2908 lines
257 KiB
Plaintext
2908 lines
257 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"id": "initial_id",
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"metadata": {
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"collapsed": true,
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"ExecuteTime": {
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"end_time": "2025-02-19T14:44:47.980877Z",
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"start_time": "2025-02-19T14:44:47.977369Z"
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}
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},
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"source": [
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"import pandas as pd\n",
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"import platform\n",
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"import os\n",
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"\n",
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"root_path = \"C:\\\\Users\\\\lanyuanxiaoyao\\\\SynologyDrive\\\\data\\\\Tushare\" \\\n",
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" if platform.processor().startswith(\"AMD\") \\\n",
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" else \"/Users/lanyuanxiaoyao/SynologyDrive/data/Tushare\""
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],
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"outputs": [],
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"execution_count": 47
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-02-19T14:44:48.019179Z",
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"start_time": "2025-02-19T14:44:48.014177Z"
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}
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},
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"cell_type": "code",
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"source": [
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"def load_stock(code):\n",
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" source_df = pd.read_csv(os.path.join(root_path, \"日线行情 1990-2024\", \"分组行情\", f\"{code}.csv\")) \\\n",
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" [[\"trade_date\", \"vol\", \"open_qfq\", \"close_qfq\", \"high_qfq\", \"low_qfq\"]]\n",
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" temp_df = pd.DataFrame()\n",
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" temp_df[[\"date\", \"Volume\", \"Open\", \"Close\", \"High\", \"Low\"]] = \\\n",
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" source_df[[\"trade_date\", \"vol\", \"open_qfq\", \"close_qfq\", \"high_qfq\", \"low_qfq\"]]\n",
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" temp_df[\"datetime\"] = pd.to_datetime(temp_df[\"date\"], format=\"%Y%m%d\")\n",
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" temp_df[\"datetime_text\"] = temp_df[\"datetime\"].apply(lambda x: x.strftime(\"%Y%m%d\"))\n",
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" temp_df = temp_df[temp_df[\"datetime\"].dt.year > 2023]\n",
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" temp_df.sort_values(by='datetime', inplace=True)\n",
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" temp_df.set_index('datetime', inplace=True)\n",
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" return temp_df"
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],
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"id": "414a7a0a199096a2",
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"outputs": [],
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"execution_count": 48
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-02-19T14:44:48.086771Z",
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"start_time": "2025-02-19T14:44:48.043313Z"
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}
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},
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"cell_type": "code",
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"source": "df = load_stock(\"000001.SZ\")",
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"id": "bdcc7bfcec324577",
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"outputs": [],
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"execution_count": 49
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-02-19T14:44:48.094953Z",
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"start_time": "2025-02-19T14:44:48.090778Z"
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}
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},
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"cell_type": "code",
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"source": [
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"def translate_metrics(data):\n",
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" \"\"\"\n",
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" 将 Pandas Series 中的指标名称翻译为中文并打印结果。\n",
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"\n",
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" 参数:\n",
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" data (pd.Series or pd.DataFrame): 包含指标的 Pandas 数据结构。\n",
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" \"\"\"\n",
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" # 翻译字典\n",
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" translation = {\n",
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" \"Start\": \"开始日期\",\n",
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" \"End\": \"结束日期\",\n",
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" \"Duration\": \"持续时间\",\n",
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" \"Exposure Time [%]\": \"有效时间\",\n",
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" \"Equity Final [$]\": \"最终权益\",\n",
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" \"Equity Peak [$]\": \"最高权益\",\n",
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" \"Commissions [$]\": \"佣金\",\n",
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" \"Return [%]\": \"回报率\",\n",
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" \"Buy & Hold Return [%]\": \"买并持有回报率\",\n",
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" \"Return (Ann.) [%]\": \"年化回报率\",\n",
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" \"Volatility (Ann.) [%]\": \"年化波动率\",\n",
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" \"CAGR [%]\": \"年复合增长率\",\n",
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" \"Sharpe Ratio\": \"夏普比率\",\n",
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" \"Sortino Ratio\": \"索提诺比率\",\n",
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" \"Calmar Ratio\": \"卡玛比率\",\n",
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" \"Max. Drawdown [%]\": \"最大回撤\",\n",
