': {'date': '20250228', 'dataItemNoList': ['251926669|STRIKE_PRICE', 'C01100008|CORTED_VALUE', 'C01100008|AUCTION_MAX_PRICE', 'C01100008|YEDAY_AMOUNT', 'ICE_CL0_LAST_YEDAY_PRICE\\n', '100028046|LISTING_PRICE', 'C01100008|PLAN_SALE', '91370200163576944B|C01100008|STRIKE_PRICE', '9137078672073757X8|C01100008|STRIKE_PRICE', '91370500674526498A|C01100008|STRIKE_PRICE', '91370305773165341A|C01100008|STRIKE_PRICE', '91370521164880008P|C01100008|STRIKE_PRICE', '91370321164425136B|C01100008|STRIKE_PRICE', 'SD|GC|ZDW|LIST_PRICE', '370500|ISOBUTANE|LIST_PRICE', 'SD|YT|SG|LIST_PRICE', '91110000710926094P|C01100008|SUPPLY_MERE', '91110000710932515R|C01100008|SUPPLY_MERE', '91370500674526498A|C01100008|SUPPLY_MERE', '91370321164425136B|C01100008|SUPPLY_MERE', 'C01100008|OTHER|SUPPLY_MERE', 'SD|WJH|DEMANDS', 'C01100008|SUY_DED_DAP', 'C01100008|EFFECTIVE_STOCK', '912102117169477344|C01100008|STRIKE_PRICE', '91110304102767480H|C01100008|STRIKE_PRICE', '91130193670310403L|C01100008|STRIKE_PRICE', 'HD|LPG|IMPORT_PRICE', 'SD|WJH|SALES_PRICE']}, 'funcModule': '数据项', 'funcOperation': '查询'}\n", + "[{'dataDate': '20250228', 'dataItemNo': '100028046|LISTING_PRICE', 'dataValue': 8441.0}, {'dataDate': '20250228', 'dataItemNo': '370500|ISOBUTANE|LIST_PRICE', 'dataValue': 5380.0}, {'dataDate': '20250228', 'dataItemNo': '91110000710926094P|C01100008|SUPPLY_MERE', 'dataValue': 1300.0}, {'dataDate': '20250228', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}, {'dataDate': '20250228', 'dataItemNo': '91110304102767480H|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250228', 'dataItemNo': '91130193670310403L|C01100008|STRIKE_PRICE', 'dataValue': 5150.0}, {'dataDate': '20250228', 'dataItemNo': '912102117169477344|C01100008|STRIKE_PRICE', 'dataValue': 4670.0}, {'dataDate': '20250228', 'dataItemNo': '91370200163576944B|C01100008|STRIKE_PRICE', 'dataValue': 5300.0}, {'dataDate': '20250228', 'dataItemNo': '91370305773165341A|C01100008|STRIKE_PRICE', 'dataValue': 5600.0}, {'dataDate': '20250228', 'dataItemNo': '91370321164425136B|C01100008|STRIKE_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250228', 'dataItemNo': '91370321164425136B|C01100008|SUPPLY_MERE', 'dataValue': 200.0}, {'dataDate': '20250228', 'dataItemNo': '91370500674526498A|C01100008|STRIKE_PRICE', 'dataValue': 5488.0}, {'dataDate': '20250228', 'dataItemNo': '91370500674526498A|C01100008|SUPPLY_MERE', 'dataValue': 175.0}, {'dataDate': '20250228', 'dataItemNo': '91370521164880008P|C01100008|STRIKE_PRICE', 'dataValue': 5455.0}, {'dataDate': '20250228', 'dataItemNo': 'C01100008|AUCTION_MAX_PRICE', 'dataValue': 5500.0}, {'dataDate': '20250228', 'dataItemNo': 'C01100008|CORTED_VALUE', 'dataValue': 5500.0}, {'dataDate': '20250228', 'dataItemNo': 'C01100008|EFFECTIVE_STOCK', 'dataValue': -550.2}, {'dataDate': '20250228', 'dataItemNo': 'C01100008|OTHER|SUPPLY_MERE', 'dataValue': 5000.0}, {'dataDate': '20250228', 'dataItemNo': 'C01100008|PLAN_SALE', 'dataValue': 500.0}, {'dataDate': '20250228', 'dataItemNo': 'C01100008|SUY_DED_DAP', 'dataValue': -50.0}, {'dataDate': '20250228', 'dataItemNo': 'HD|LPG|IMPORT_PRICE', 'dataValue': 5400.0}, {'dataDate': '20250228', 'dataItemNo': 'SD|GC|ZDW|LIST_PRICE', 'dataValue': 