{ "cells": [ { "cell_type": "code", "execution_count": 6, "id": "1c4126c0", "metadata": {}, "outputs": [], "source": [ "from operator import index\n", "\n", "import tushare as ts\n", "import pandas as pd\n", "import time\n", "import akshare as ak\n", "\n", "ts.set_token('3a0741c702ee7e5e5f2bf1f0846bafaafe4e320833240b2a7e4a685f')\n", "pro = ts.pro_api()\n", "\n", "from datetime import datetime\n", "import pandas as pd\n", "import warnings\n", "import warnings\n", "\n", "warnings.filterwarnings(\"ignore\")" ] }, { "cell_type": "code", "execution_count": 42, "id": "dc90836a", "metadata": {}, "outputs": [], "source": [ "def filter_rows(df):\n", " # 按照 name 和 start_date 分组\n", " def select_row(group):\n", " # 如果有 end_date 不为 NaT 的行，优先保留这些行\n", " valid_rows = group[group['end_date'].notna()]\n", " if not valid_rows.empty:\n", " return valid_rows.iloc[0] # 返回第一个有效行\n", " else:\n", " return group.iloc[0] # 如果没有有效行，返回第一行\n", "\n", " filtered_df = df.groupby(['name', 'start_date'], group_keys=False).apply(select_row)\n", " filtered_df = filtered_df.reset_index(drop=True)\n", " return filtered_df\n", "\n", "name_change_df = pd.read_hdf('E:/PyProject/NewStock/data/name_change.h5', key='name_change')\n", "name_change_df = name_change_df.drop_duplicates(keep='first')\n", "\n", "# 确保 name_change_df 的日期格式正确\n", "name_change_df['start_date'] = pd.to_datetime(name_change_df['start_date'], format='%Y%m%d')\n", "name_change_df['end_date'] = pd.to_datetime(name_change_df['end_date'], format='%Y%m%d', errors='coerce')\n", "name_change_df = name_change_df[name_change_df.name.str.contains('ST')]\n", "name_change_dict = {}\n", "for ts_code, group in name_change_df.groupby('ts_code'):\n", " # 只保留 'ST' 和 '*ST' 的记录\n", " st_data = group[group['name'].str.contains('ST')]\n", " if not st_data.empty and ts_code == '002569.SZ':\n", " name_change_dict[ts_code] = filter_rows(st_data)\n", " # name_change_dict[ts_code] = st_data" ] }, { "cell_type": "code", "execution_count": 43, "id": "f0ed36d1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " ts_code name start_date end_date change_reason\n", "7990 002569.SZ ST步森 2020-06-09 NaT 摘星\n", "7992 002569.SZ *ST步森 2019-04-30 NaT *ST\n", "7993 002569.SZ *ST步森 2019-04-30 2020-06-08 *ST\n", " ts_code name start_date end_date change_reason\n", "0 002569.SZ *ST步森 2019-04-30 2020-06-08 *ST\n", "1 002569.SZ ST步森 2020-06-09 NaT 摘星\n" ] } ], "source": [ "print(name_change_df[name_change_df['ts_code'] == '002569.SZ'])\n", "print(filter_rows(name_change_df[name_change_df['ts_code'] == '002569.SZ']))\n" ] }, { "cell_type": "code", "execution_count": 44, "id": "3c526622", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " ts_code name start_date end_date change_reason\n", "0 002569.SZ *ST步森 2019-04-30 2020-06-08 *ST\n", "1 002569.SZ ST步森 2020-06-09 NaT 摘星\n", " ts_code trade_date is_st\n", "3753 002569.SZ 20230120 True\n" ] } ], "source": [ "\n", "warnings.filterwarnings(\"ignore\")\n", "\n", "\n", "def is_st(name_change_dict, stock_code, target_date):\n", " target_date = datetime.strptime(target_date, '%Y%m%d')\n", " if stock_code not in name_change_dict.keys():\n", " return False\n", " df = name_change_dict[stock_code]\n", " print(df)\n", " for i in range(len(df)):\n", " sds = df.iloc[i, 2]\n", " eds = df.iloc[i, 3]\n", " if eds is None or eds is pd.NaT:\n", " eds = datetime.now()\n", " if (target_date - sds).days >= 0 and (target_date - eds).days <= 0:\n", " return True\n", " return False\n", "\n", " \n", "trade_date = '20230120'\n", "daily_basic_data = pro.daily_basic(ts_code='', trade_date=trade_date)\n", "daily_basic_data = daily_basic_data[daily_basic_data['ts_code'] == '002569.SZ']\n", "if daily_basic_data is not None and not daily_basic_data.empty:\n", " # 添加交易日期列标识\n", " daily_basic_data['trade_date'] = trade_date\n", " daily_basic_data['is_st'] = daily_basic_data.apply(\n", " lambda row: is_st(name_change_dict, row['ts_code'], row['trade_date']), axis=1\n", " )\n", " \n", "print(daily_basic_data[daily_basic_data['ts_code'] == '002569.SZ'][['ts_code', 'trade_date', 'is_st']])" ] }, { "cell_type": "code", "execution_count": null, "id": "cf4c9fd5", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 45, "id": "4a3638e6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " ts_code name start_date end_date change_reason\n", "0 002569.SZ *ST步森 20250428 None *ST\n", "1 002569.SZ ST步森 20200609 None 摘星\n", "2 002569.SZ ST步森 20200609 None 摘星\n", "3 002569.SZ ST步森 20200609 20250427 摘星\n", "4 002569.SZ *ST步森 20190430 None *ST\n", "5 002569.SZ *ST步森 20190430 20200608 *ST\n", "6 002569.SZ *ST步森 20190430 20200608 *ST\n", "7 002569.SZ 步森股份 20110412 20190429 其他\n", "8 002569.SZ 步森股份 20110412 20190429 其他\n" ] } ], "source": [ "df = pro.namechange(ts_code='002569.SZ', fields='ts_code,name,start_date,end_date,change_reason')\n", "print(df)" ] } ], "metadata": { "kernelspec": { "display_name": "new_trader", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.11" } }, "nbformat": 4, "nbformat_minor": 5 }