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" \"Avg. Drawdown [%]\": \"平均回撤\",\n",
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" \"Max. Drawdown Duration\": \"最长回撤时间\",\n",
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" \"Avg. Drawdown Duration\": \"平均回撤时间\",\n",
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" \"# Trades\": \"交易次数\",\n",
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" \"Win Rate [%]\": \"胜率\",\n",
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" \"Best Trade [%]\": \"最佳交易\",\n",
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" \"Worst Trade [%]\": \"最差交易\",\n",
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" \"Avg. Trade [%]\": \"平均交易\",\n",
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" \"Max. Trade Duration\": \"最长交易时间\",\n",
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" \"Avg. Trade Duration\": \"平均交易时间\",\n",
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" \"Profit Factor\": \"利润因子\",\n",
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" \"Expectancy [%]\": \"期望\",\n",
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" \"SQN\": \"系统质量系数\",\n",
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" \"Kelly Criterion\": \"凯利比率\"\n",
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" }\n",
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"\n",
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" # 如果是 Series\n",
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" if isinstance(data, pd.Series):\n",
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" for idx in range(len(data)):\n",
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" key = data.index[idx]\n",
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" value = data.iloc[idx]\n",
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" translated_key = translation.get(key, key)\n",
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" print(f\"{translated_key}: {value}\")\n",
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" else:\n",
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" raise ValueError(\"输入数据必须是 Pandas Series 或 DataFrame。\")"
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],
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"id": "f6e932667ad314ff",
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"outputs": [],
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||
"execution_count": 50
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||
},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-02-19T14:44:48.110292Z",
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"start_time": "2025-02-19T14:44:48.106357Z"
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}
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},
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"cell_type": "code",
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"source": [
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"from backtesting import Strategy\n",
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"from backtesting.lib import crossover\n",
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"import talib\n",
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"\n",
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"\n",
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"class MACDStrategy(Strategy):\n",
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" def init(self):\n",
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" self.dea, self.dif, self.macd = self.I(talib.MACD, self.data.Close, 12, 26, 9)\n",
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"\n",
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" def next(self):\n",
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" # print(self.position.size)\n",
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" if crossover(self.dif, self.dea) and self.macd > 0 and (self.dif > self.macd and self.dea > self.macd):\n",
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" print(\"buy\")\n",
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" self.buy()\n",
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" elif crossover(self.dea, self.dif):\n",
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" print(\"sell\")\n",
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" self.position.close()"
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],
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||
"id": "1b47368c3b916b9b",
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||
"outputs": [],
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||
"execution_count": 51
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||
},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-02-19T14:44:48.126801Z",
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"start_time": "2025-02-19T14:44:48.121801Z"
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||
}
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||
},
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||
"cell_type": "code",
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||
"source": [
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"class SMAStrategy(Strategy):\n",
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" def init(self):\n",
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" self.sma_fast = self.I(talib.SMA, self.data.Close, 14)\n",
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" self.sma_slow = self.I(talib.SMA, self.data.Close, 60)\n",
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"\n",
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" def next(self):\n",
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" if crossover(self.sma_fast, self.sma_slow):\n",
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" self.buy(size=100)\n",
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" elif crossover(self.sma_slow, self.sma_fast):\n",
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" self.position.close()"
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],
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"id": "85da7018d63adc0",
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||
"outputs": [],
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||
"execution_count": 52
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-02-19T14:52:01.326524Z",
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"start_time": "2025-02-19T14:52:01.155798Z"
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}
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||
},
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||
"cell_type": "code",
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||
"source": [
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"from backtesting import Backtest\n",
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"\n",
