{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path_888 = r\"E:\\data\\data_rs_merged\\中金所\\IM888\\IM888_rs_2023.csv\"\n",
    "df_888 = pd.read_csv(file_path_888, encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>main_contract</th>\n",
       "      <th>symbol</th>\n",
       "      <th>datetime</th>\n",
       "      <th>lastprice</th>\n",
       "      <th>volume</th>\n",
       "      <th>bid_p</th>\n",
       "      <th>ask_p</th>\n",
       "      <th>bid_v</th>\n",
       "      <th>ask_v</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IM888</td>\n",
       "      <td>IM2301</td>\n",
       "      <td>2023-01-03 09:30:00.200</td>\n",
       "      <td>6280.0</td>\n",
       "      <td>46</td>\n",
       "      <td>6276.0</td>\n",
       "      <td>6277.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IM888</td>\n",
       "      <td>IM2301</td>\n",
       "      <td>2023-01-03 09:30:00.700</td>\n",
       "      <td>6277.0</td>\n",
       "      <td>61</td>\n",
       "      <td>6278.0</td>\n",
       "      <td>6278.8</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>IM888</td>\n",
       "      <td>IM2301</td>\n",
       "      <td>2023-01-03 09:30:01.200</td>\n",
       "      <td>6277.2</td>\n",
       "      <td>81</td>\n",
       "      <td>6277.2</td>\n",
       "      <td>6278.8</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IM888</td>\n",
       "      <td>IM2301</td>\n",
       "      <td>2023-01-03 09:30:01.700</td>\n",
       "      <td>6277.8</td>\n",
       "      <td>90</td>\n",
       "      <td>6277.8</td>\n",
       "      <td>6278.6</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IM888</td>\n",
       "      <td>IM2301</td>\n",
       "      <td>2023-01-03 09:30:02.200</td>\n",
       "      <td>6278.8</td>\n",
       "      <td>112</td>\n",
       "      <td>6278.8</td>\n",
       "      <td>6280.0</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  main_contract  symbol                 datetime  lastprice  volume   bid_p  \\\n",
       "0         IM888  IM2301  2023-01-03 09:30:00.200     6280.0      46  6276.0   \n",
       "1         IM888  IM2301  2023-01-03 09:30:00.700     6277.0      61  6278.0   \n",
       "2         IM888  IM2301  2023-01-03 09:30:01.200     6277.2      81  6277.2   \n",
       "3         IM888  IM2301  2023-01-03 09:30:01.700     6277.8      90  6277.8   \n",
       "4         IM888  IM2301  2023-01-03 09:30:02.200     6278.8     112  6278.8   \n",
       "\n",
       "    ask_p  bid_v  ask_v  \n",
       "0  6277.0      1      3  \n",
       "1  6278.8      1     16  \n",
       "2  6278.8      1      5  \n",
       "3  6278.6      3      4  \n",
       "4  6280.0      1      7  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_888.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 重命名列以便处理\n",
    "# df_888.rename(columns={'时间': 'datetime', '最新': 'price', '成交量': 'volume'}, inplace=True)\n",
    "df_888.rename(columns={'datetime': 'datetime', 'lastprice': 'price', 'volume': 'volume'}, inplace=True)\n",
    "\n",
    "# 确保datetime列是datetime类型\n",
    "df_888['datetime'] = pd.to_datetime(df_888['datetime'])\n",
    "\n",
    "# 设置datetime列为索引\n",
    "df_888.set_index('datetime', inplace=True)\n",
    "\n",
    "# 使用resample方法将数据重新采样为1分钟数据\n",
    "df_resampled = df_888.resample('1T').agg({\n",
    "    'price': ['first', 'max', 'min', 'last'],\n",
    "    'volume': 'sum'\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">price</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>first</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "      <th>last</th>\n",
       "      <th>sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:30:00</th>\n",
       "      <td>6280.0</td>\n",
       "      <td>6306.4</td>\n",
       "      <td>6277.0</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>66894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:31:00</th>\n",
       "      <td>6302.0</td>\n",
       "      <td>6320.0</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>6318.8</td>\n",
       "      <td>172512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:32:00</th>\n",
       "      <td>6319.8</td>\n",
       "      <td>6328.0</td>\n",
       "      <td>6314.8</td>\n",
       "      <td>6314.8</td>\n",
       "      <td>238716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:33:00</th>\n",
       "      <td>6313.0</td>\n",
       "      <td>6325.0</td>\n",
       "      <td>6310.4</td>\n",
       "      <td>6312.4</td>\n",
       "      <td>297675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:34:00</th>\n",
       "      <td>6311.0</td>\n",
       "      <td>6323.2</td>\n",
       "      <td>6311.0</td>\n",
       "      <td>6319.4</td>\n",
       "      <td>352184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      price                          volume\n",
       "                      first     max     min    last     sum\n",
       "datetime                                                   \n",
       "2023-01-03 09:30:00  6280.0  6306.4  6277.0  6302.0   66894\n",
       "2023-01-03 09:31:00  6302.0  6320.0  6302.0  6318.8  172512\n",
       "2023-01-03 09:32:00  6319.8  6328.0  6314.8  6314.8  238716\n",
       "2023-01-03 09:33:00  6313.0  6325.0  6310.4  6312.4  297675\n",