5250.0}, {'dataDate': '20250228', 'dataItemNo': 'SD|WJH|DEMANDS', 'dataValue': 8500.0}, {'dataDate': '20250228', 'dataItemNo': 'SD|WJH|SALES_PRICE', 'dataValue': 8400.0}, {'dataDate': '20250228', 'dataItemNo': 'SD|YT|SG|LIST_PRICE', 'dataValue': 6050.0}]\n", + "{'dataDate': '20250228', 'dataItemNo': '91110000710932515R|C01100008|SUPPLY_MERE'}\n", + "[]\n" ] } ], "source": [ - "start_date = datetime(2025, 2, 4)\n", - "end_date = datetime(2025, 2, 25)\n", + "start_date = datetime(2025, 2, 25)\n", + "end_date = datetime(2025, 3, 1)\n", "\n", "while start_date < end_date:\n", " date = start_date.strftime('%Y%m%d')\n", diff --git a/aisenzhecode/液化石油气/液化气数据.xls b/aisenzhecode/液化石油气/液化气数据.xls index cf91e1c86307a804e2189b4002cc67cf17fa889a..9f177cd7be1a096851d5e7f1534a7bfa42f4d39d 100644 GIT binary patch delta 1032 zcma*lO=uHA6ae72FU{tsVBJ_X7E&!(R7@pVNELrTibC*aqlX?8QHnqGB)#ZmXC?$u zj1Y2Is5eo>i-;**qeMk8Dqc)L5WGr3j~-^~7G3!%7&$Go?1X7<||wmi(1ho9}m zLxa02F_k;e;>(Z~CM9vwejh~aZqj@uD z7N&CMlvzju1j%$bIT%h3*_}3?syFwK#mcl8z_@+%12)Rl?5%26bE;W9u%yRvGgw%k zc(Nr;JqD~$)KI6IMp+9|VA)^Z<| zsbg)-?74PYHY}B7e0NU9*-;tYeNr@P!ES1195ePv6O)%MOjC9B>Ew^dk=k+f7I#o( zt=L~FIV;C|?#uW9nXDP`!jthp#u2Ih;H>|LBJi621IHng%KjO0 zC0#A6ri9<>o*@sUJS@FF@C3O3MFJDh5bp&48vS6@gSJ>2D>K z(UpqzQW27NV{)M`T^?5|0;vc~Q|eybIWL?0w^ex3A_yhjbhy{+8BluohvHh%ezTx$ e!SRNv^vMoPtea;r{bUj;)?@$zHiqDg)YKBgRt9;7t4Ag; zWmRO|$;800ZS!eXSp~+{%`a6uS*ItRW^$kWR$Gd(zL`U(okNFlJBJR_^I6+HPcv<2 a+rHrpQy 0: - set_clause = ", ".join([f"{key} = '{value}'" for key, value in row_dict.items()]) - sqlitedb.update_data('trueandpredict', set_clause, where_condition=f"ds = '{row.ds}'") + set_clause = ", ".join( + [f"{key} = '{value}'" for key, value in row_dict.items()]) + sqlitedb.update_data( + 'trueandpredict', set_clause, where_condition=f"ds = '{row.ds}'") continue - sqlitedb.insert_data('trueandpredict', tuple(row_dict.values()), columns=row_dict.keys()) + sqlitedb.insert_data('trueandpredict', tuple( + row_dict.values()), columns=row_dict.keys()) # 更新accuracy表的y值 if not sqlitedb.check_table_exists('accuracy'): pass else: - update_y = sqlitedb.select_data('accuracy',where_condition="y is null") + update_y = sqlitedb.select_data( + 'accuracy', where_condition="y is null") if len(update_y) > 0: logger.info('更新accuracy表的y值') # 找到update_y 中ds且df中的y的行 - update_y = update_y[update_y['ds']<=end_time] + update_y = update_y[update_y['ds'] <= end_time] logger.info(f'要更新y的信息：{update_y}') # try: for row in update_y.itertuples(index=False): try: - row_dict = row._asdict() - yy = df[df['ds']==row_dict['ds']]['y'].values[0] - LOW = df[df['ds']==row_dict['ds']]['Brentzdj'].values[0] - HIGH = df[df['ds']==row_dict['ds']]['Brentzgj'].values[0] - sqlitedb.update_data('accuracy', f"y = {yy},LOW_PRICE = {LOW},HIGH_PRICE = {HIGH}", where_condition=f"ds = '{row_dict['ds']}'") + row_dict = row._asdict() + yy = df[df['ds'] == row_dict['ds']]['y'].values[0] + LOW = df[df['ds'] == row_dict['ds']]['Brentzdj'].values[0] + HIGH = df[df['ds'] == row_dict['ds']]['Brentzgj'].values[0] + sqlitedb.update_data( + 'accuracy', f"y = {yy},LOW_PRICE = {LOW},HIGH_PRICE = {HIGH}", where_condition=f"ds = '{row_dict['ds']}'") except: logger.info(f'更新accuracy表的y值失败：{row_dict}') # except