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"bt = Backtest(df, SMAStrategy, cash=10000, commission=.002, trade_on_close=True)\n",
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"result = bt.run()\n",
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"print(result.iloc[4])\n",
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"bt.plot()"
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],
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||
"id": "ab574b78805925e5",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"9824.765695999999\n"
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]
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},
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|
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||
"<div style=\"display: table;\"><div style=\"display: table-row;\"><div style=\"display: table-cell;\"><b title=\"bokeh.models.plots.GridPlot\">GridPlot</b>(</div><div style=\"display: table-cell;\">id = 'p10194', <span id=\"p10225\" style=\"cursor: pointer;\">…)</span></div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">align = 'auto',</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">aspect_ratio = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">children = [(figure(id='p9904', ...), 0, 0), (figure(id='p10003', ...), 1, 0), (figure(id='p9858', ...), 2, 0), (figure(id='p10060', ...), 3, 0)],</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">cols = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">context_menu = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">css_classes = [],</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">css_variables = {},</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">disabled = False,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">elements = [],</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">flow_mode = 'block',</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">height = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">height_policy = 'auto',</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_event_callbacks = {},</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_property_callbacks = {},</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">margin = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">max_height = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">max_width = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">min_height = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">min_width = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">name = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">resizable = False,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">rows = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">sizing_mode = 'stretch_width',</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">spacing = 0,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">styles = {},</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">stylesheets = [],</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">subscribed_events = PropertyValueSet(),</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">syncable = True,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">tags = [],</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">toolbar = Toolbar(id='p10193', ...),</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">toolbar_location = 'right',</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">visible = True,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">width = None,</div></div><div class=\"p10224\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">width_policy = 'auto')</div></div></div>\n",
|
||
"<script>\n",
|
||
"(function() {\n",
|
||
" let expanded = false;\n",
|
||
" const ellipsis = document.getElementById(\"p10225\");\n",
|
||
" ellipsis.addEventListener(\"click\", function() {\n",
|
||
" const rows = document.getElementsByClassName(\"p10224\");\n",
|
||
" for (let i = 0; i < rows.length; i++) {\n",
|
||
" const el = rows[i];\n",
|
||
" el.style.display = expanded ? \"none\" : \"table-row\";\n",
|
||
" }\n",
|
||
" ellipsis.innerHTML = expanded ? \"…)\" : \"‹‹‹\";\n",
|
||
" expanded = !expanded;\n",
|
||
" });\n",
|
||
"})();\n",
|
||
"</script>\n"
|
||
]
|
||
},
|
||
"execution_count": 56,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"execution_count": 56
|
||
},
|
||
{
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2025-02-19T15:01:49.262777Z",
|
||
"start_time": "2025-02-19T14:55:44.559148Z"
|
||
}
|
||
},
|
||
"cell_type": "code",
|
||
"source": [
|
||
"count = 0\n",
|
||
"success = 0\n",
|
||
"\n",
|
||
"for name in os.listdir(os.path.join(root_path, \"日线行情 1990-2024\", \"分组行情\")):\n",
|
||
" if name.endswith(\"SZ.csv\"):\n",
|
||
" stock_df = load_stock(name.replace(\".csv\", \"\"))\n",
|
||
" if stock_df.empty:\n",
|
||
" continue\n",
|
||
" bt = Backtest(stock_df, SMAStrategy, cash=10000, commission=.002, trade_on_close=True)\n",
|
||
" result = bt.run()\n",
|
||
" count += 1\n",
|
||
" final = result.iloc[4]\n",
|
||
" if final > 10000:\n",
|
||
" success += 1\n",
|
||
" print(f\"{name}: {result.iloc[4]} 胜率：{(success / count) * 100:.2f}%\")"
|
||
],
|
||
"id": "abcba3a2b27082af",
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"000001.SZ.csv: 9824.765695999999 胜率：0.00%\n",
|
||
"000002.SZ.csv: 9909.224 胜率：0.00%\n",
|
||
"000004.SZ.csv: 10158.748 胜率：33.33%\n",
|
||
"000005.SZ.csv: 10000.0 胜率：25.00%\n",
|
||
"000006.SZ.csv: 10244.208 胜率：40.00%\n",
|
||
"000007.SZ.csv: 10152.646 胜率：50.00%\n",
|
||
"000008.SZ.csv: 10040.732 胜率：57.14%\n",
|
||
"000009.SZ.csv: 9896.06 胜率：50.00%\n",
|
||
"000010.SZ.csv: 10075.912 胜率：55.56%\n",
|
||
"000011.SZ.csv: 9950.799048 胜率：50.00%\n",
|
||
"000012.SZ.csv: 9860.842931999998 胜率：45.45%\n",
|
||
"000014.SZ.csv: 10164.134 胜率：50.00%\n",
|
||
"000016.SZ.csv: 10314.526 胜率：53.85%\n",
|
||
"000017.SZ.csv: 9957.758 胜率：50.00%\n",
|
||
"000019.SZ.csv: 10018.503198 胜率：53.33%\n",
|
||
"000020.SZ.csv: 10113.974 胜率：56.25%\n",
|
||
"000021.SZ.csv: 9885.264262 胜率：52.94%\n",
|
||
"000023.SZ.csv: 10000.0 胜率：50.00%\n",
|
||
"000025.SZ.csv: 10069.527844 胜率：52.63%\n",
|
||
"000026.SZ.csv: 10148.226 胜率：55.00%\n",
|
||
"000027.SZ.csv: 9962.504 胜率：52.38%\n",
|
||
"000028.SZ.csv: 10168.498 胜率：54.55%\n",
|
||
"000029.SZ.csv: 10290.295999999998 胜率：56.52%\n",
|
||
"000030.SZ.csv: 10001.98 胜率：58.33%\n",
|
||
"000031.SZ.csv: 10022.404 胜率：60.00%\n",
|
||
"000032.SZ.csv: 10126.808 胜率：61.54%\n",
|
||
"000034.SZ.csv: 10855.441738 胜率：62.96%\n",
|
||
"000035.SZ.csv: 10015.058 胜率：64.29%\n",
|
||
"000036.SZ.csv: 10085.300000000001 胜率：65.52%\n",
|
||
"000037.SZ.csv: 10006.736 胜率：66.67%\n",
|
||
"000039.SZ.csv: 9940.668 胜率：64.52%\n",
|
||
"000040.SZ.csv: 9956.47 胜率：62.50%\n",
|
||
"000042.SZ.csv: 9907.178 胜率：60.61%\n",
|
||
"000045.SZ.csv: 10190.258 胜率：61.76%\n",
|
||
"000048.SZ.csv: 10127.17092 胜率：62.86%\n",