       "2023-01-03 09:34:00  6311.0  6323.2  6311.0  6319.4  352184"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_resampled.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'IM888'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_888['main_contract'][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_resampled['symbol'] = df_888['main_contract'][1]\n",
    "df_resampled.insert(0, 'symbol', df_888['main_contract'][1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th colspan=\"4\" halign=\"left\">price</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>first</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "      <th>last</th>\n",
       "      <th>sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:30:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6280.0</td>\n",
       "      <td>6306.4</td>\n",
       "      <td>6277.0</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>66894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:31:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>6320.0</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>6318.8</td>\n",
       "      <td>172512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:32:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6319.8</td>\n",
       "      <td>6328.0</td>\n",
       "      <td>6314.8</td>\n",
       "      <td>6314.8</td>\n",
       "      <td>238716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:33:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6313.0</td>\n",
       "      <td>6325.0</td>\n",
       "      <td>6310.4</td>\n",
       "      <td>6312.4</td>\n",
       "      <td>297675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:34:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6311.0</td>\n",
       "      <td>6323.2</td>\n",
       "      <td>6311.0</td>\n",
       "      <td>6319.4</td>\n",
       "      <td>352184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    symbol   price                          volume\n",
       "                             first     max     min    last     sum\n",
       "datetime                                                          \n",
       "2023-01-03 09:30:00  IM888  6280.0  6306.4  6277.0  6302.0   66894\n",
       "2023-01-03 09:31:00  IM888  6302.0  6320.0  6302.0  6318.8  172512\n",
       "2023-01-03 09:32:00  IM888  6319.8  6328.0  6314.8  6314.8  238716\n",
       "2023-01-03 09:33:00  IM888  6313.0  6325.0  6310.4  6312.4  297675\n",
       "2023-01-03 09:34:00  IM888  6311.0  6323.2  6311.0  6319.4  352184"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_resampled.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 重命名列名以符合K线数据的标准命名\n",
    "df_resampled.columns = ['open', 'high', 'low', 'close', 'volume', 'symbol']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:30:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6280.0</td>\n",
       "      <td>6306.4</td>\n",
       "      <td>6277.0</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>66894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:31:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>6320.0</td>\n",
       "      <td>6302.0</td>\n",
       "      <td>6318.8</td>\n",
       "      <td>172512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:32:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6319.8</td>\n",
       "      <td>6328.0</td>\n",
       "      <td>6314.8</td>\n",
       "      <td>6314.8</td>\n",
       "      <td>238716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:33:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6313.0</td>\n",
       "      <td>6325.0</td>\n",
       "      <td>6310.4</td>\n",
       "      <td>6312.4</td>\n",
       "      <td>297675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03 09:34:00</th>\n",
       "      <td>IM888</td>\n",
       "      <td>6311.0</td>\n",
       "      <td>6323.2</td>\n",
       "      <td>6311.0</td>\n",
       "      <td>6319.4</td>\n",
       "      <td>352184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      open    high     low   close  volume  symbol\n",
       "datetime                                                          \n",
       "2023-01-03 09:30:00  IM888  6280.0  6306.4  6277.0  6302.0   66894\n",
       "2023-01-03 09:31:00  IM888  6302.0  6320.0  6302.0  6318.8  172512\n",
       "2023-01-03 09:32:00  IM888  6319.8  6328.0  6314.8  6314.8  238716\n",
       "2023-01-03 09:33:00  IM888  6313.0  6325.0  6310.4  6312.4  297675\n",
       "2023-01-03 09:34:00  IM888  6311.0  6323.2  6311.0  6319.4  352184"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_resampled.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1分钟历史数据已保存至E:\\data\\data_rs_merged\\中金所\\IM888\\IM888_rs_2023_1min.csv\n"
     ]
    }
   ],
   "source": [
    "# 删除存在NA值的行（如果有的时间段没有交易数据）\n",
    "df_resampled.dropna(inplace=True)\n",
    "# df_resampled['symbol'] = df_888['统一代码']\n",
    "# df_resampled.insert(loc=0, column='main_contract', value=df_888['main_contract'])\n",
    "# df_resampled['symbol'] = df_888['main_contract']\n",
    "# 将重新采样的数据写入新的CSV文件\n",
    "output_file = r\"E:\\data\\data_rs_merged\\中金所\\IM888\\IM888_rs_2023_1min.csv\"\n",
    "df_resampled.to_csv(output_file)\n",
    "\n",
    "print(f'1分钟历史数据已保存至{output_file}')"
   ]
  }
 ],
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