Exception as e: # logger.info(f'更新accuracy表的y值失败：{e}') - import datetime # 判断当前日期是不是周一 is_weekday = datetime.datetime.now().weekday() == 0 if is_weekday: logger.info('今天是周一，更新预测模型') # 计算最近60天预测残差最低的模型名称 - model_results = sqlitedb.select_data('trueandpredict', order_by="ds DESC", limit="60") + model_results = sqlitedb.select_data( + 'trueandpredict', order_by="ds DESC", limit="60") # 删除空值率为90%以上的列 if len(model_results) > 10: - model_results = model_results.dropna(thresh=len(model_results)*0.1,axis=1) + model_results = model_results.dropna( + thresh=len(model_results)*0.1, axis=1) # 删除空行 model_results = model_results.dropna() modelnames = model_results.columns.to_list()[2:-1] @@ -172,51 +245,61 @@ def predict_main(): model_results[col] = model_results[col].astype(np.float32) # 计算每个预测值与真实值之间的偏差率 for model in modelnames: - model_results[f'{model}_abs_error_rate'] = abs(model_results['y'] - model_results[model]) / model_results['y'] + model_results[f'{model}_abs_error_rate'] = abs( + model_results['y'] - model_results[model]) / model_results['y'] # 获取每行对应的最小偏差率值 - min_abs_error_rate_values = model_results.apply(lambda row: row[[f'{model}_abs_error_rate' for model in modelnames]].min(), axis=1) + min_abs_error_rate_values = model_results.apply( + lambda row: row[[f'{model}_abs_error_rate' for model in modelnames]].min(), axis=1) # 获取每行对应的最小偏差率值对应的列名 - min_abs_error_rate_column_name = model_results.apply(lambda row: row[[f'{model}_abs_error_rate' for model in modelnames]].idxmin(), axis=1) + min_abs_error_rate_column_name = model_results.apply( + lambda row: row[[f'{model}_abs_error_rate' for model in modelnames]].idxmin(), axis=1) # 将列名索引转换为列名 - min_abs_error_rate_column_name = min_abs_error_rate_column_name.map(lambda x: x.split('_')[0]) + min_abs_error_rate_column_name = min_abs_error_rate_column_name.map( + lambda x: x.split('_')[0]) # 取出现次数最多的模型名称 most_common_model = min_abs_error_rate_column_name.value_counts().idxmax() logger.info(f"最近60天预测残差最低的模型名称：{most_common_model}") # 保存结果到数据库 if not sqlitedb.check_table_exists('most_model'): - sqlitedb.create_table('most_model', columns="ds datetime, most_common_model TEXT") - sqlitedb.insert_data('most_model', (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'), most_common_model,), columns=('ds', 'most_common_model',)) + sqlitedb.create_table( + 'most_model', columns="ds datetime, most_common_model TEXT") + sqlitedb.insert_data('most_model', (datetime.datetime.now().strftime( + '%Y-%m-%d %H:%M:%S'), most_common_model,), columns=('ds', 'most_common_model',)) try: - # if is_weekday: - if True: - # logger.info('今天是周一，发送特征预警') - # # 上传预警信息到数据库 - # warning_data_df = df_zhibiaoliebiao.copy() - # warning_data_df = warning_data_df[warning_data_df['停更周期']> 3 ][['指标名称', '指标id', '频度','更新周期','指标来源','最后更新时间','停更周期']] - # # 重命名列名 - # warning_data_df = warning_data_df.rename(columns={'指标名称': 'INDICATOR_NAME', '指标id': 'INDICATOR_ID', '频度': 'FREQUENCY', '更新周期': 'UPDATE_FREQUENCY', '指标来源': 'DATA_SOURCE', '最后更新时间': 'LAST_UPDATE_DATE', '停更周期': 'UPDATE_SUSPENSION_CYCLE'}) - # from sqlalchemy import create_engine - # import urllib - # global password - # if '@' in password: - # password = urllib.parse.quote_plus(password) + if