|
||
"000049.SZ.csv: 9735.124 胜率：61.11%\n",
|
||
"000050.SZ.csv: 10084.366 胜率：62.16%\n",
|
||
"000055.SZ.csv: 9953.573828 胜率：60.53%\n",
|
||
"000056.SZ.csv: 10092.64 胜率：61.54%\n",
|
||
"000058.SZ.csv: 10218.834 胜率：62.50%\n",
|
||
"000059.SZ.csv: 9993.034 胜率：60.98%\n",
|
||
"000060.SZ.csv: 9983.046 胜率：59.52%\n",
|
||
"000061.SZ.csv: 10168.938 胜率：60.47%\n",
|
||
"000062.SZ.csv: 11370.720175999999 胜率：61.36%\n",
|
||
"000063.SZ.csv: 10629.793006 胜率：62.22%\n",
|
||
"000065.SZ.csv: 9923.795999999998 胜率：60.87%\n",
|
||
"000066.SZ.csv: 10592.274 胜率：61.70%\n",
|
||
"000068.SZ.csv: 10040.412 胜率：62.50%\n",
|
||
"000069.SZ.csv: 9968.894 胜率：61.22%\n",
|
||
"000070.SZ.csv: 10124.1 胜率：62.00%\n",
|
||
"000078.SZ.csv: 9959.516 胜率：60.78%\n",
|
||
"000088.SZ.csv: 9953.975999999999 胜率：59.62%\n",
|
||
"000089.SZ.csv: 10026.226 胜率：60.38%\n",
|
||
"000090.SZ.csv: 9917.309244 胜率：59.26%\n",
|
||
"000096.SZ.csv: 10045.015344 胜率：60.00%\n",
|
||
"000099.SZ.csv: 10584.068 胜率：60.71%\n",
|
||
"000100.SZ.csv: 10023.042 胜率：61.40%\n",
|
||
"000151.SZ.csv: 10330.771999999999 胜率：62.07%\n",
|
||
"000153.SZ.csv: 10004.454765999999 胜率：62.71%\n",
|
||
"000155.SZ.csv: 9694.358286 胜率：61.67%\n",
|
||
"000156.SZ.csv: 10079.825206000001 胜率：62.30%\n",
|
||
"000157.SZ.csv: 10008.574 胜率：62.90%\n",
|
||
"000158.SZ.csv: 11604.982 胜率：63.49%\n",
|
||
"000159.SZ.csv: 10019.555999999999 胜率：64.06%\n",
|
||
"000166.SZ.csv: 9985.224348 胜率：63.08%\n",
|
||
"000301.SZ.csv: 9962.286 胜率：62.12%\n",
|
||
"000333.SZ.csv: 10549.185999999998 胜率：62.69%\n",
|
||
"000338.SZ.csv: 9928.012026 胜率：61.76%\n",
|
||
"000400.SZ.csv: 9674.79219 胜率：60.87%\n",
|
||
"000401.SZ.csv: 10067.266 胜率：61.43%\n",
|
||
"000402.SZ.csv: 9995.242000000002 胜率：60.56%\n",
|
||
"000403.SZ.csv: 9811.777565999999 胜率：59.72%\n",
|
||
"000404.SZ.csv: 10133.79 胜率：60.27%\n",
|
||
"000407.SZ.csv: 10037.867925999999 胜率：60.81%\n",
|
||
"000408.SZ.csv: 10345.912 胜率：61.33%\n",
|
||
"000409.SZ.csv: 10005.232 胜率：61.84%\n",
|
||
"000410.SZ.csv: 9993.762 胜率：61.04%\n",
|
||
"000411.SZ.csv: 9904.991999999998 胜率：60.26%\n",
|
||
"000413.SZ.csv: 10000.0 胜率：59.49%\n",
|
||
"000415.SZ.csv: 10084.454 胜率：60.00%\n",
|
||
"000416.SZ.csv: 10000.0 胜率：59.26%\n",
|
||
"000417.SZ.csv: 10136.938234 胜率：59.76%\n",
|
||
"000419.SZ.csv: 10085.181413999999 胜率：60.24%\n",
|
||
"000420.SZ.csv: 10046.372 胜率：60.71%\n",
|
||
"000421.SZ.csv: 9690.21013 胜率：60.00%\n",
|
||
"000422.SZ.csv: 10234.994044000001 胜率：60.47%\n",
|
||
"000423.SZ.csv: 10300.08 胜率：60.92%\n",
|
||
"000425.SZ.csv: 9984.916 胜率：60.23%\n",
|
||
"000426.SZ.csv: 10032.916 胜率：60.67%\n",
|
||
"000428.SZ.csv: 9943.984 胜率：60.00%\n",
|
||
"000429.SZ.csv: 10290.646 胜率：60.44%\n",
|
||
"000430.SZ.csv: 9848.46 胜率：59.78%\n",
|
||
"000488.SZ.csv: 9837.72 胜率：59.14%\n",
|
||
"000498.SZ.csv: 10015.545607999999 胜率：59.57%\n",
|
||
"000501.SZ.csv: 10257.867360000002 胜率：60.00%\n",
|
||
"000503.SZ.csv: 10456.184 胜率：60.42%\n",
|
||
"000504.SZ.csv: 10000.064 胜率：60.82%\n",
|
||
"000505.SZ.csv: 10004.096119999998 胜率：61.22%\n",
|
||
"000506.SZ.csv: 10264.736 胜率：61.62%\n",
|
||
"000507.SZ.csv: 9953.265153999999 胜率：61.00%\n",
|
||
"000509.SZ.csv: 9990.326000000001 胜率：60.40%\n",
|
||
"000510.SZ.csv: 10076.68 胜率：60.78%\n",
|
||
"000513.SZ.csv: 9419.782 胜率：60.19%\n",
|
||
"000514.SZ.csv: 10097.117354 胜率：60.58%\n",
|
||
"000516.SZ.csv: 9925.798 胜率：60.00%\n",
|
||
"000517.SZ.csv: 9962.032136 胜率：59.43%\n",
|
||
"000518.SZ.csv: 10005.790000000003 胜率：59.81%\n",
|
||
"000519.SZ.csv: 9725.471074000001 胜率：59.26%\n",
|
||
"000520.SZ.csv: 10198.524 胜率：59.63%\n",
|
||
"000521.SZ.csv: 9983.712 胜率：59.09%\n",
|
||
"000523.SZ.csv: 9956.114000000001 胜率：58.56%\n",
|
||
"000524.SZ.csv: 9843.39 胜率：58.04%\n",
|
||
"000525.SZ.csv: 10025.091978 胜率：58.41%\n",
|
||
"000526.SZ.csv: 7486.533999999998 胜率：57.89%\n",
|
||
"000528.SZ.csv: 10035.483999999999 胜率：58.26%\n",
|
||
"000529.SZ.csv: 9973.151346 胜率：57.76%\n",
|
||
"000530.SZ.csv: 10112.763794000002 胜率：58.12%\n",
|
||
"000531.SZ.csv: 9922.603352 胜率：57.63%\n",
|
||
"000532.SZ.csv: 9350.934438000002 胜率：57.14%\n",
|
||
"000533.SZ.csv: 10218.862000000001 胜率：57.50%\n",
|
||
"000534.SZ.csv: 10023.382952 胜率：57.85%\n",
|
||
"000536.SZ.csv: 10217.554 胜率：58.20%\n",
|
||
"000537.SZ.csv: 9815.95912 胜率：57.72%\n",
|
||
"000538.SZ.csv: 9804.412686 胜率：57.26%\n",
|
||
"000539.SZ.csv: 9980.099999999999 胜率：56.80%\n",
|
||
"000541.SZ.csv: 10108.98 胜率：57.14%\n",
|
||
"000543.SZ.csv: 9978.000104 胜率：56.69%\n",
|
||
"000544.SZ.csv: 9999.462 胜率：56.25%\n",
|
||
"000545.SZ.csv: 9971.752 胜率：55.81%\n",
|
||
"000546.SZ.csv: 10045.054 胜率：56.15%\n",
|
||
"000547.SZ.csv: 9873.253999999999 胜率：55.73%\n",
|
||
"000548.SZ.csv: 9966.549856 胜率：55.30%\n",
|
||
"000550.SZ.csv: 9229.768 胜率：54.89%\n",
|
||
"000551.SZ.csv: 9921.066124 胜率：54.48%\n",
|
||
"000552.SZ.csv: 10027.166067999999 胜率：54.81%\n",
|
||
"000553.SZ.csv: 10062.572 胜率：55.15%\n",
|
||
"000554.SZ.csv: 9918.149696 胜率：54.74%\n",
|
||
"000555.SZ.csv: 10124.012 胜率：55.07%\n",
|
||
"000557.SZ.csv: 9969.593999999997 胜率：54.68%\n",
|
||
"000558.SZ.csv: 10112.544 胜率：55.00%\n",
|
||
"000559.SZ.csv: 10131.034 胜率：55.32%\n",
|
||
"000560.SZ.csv: 9959.742 胜率：54.93%\n",
|
||
"000561.SZ.csv: 10188.310688 胜率：55.24%\n",
|
||
"000563.SZ.csv: 10028.951442 胜率：55.56%\n",
|
||
"000564.SZ.csv: 10134.898000000001 胜率：55.86%\n",
|
||
"000565.SZ.csv: 10081.564304 胜率：56.16%\n",
|
||
"000566.SZ.csv: 10136.924 胜率：56.46%\n",
|
||
"000567.SZ.csv: 9863.413636 胜率：56.08%\n",
|
||
"000568.SZ.csv: 10000.0 胜率：55.70%\n",
|
||
"000570.SZ.csv: 10024.189465999998 胜率：56.00%\n",
|
||
"000571.SZ.csv: 10013.488 胜率：56.29%\n",
|
||
"000572.SZ.csv: 9999.936000000002 胜率：55.92%\n",
|
||
"000573.SZ.csv: 10018.062431999999 胜率：56.21%\n",
|
||
"000576.SZ.csv: 10025.696 胜率：56.49%\n",
|
||
"000581.SZ.csv: 10113.976034 胜率：56.77%\n",
|
||
"000582.SZ.csv: 9917.368174 胜率：56.41%\n",
|
||
"000584.SZ.csv: 10102.571999999998 胜率：56.69%\n",
|
||
"000586.SZ.csv: 10190.484 胜率：56.96%\n",
|
||
"000589.SZ.csv: 9942.371324000002 胜率：56.60%\n",
|
||
"000590.SZ.csv: 10022.07 胜率：56.88%\n",
|
||
"000591.SZ.csv: 9958.528344 胜率：56.52%\n",
|
||
"000592.SZ.csv: 10135.698 胜率：56.79%\n",
|
||
"000593.SZ.csv: 10002.89 胜率：57.06%\n",
|
||
"000595.SZ.csv: 10417.583999999999 胜率：57.32%\n",
|
||
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"300908.SZ.csv: 10283.745630000001 胜率：57.95%\n",
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"300909.SZ.csv: 9570.931478 胜率：57.92%\n",
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"300910.SZ.csv: 9792.885616 胜率：57.90%\n",
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"300911.SZ.csv: 10205.971368 胜率：57.92%\n",
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"300912.SZ.csv: 10144.921999999999 胜率：57.93%\n",
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"300913.SZ.csv: 11762.446 胜率：57.95%\n",
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"300915.SZ.csv: 9889.352 胜率：57.93%\n",
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"300916.SZ.csv: 10484.98 胜率：57.95%\n",
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"300917.SZ.csv: 12289.290448 胜率：57.96%\n",
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"300918.SZ.csv: 9899.552449999997 胜率：57.94%\n",
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"300919.SZ.csv: 10778.455488 胜率：57.96%\n",
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"300920.SZ.csv: 9696.087866 胜率：57.93%\n",
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"300921.SZ.csv: 10750.057999999999 胜率：57.95%\n",
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"300922.SZ.csv: 9727.937456000001 胜率：57.93%\n",
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"300923.SZ.csv: 9747.740462000002 胜率：57.90%\n",
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"300925.SZ.csv: 11256.816079999999 胜率：57.92%\n",
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"300926.SZ.csv: 9431.801999999998 胜率：57.89%\n",
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"300927.SZ.csv: 10041.703999999998 胜率：57.91%\n",
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"300928.SZ.csv: 10033.71644 胜率：57.93%\n",
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"300929.SZ.csv: 10055.683879999999 胜率：57.95%\n",
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"300930.SZ.csv: 9552.093631999998 胜率：57.92%\n",
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"300931.SZ.csv: 9755.74761 胜率：57.90%\n",
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"300932.SZ.csv: 10504.74514 胜率：57.92%\n",
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"300933.SZ.csv: 10219.452496000002 胜率：57.93%\n",
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"300935.SZ.csv: 10431.474 胜率：57.95%\n",
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"300936.SZ.csv: 8947.864996 胜率：57.93%\n",
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"300937.SZ.csv: 9960.078 胜率：57.90%\n",
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"300938.SZ.csv: 10539.952 胜率：57.92%\n",
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"300939.SZ.csv: 10218.536010000002 胜率：57.94%\n",
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"300940.SZ.csv: 10020.232 胜率：57.96%\n",
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"300941.SZ.csv: 11009.751132 胜率：57.97%\n",
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"300942.SZ.csv: 9886.053999999998 胜率：57.95%\n",
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"300943.SZ.csv: 9368.264812000001 胜率：57.93%\n",
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"300945.SZ.csv: 9969.664518 胜率：57.90%\n",
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"300946.SZ.csv: 9389.128598 胜率：57.88%\n",
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"300947.SZ.csv: 9492.488 胜率：57.85%\n",
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"300948.SZ.csv: 10054.768 胜率：57.87%\n",
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"300949.SZ.csv: 10739.632 胜率：57.89%\n",
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"300950.SZ.csv: 10015.347272 胜率：57.91%\n",
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"300951.SZ.csv: 9755.567735999999 胜率：57.88%\n",
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"300952.SZ.csv: 9850.958 胜率：57.86%\n",
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"300953.SZ.csv: 10200.5 胜率：57.88%\n",
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"300955.SZ.csv: 9989.827309999999 胜率：57.85%\n",
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"300956.SZ.csv: 11193.187358000001 胜率：57.87%\n",
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"300957.SZ.csv: 7889.054000000001 胜率：57.84%\n",
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"300958.SZ.csv: 9452.987003999999 胜率：57.82%\n",
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"300959.SZ.csv: 11423.886 胜率：57.84%\n",
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"300960.SZ.csv: 8398.407926 胜率：57.81%\n",
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"300961.SZ.csv: 9492.758 胜率：57.79%\n",
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"300962.SZ.csv: 9983.458 胜率：57.77%\n",
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"300963.SZ.csv: 9706.388892 胜率：57.74%\n",
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"300964.SZ.csv: 8175.37058 胜率：57.72%\n",
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"300965.SZ.csv: 10238.911196 胜率：57.74%\n",
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"300966.SZ.csv: 9282.709671999999 胜率：57.71%\n",
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"300967.SZ.csv: 9761.196 胜率：57.69%\n",
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"300968.SZ.csv: 10433.898408000001 胜率：57.71%\n",
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"300969.SZ.csv: 11022.74 胜率：57.72%\n",
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"300970.SZ.csv: 9482.030030000002 胜率：57.70%\n",
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"300971.SZ.csv: 9543.836188000001 胜率：57.68%\n",
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"300972.SZ.csv: 15205.34 胜率：57.69%\n",
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"300973.SZ.csv: 10480.960761999999 胜率：57.71%\n",
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"300975.SZ.csv: 9993.284 胜率：57.69%\n",
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"300976.SZ.csv: 10142.467034000001 胜率：57.70%\n",
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"300977.SZ.csv: 8630.082986000001 胜率：57.68%\n",
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"300978.SZ.csv: 9574.991648000003 胜率：57.66%\n",
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"300979.SZ.csv: 10608.948 胜率：57.67%\n",
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"300980.SZ.csv: 10113.620965999999 胜率：57.69%\n",
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"300981.SZ.csv: 10087.343090000002 胜率：57.71%\n",
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"300982.SZ.csv: 9297.972265999999 胜率：57.69%\n",
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"300983.SZ.csv: 10079.369782000002 胜率：57.70%\n",
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"300984.SZ.csv: 11373.220614000002 胜率：57.72%\n",
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"300985.SZ.csv: 9829.092 胜率：57.70%\n",
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"300986.SZ.csv: 10248.449018 胜率：57.71%\n",
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"300987.SZ.csv: 10268.62 胜率：57.73%\n",
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"300988.SZ.csv: 9679.614 胜率：57.71%\n",
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"300989.SZ.csv: 9849.922 胜率：57.68%\n",
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"300990.SZ.csv: 11026.45612 胜率：57.70%\n",
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"300991.SZ.csv: 10390.65 胜率：57.72%\n",
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"300992.SZ.csv: 10620.93 胜率：57.74%\n",