is_weekday: + # if True: + logger.info('今天是周一，发送特征预警') + # 上传预警信息到数据库 + warning_data_df = df_zhibiaoliebiao.copy() + warning_data_df = warning_data_df[warning_data_df['停更周期'] > 3][[ + '指标名称', '指标id', '频度', '更新周期', '指标来源', '最后更新时间', '停更周期']] + # 重命名列名 + warning_data_df = warning_data_df.rename(columns={'指标名称': 'INDICATOR_NAME', '指标id': 'INDICATOR_ID', '频度': 'FREQUENCY', + '更新周期': 'UPDATE_FREQUENCY', '指标来源': 'DATA_SOURCE', '最后更新时间': 'LAST_UPDATE_DATE', '停更周期': 'UPDATE_SUSPENSION_CYCLE'}) + from sqlalchemy import create_engine + import urllib + global password + if '@' in password: + password = urllib.parse.quote_plus(password) - # engine = create_engine(f'mysql+pymysql://{dbusername}:{password}@{host}:{port}/{dbname}') - # warning_data_df['WARNING_DATE'] = datetime.date.today().strftime("%Y-%m-%d %H:%M:%S") - # warning_data_df['TENANT_CODE'] = 'T0004' - # # 插入数据之前查询表数据然后新增id列 - # existing_data = pd.read_sql(f"SELECT * FROM {table_name}", engine) - # if not existing_data.empty: - # max_id = existing_data['ID'].astype(int).max() - # warning_data_df['ID'] = range(max_id + 1, max_id + 1 + len(warning_data_df)) - # else: - # warning_data_df['ID'] = range(1, 1 + len(warning_data_df)) - # warning_data_df.to_sql(table_name, con=engine, if_exists='append', index=False) - # if is_update_warning_data: - # upload_warning_info(len(warning_data_df)) + engine = create_engine( + f'mysql+pymysql://{dbusername}:{password}@{host}:{port}/{dbname}') + warning_data_df['WARNING_DATE'] = datetime.date.today().strftime( + "%Y-%m-%d %H:%M:%S") + warning_data_df['TENANT_CODE'] = 'T0004' + # 插入数据之前查询表数据然后新增id列 + existing_data = pd.read_sql(f"SELECT * FROM {table_name}", engine) + if not existing_data.empty: + max_id = existing_data['ID'].astype(int).max() + warning_data_df['ID'] = range( + max_id + 1, max_id + 1 + len(warning_data_df)) + else: + warning_data_df['ID'] = range(1, 1 + len(warning_data_df)) + warning_data_df.to_sql( + table_name, con=engine, if_exists='append', index=False) if is_update_warning_data: - upload_warning_info(10) + upload_warning_info(len(warning_data_df)) except: logger.info('上传预警信息到数据库失败') @@ -228,76 +311,75 @@ def predict_main(): row, col = df.shape now = datetime.datetime.now().strftime('%Y%m%d%H%M%S') - # ex_Model_Juxiting(df, - # horizon=horizon, - # input_size=input_size, - # train_steps=train_steps, - # val_check_steps=val_check_steps, - # early_stop_patience_steps=early_stop_patience_steps, - # is_debug=is_debug, - # dataset=dataset, - # is_train=is_train, - # is_fivemodels=is_fivemodels, - # val_size=val_size, - # test_size=test_size, - # settings=settings, - # now=now, - # etadata=etadata, - # modelsindex=modelsindex, - # data=data, - # is_eta=is_eta, - # end_time=end_time, - # ) - + ex_Model(df, + horizon=global_config['horizon'], + input_size=global_config['input_size'], + train_steps=global_config['train_steps'], + val_check_steps=global_config['val_check_steps'], + early_stop_patience_steps=global_config['early_stop_patience_steps'], + is_debug=global_config['is_debug'], + dataset=global_config['dataset'], + is_train=global_config['is_train'], + is_fivemodels=global_config['is_fivemodels'], + val_size=global_config['val_size'], + test_size=global_config['test_size'], + settings=global_config['settings'], + now=now, + etadata=global_config['etadata'], + modelsindex=global_config['modelsindex'], + data=data, + is_eta=global_config['is_eta'], + end_time=global_config['end_time'], + ) logger.info('模型训练完成') - + logger.info('训练数据绘图ing') - model_results3 = model_losss_juxiting(sqlitedb) + model_results3 = model_losss(sqlitedb, end_time=end_time) logger.info('训练数据绘图end') - - # 模型报告 - logger.info('制作报告ing') - title = f'{settings}--{end_time}-预测报告' # 报告标题 - reportname = f'PP大模型预测报告--{end_time}.pdf' # 报告文件名 - reportname = reportname.replace(':', '-') # 替换冒号 - pp_export_pdf(dataset=dataset,num_models = 5 if is_fivemodels else 22,time=end_time, - reportname=reportname,sqlitedb=sqlitedb), - logger.info('制作报告end') - logger.info('模型训练完成') + # # 模型报告 + # logger.info('制作报告ing') + # title = f'{settings}--{end_time}-预测报告' # 报告标题 + # reportname = f'Brent原油大模型月度预测--{end_time}.pdf' # 报告文件名 + # reportname = reportname.replace(':', '-') # 替换冒号 + # brent_export_pdf(dataset=dataset, num_models=5 if is_fivemodels else 22, time=end_time, + # reportname=reportname, sqlitedb=sqlitedb), + + # logger.info('制作报告end') + # logger.info('模型训练完成') # # LSTM 单变量模型 # ex_Lstm(df,input_seq_len=input_size,output_seq_len=horizon,is_debug=is_debug,dataset=dataset) - + # # lstm 多变量模型 # ex_Lstm_M(df,n_days=input_size,out_days=horizon,is_debug=is_debug,datasetpath=dataset) - + # # GRU 模型 # # ex_GRU(df) # 发送邮件 - m = SendMail( - username=username, - passwd=passwd, - recv=recv, - title=title, - content=content, - file=max(glob.glob(os.path.join(dataset,'*.pdf')), key=os.path.getctime), - ssl=ssl, - ) - # m.send_mail() + # m = SendMail( + # username=username, + # passwd=passwd, + # recv=recv, + # title=title, + # content=content, + # file=max(glob.glob(os.path.join(dataset,'*.pdf')), key=os.path.getctime), + # ssl=ssl, + # ) + # m.send_mail() if __name__ == '__main__': # global end_time - # is_on = True - # # 遍历2024-11-25 到 2024-12-3 之间的工作日日期 - # for i_time in pd.date_range('2025-1-20', '2025-2-6', freq='B'): - # end_time = i_time.strftime('%Y-%m-%d') + # 遍历2024-11-25 到 2024-12-3 之间的工作日日期 + # for i_time in pd.date_range('2022-1-1', '2025-3-26', freq='M'): # try: + # global_config['end_time'] = i_time.strftime('%Y-%m-%d') # predict_main() - # except: - # pass + # except Exception as e: + # logger.info(f'预测失败：{e}') + # continue - predict_main() \ No newline at end of file + predict_main() diff --git a/main_yuanyou_yuedu.py b/main_yuanyou_yuedu.py index d9b055b..c00a2b0 100644 --- a/main_yuanyou_yuedu.py +++ b/main_yuanyou_yuedu.py @@ -374,13 +374,12 @@ def predict_main(): if __name__ == '__main__': # global end_time # 遍历2024-11-25 到 2024-12-3 之间的工作日日期 - for i_time in pd.date_range('2022-1-1', '2025-3-26', freq='M'): - try: - global_config['end_time'] = i_time.strftime('%Y-%m-%d') - predict_main() - except Exception as e: - logger.info(f'预测失败：{e}') - continue + # for i_time in pd.date_range('2022-1-1', '2025-3-26', freq='M'): + # try: + # global_config['end_time'] = i_time.strftime('%Y-%m-%d') + # predict_main() + # except Exception as e: + # logger.info(f'预测失败：{e}') + # continue - - # predict_main() + predict_main()