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"300993.SZ.csv: 10237.203968 胜率：57.75%\n",
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"300994.SZ.csv: 9748.180972 胜率：57.73%\n",
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"300995.SZ.csv: 10012.87 胜率：57.75%\n",
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"300996.SZ.csv: 10273.404949999998 胜率：57.76%\n",
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"300997.SZ.csv: 10320.554 胜率：57.78%\n",
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"300998.SZ.csv: 9897.82 胜率：57.76%\n",
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"300999.SZ.csv: 9586.130261999999 胜率：57.73%\n",
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"301000.SZ.csv: 10956.607686 胜率：57.75%\n",
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"301001.SZ.csv: 11009.508318 胜率：57.77%\n",
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"301002.SZ.csv: 9224.694155999998 胜率：57.75%\n",
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"301003.SZ.csv: 9681.466 胜率：57.72%\n",
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"301004.SZ.csv: 10000.0 胜率：57.70%\n",
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"301005.SZ.csv: 9738.596325999997 胜率：57.68%\n",
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"301006.SZ.csv: 10045.596669999999 胜率：57.69%\n",
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"301007.SZ.csv: 10186.429212 胜率：57.71%\n",
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"301008.SZ.csv: 9871.279649999999 胜率：57.69%\n",
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"301009.SZ.csv: 9958.515991999999 胜率：57.66%\n",
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"301010.SZ.csv: 10659.075410000001 胜率：57.68%\n",
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"301011.SZ.csv: 10524.036242 胜率：57.70%\n",
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"301012.SZ.csv: 10824.921801999999 胜率：57.71%\n",
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"301013.SZ.csv: 9506.873999999998 胜率：57.69%\n",
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"301015.SZ.csv: 9665.678 胜率：57.67%\n",
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"301016.SZ.csv: 9734.914 胜率：57.64%\n",
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"301017.SZ.csv: 9836.288 胜率：57.62%\n",
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"301018.SZ.csv: 11430.946 胜率：57.64%\n",
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"301019.SZ.csv: 10155.034292 胜率：57.66%\n",
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"301020.SZ.csv: 9108.142434000001 胜率：57.63%\n",
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"301021.SZ.csv: 10286.072 胜率：57.65%\n",
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"301022.SZ.csv: 9896.398 胜率：57.63%\n",
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"301023.SZ.csv: 10838.544574000001 胜率：57.64%\n",
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"301024.SZ.csv: 9203.111999999997 胜率：57.62%\n",
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"301025.SZ.csv: 9774.648 胜率：57.60%\n",
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"301026.SZ.csv: 9954.608617999998 胜率：57.57%\n",
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"301027.SZ.csv: 10566.886 胜率：57.59%\n",
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"301028.SZ.csv: 10164.643628 胜率：57.61%\n",
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"301029.SZ.csv: 9937.942 胜率：57.58%\n",
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"301030.SZ.csv: 10598.007999999998 胜率：57.60%\n",
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"301031.SZ.csv: 12438.252295999999 胜率：57.62%\n",
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"301032.SZ.csv: 10097.987653999999 胜率：57.64%\n",
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"301033.SZ.csv: 11029.373558000001 胜率：57.65%\n",
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"301035.SZ.csv: 10703.806 胜率：57.67%\n",
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"301036.SZ.csv: 11943.46142 胜率：57.69%\n",
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"301037.SZ.csv: 9631.919772000003 胜率：57.66%\n",
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"301038.SZ.csv: 10357.672 胜率：57.68%\n",
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"301039.SZ.csv: 10133.344902 胜率：57.70%\n",
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"301040.SZ.csv: 10245.284 胜率：57.71%\n",
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"301041.SZ.csv: 9732.363115999999 胜率：57.69%\n",
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"301042.SZ.csv: 10217.11473 胜率：57.71%\n",
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"301043.SZ.csv: 9711.625142 胜率：57.68%\n",
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"301045.SZ.csv: 9280.597978000003 胜率：57.66%\n",
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"301046.SZ.csv: 9813.080372 胜率：57.64%\n",
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"301047.SZ.csv: 9355.046 胜率：57.62%\n",
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"301048.SZ.csv: 9901.832218 胜率：57.59%\n",
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"301049.SZ.csv: 10235.224000000002 胜率：57.61%\n",
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"301050.SZ.csv: 9526.847695999997 胜率：57.59%\n",
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"301051.SZ.csv: 10310.358 胜率：57.60%\n",
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"301052.SZ.csv: 10569.478 胜率：57.62%\n",
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"301053.SZ.csv: 9413.291109999998 胜率：57.60%\n",
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"301055.SZ.csv: 10269.858000000002 胜率：57.61%\n",
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"301056.SZ.csv: 9934.964404 胜率：57.59%\n",
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"301057.SZ.csv: 9990.847854 胜率：57.57%\n",
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"301058.SZ.csv: 9901.236169999998 胜率：57.55%\n",
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"301059.SZ.csv: 10140.674716 胜率：57.56%\n",
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"301060.SZ.csv: 9716.216 胜率：57.54%\n",
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"301061.SZ.csv: 10527.628558 胜率：57.56%\n",
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"301062.SZ.csv: 10086.518000000002 胜率：57.57%\n",
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"301063.SZ.csv: 9662.398761999999 胜率：57.55%\n",
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"301065.SZ.csv: 9313.171562 胜率：57.53%\n",
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"301066.SZ.csv: 10330.909368 胜率：57.54%\n",
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"301067.SZ.csv: 10233.282000000001 胜率：57.56%\n",
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"301068.SZ.csv: 10707.326 胜率：57.58%\n",
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"301069.SZ.csv: 9549.079015999998 胜率：57.56%\n",
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"301070.SZ.csv: 10733.826000000001 胜率：57.57%\n",
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"301071.SZ.csv: 10808.841926 胜率：57.59%\n",
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"301072.SZ.csv: 9198.447221999999 胜率：57.57%\n",
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"301073.SZ.csv: 9579.996 胜率：57.54%\n",
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"301075.SZ.csv: 9133.241493999998 胜率：57.52%\n",
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"301076.SZ.csv: 11175.174 胜率：57.54%\n",
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"301077.SZ.csv: 10305.314658000001 胜率：57.55%\n",
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"301078.SZ.csv: 10576.487216 胜率：57.57%\n",
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"301079.SZ.csv: 9545.989774000001 胜率：57.55%\n",
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"301080.SZ.csv: 9265.927166 胜率：57.53%\n",
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"301081.SZ.csv: 9961.011117999999 胜率：57.50%\n",
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"301082.SZ.csv: 10327.221412 胜率：57.52%\n",
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"301083.SZ.csv: 9918.366858 胜率：57.50%\n",
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"301085.SZ.csv: 12632.568 胜率：57.51%\n",
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"301086.SZ.csv: 9801.93829 胜率：57.49%\n",
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"301087.SZ.csv: 9706.654694 胜率：57.47%\n",
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"301088.SZ.csv: 10148.790262 胜率：57.49%\n",
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"301089.SZ.csv: 9363.965999999999 胜率：57.46%\n",
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"301090.SZ.csv: 10063.212000000001 胜率：57.48%\n",
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"301091.SZ.csv: 11457.856 胜率：57.50%\n",
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"301092.SZ.csv: 9890.124 胜率：57.47%\n",
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"301093.SZ.csv: 10287.392 胜率：57.49%\n",
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"301095.SZ.csv: 10480.842 胜率：57.51%\n",
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"301096.SZ.csv: 9795.74 胜率：57.48%\n",
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"301097.SZ.csv: 9481.923999999999 胜率：57.46%\n",
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"301098.SZ.csv: 9918.828322 胜率：57.44%\n",
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"301099.SZ.csv: 9901.563872 胜率：57.42%\n",
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"301100.SZ.csv: 9373.0514 胜率：57.39%\n",
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"301101.SZ.csv: 10950.948 胜率：57.41%\n",
|
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"301102.SZ.csv: 10134.086 胜率：57.43%\n",
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"301103.SZ.csv: 9728.20844 胜率：57.41%\n",
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"301105.SZ.csv: 9261.652 胜率：57.38%\n",
|
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"301106.SZ.csv: 9459.516784000003 胜率：57.36%\n",
|
||
"301107.SZ.csv: 9495.6595 胜率：57.34%\n",
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"301108.SZ.csv: 9962.993462 胜率：57.32%\n",
|
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"301109.SZ.csv: 9771.214 胜率：57.29%\n",
|
||
"301110.SZ.csv: 12539.841011999999 胜率：57.31%\n"
|
||
]
|
||
},
|
||
{
|
||
"ename": "KeyboardInterrupt",
|
||
"evalue": "",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
|
||
"\u001B[1;31mKeyboardInterrupt\u001B[0m Traceback (most recent call last)",
|
||
"Cell \u001B[1;32mIn[63], line 6\u001B[0m\n\u001B[0;32m 4\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m name \u001B[38;5;129;01min\u001B[39;00m os\u001B[38;5;241m.\u001B[39mlistdir(os\u001B[38;5;241m.\u001B[39mpath\u001B[38;5;241m.\u001B[39mjoin(root_path, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124m日线行情 1990-2024\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124m分组行情\u001B[39m\u001B[38;5;124m\"\u001B[39m)):\n\u001B[0;32m 5\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m name\u001B[38;5;241m.\u001B[39mendswith(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mSZ.csv\u001B[39m\u001B[38;5;124m\"\u001B[39m):\n\u001B[1;32m----> 6\u001B[0m stock_df \u001B[38;5;241m=\u001B[39m \u001B[43mload_stock\u001B[49m\u001B[43m(\u001B[49m\u001B[43mname\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mreplace\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43m.csv\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m)\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 7\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m stock_df\u001B[38;5;241m.\u001B[39mempty:\n\u001B[0;32m 8\u001B[0m \u001B[38;5;28;01mcontinue\u001B[39;00m\n",
|
||
"Cell \u001B[1;32mIn[48], line 2\u001B[0m, in \u001B[0;36mload_stock\u001B[1;34m(code)\u001B[0m\n\u001B[0;32m 1\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;21mload_stock\u001B[39m(code):\n\u001B[1;32m----> 2\u001B[0m source_df \u001B[38;5;241m=\u001B[39m \u001B[43mpd\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mread_csv\u001B[49m\u001B[43m(\u001B[49m\u001B[43mos\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mpath\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mjoin\u001B[49m\u001B[43m(\u001B[49m\u001B[43mroot_path\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43m日线行情 1990-2024\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43m分组行情\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;124;43mf\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;132;43;01m{\u001B[39;49;00m\u001B[43mcode\u001B[49m\u001B[38;5;132;43;01m}\u001B[39;49;00m\u001B[38;5;124;43m.csv\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m)\u001B[49m\u001B[43m)\u001B[49m \\\n\u001B[0;32m 3\u001B[0m [[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtrade_date\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mvol\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mopen_qfq\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mclose_qfq\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mhigh_qfq\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mlow_qfq\u001B[39m\u001B[38;5;124m\"\u001B[39m]]\n\u001B[0;32m 4\u001B[0m temp_df \u001B[38;5;241m=\u001B[39m pd\u001B[38;5;241m.\u001B[39mDataFrame()\n\u001B[0;32m 5\u001B[0m temp_df[[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mdate\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mVolume\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mOpen\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mClose\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mHigh\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mLow\u001B[39m\u001B[38;5;124m\"\u001B[39m]] \u001B[38;5;241m=\u001B[39m \\\n\u001B[0;32m 6\u001B[0m source_df[[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtrade_date\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mvol\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mopen_qfq\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mclose_qfq\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mhigh_qfq\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mlow_qfq\u001B[39m\u001B[38;5;124m\"\u001B[39m]]\n",
|
||
"File \u001B[1;32m~\\AppData\\Local\\pypoetry\\Cache\\virtualenvs\\finance-xaAHQYW0-py3.12\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:1026\u001B[0m, in \u001B[0;36mread_csv\u001B[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001B[0m\n\u001B[0;32m 1013\u001B[0m kwds_defaults \u001B[38;5;241m=\u001B[39m _refine_defaults_read(\n\u001B[0;32m 1014\u001B[0m dialect,\n\u001B[0;32m 1015\u001B[0m delimiter,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 1022\u001B[0m dtype_backend\u001B[38;5;241m=\u001B[39mdtype_backend,\n\u001B[0;32m 1023\u001B[0m )\n\u001B[0;32m 1024\u001B[0m kwds\u001B[38;5;241m.\u001B[39mupdate(kwds_defaults)\n\u001B[1;32m-> 1026\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43m_read\u001B[49m\u001B[43m(\u001B[49m\u001B[43mfilepath_or_buffer\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mkwds\u001B[49m\u001B[43m)\u001B[49m\n",
|
||
"File \u001B[1;32m~\\AppData\\Local\\pypoetry\\Cache\\virtualenvs\\finance-xaAHQYW0-py3.12\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:620\u001B[0m, in \u001B[0;36m_read\u001B[1;34m(filepath_or_buffer, kwds)\u001B[0m\n\u001B[0;32m 617\u001B[0m _validate_names(kwds\u001B[38;5;241m.\u001B[39mget(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mnames\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;28;01mNone\u001B[39;00m))\n\u001B[0;32m 619\u001B[0m \u001B[38;5;66;03m# Create the parser.\u001B[39;00m\n\u001B[1;32m--> 620\u001B[0m parser \u001B[38;5;241m=\u001B[39m \u001B[43mTextFileReader\u001B[49m\u001B[43m(\u001B[49m\u001B[43mfilepath_or_buffer\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwds\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 622\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m chunksize \u001B[38;5;129;01mor\u001B[39;00m iterator:\n\u001B[0;32m 623\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m parser\n",
|
||
"File \u001B[1;32m~\\AppData\\Local\\pypoetry\\Cache\\virtualenvs\\finance-xaAHQYW0-py3.12\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:1620\u001B[0m, in \u001B[0;36mTextFileReader.__init__\u001B[1;34m(self, f, engine, **kwds)\u001B[0m\n\u001B[0;32m 1617\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39moptions[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mhas_index_names\u001B[39m\u001B[38;5;124m\"\u001B[39m] \u001B[38;5;241m=\u001B[39m kwds[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mhas_index_names\u001B[39m\u001B[38;5;124m\"\u001B[39m]\n\u001B[0;32m 1619\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mhandles: IOHandles \u001B[38;5;241m|\u001B[39m \u001B[38;5;28;01mNone\u001B[39;00m \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[1;32m-> 1620\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_engine \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_make_engine\u001B[49m\u001B[43m(\u001B[49m\u001B[43mf\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mengine\u001B[49m\u001B[43m)\u001B[49m\n",
|
||
"File \u001B[1;32m~\\AppData\\Local\\pypoetry\\Cache\\virtualenvs\\finance-xaAHQYW0-py3.12\\Lib\\site-packages\\pandas\\io\\parsers\\readers.py:1898\u001B[0m, in \u001B[0;36mTextFileReader._make_engine\u001B[1;34m(self, f, engine)\u001B[0m\n\u001B[0;32m 1895\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(msg)\n\u001B[0;32m 1897\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m-> 1898\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mmapping\u001B[49m\u001B[43m[\u001B[49m\u001B[43mengine\u001B[49m\u001B[43m]\u001B[49m\u001B[43m(\u001B[49m\u001B[43mf\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43moptions\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1899\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m:\n\u001B[0;32m 1900\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mhandles \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n",
|
||
"File \u001B[1;32m~\\AppData\\Local\\pypoetry\\Cache\\virtualenvs\\finance-xaAHQYW0-py3.12\\Lib\\site-packages\\pandas\\io\\parsers\\c_parser_wrapper.py:93\u001B[0m, in \u001B[0;36mCParserWrapper.__init__\u001B[1;34m(self, src, **kwds)\u001B[0m\n\u001B[0;32m 90\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m kwds[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mdtype_backend\u001B[39m\u001B[38;5;124m\"\u001B[39m] \u001B[38;5;241m==\u001B[39m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mpyarrow\u001B[39m\u001B[38;5;124m\"\u001B[39m:\n\u001B[0;32m 91\u001B[0m \u001B[38;5;66;03m# Fail here loudly instead of in cython after reading\u001B[39;00m\n\u001B[0;32m 92\u001B[0m import_optional_dependency(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mpyarrow\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n\u001B[1;32m---> 93\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_reader \u001B[38;5;241m=\u001B[39m \u001B[43mparsers\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mTextReader\u001B[49m\u001B[43m(\u001B[49m\u001B[43msrc\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwds\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 95\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39munnamed_cols \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_reader\u001B[38;5;241m.\u001B[39munnamed_cols\n\u001B[0;32m 97\u001B[0m \u001B[38;5;66;03m# error: Cannot determine type of 'names'\u001B[39;00m\n",
|
||
"File \u001B[1;32mparsers.pyx:574\u001B[0m, in \u001B[0;36mpandas._libs.parsers.TextReader.__cinit__\u001B[1;34m()\u001B[0m\n",
|
||
"File \u001B[1;32mparsers.pyx:663\u001B[0m, in \u001B[0;36mpandas._libs.parsers.TextReader._get_header\u001B[1;34m()\u001B[0m\n",
|
||
"File \u001B[1;32mparsers.pyx:874\u001B[0m, in \u001B[0;36mpandas._libs.parsers.TextReader._tokenize_rows\u001B[1;34m()\u001B[0m\n",
|
||
"File \u001B[1;32mparsers.pyx:891\u001B[0m, in \u001B[0;36mpandas._libs.parsers.TextReader._check_tokenize_status\u001B[1;34m()\u001B[0m\n",
|
||
"File \u001B[1;32mparsers.pyx:2053\u001B[0m, in \u001B[0;36mpandas._libs.parsers.raise_parser_error\u001B[1;34m()\u001B[0m\n",
|
||
"File \u001B[1;32m<frozen codecs>:319\u001B[0m, in \u001B[0;36mdecode\u001B[1;34m(self, input, final)\u001B[0m\n",
|
||
"\u001B[1;31mKeyboardInterrupt\u001B[0m: "
|
||
]
|
||
}
|
||
],
|
||
"execution_count": 63
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 2
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython2",
|
||
"version": "2.7.6"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|