#!/usr/bin/env python # -*- coding:utf-8 -*- """ Date: 2024/4/4 18:20 Desc: 东方财富网-数据中心-特色数据-千股千评 https://data.eastmoney.com/stockcomment/ """ import json import re import time import pandas as pd import requests from akshare.utils.tqdm import get_tqdm def stock_comment_em() -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-千股千评 https://data.eastmoney.com/stockcomment/ :return: 千股千评数据 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "SECURITY_CODE", "sortTypes": "1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_DMSK_TS_STOCKNEW", "quoteColumns": "f2~01~SECURITY_CODE~CLOSE_PRICE,f8~01~SECURITY_CODE~TURNOVERRATE," "f3~01~SECURITY_CODE~CHANGE_RATE,f9~01~SECURITY_CODE~PE_DYNAMIC", "columns": "ALL", "filter": "", "token": "894050c76af8597a853f5b408b759f5d", } r = requests.get(url, params=params) data_json = r.json() total_page = data_json["result"]["pages"] big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, total_page + 1), leave=False): params.update({"pageNumber": page}) r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["result"]["data"]) big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True) big_df.reset_index(inplace=True) big_df["index"] = big_df.index + 1 big_df.columns = [ "序号", "-", "代码", "-", "交易日", "名称", "-", "-", "-", "最新价", "涨跌幅", "-", "换手率", "主力成本", "市盈率", "-", "-", "机构参与度", "-", "-", "-", "-", "-", "-", "-", "-", "综合得分", "上升", "目前排名", "关注指数", "-", "-", ] big_df = big_df[ [ "序号", "代码", "名称", "最新价", "涨跌幅", "换手率", "市盈率", "主力成本", "机构参与度", "综合得分", "上升", "目前排名", "关注指数", "交易日", ] ] big_df["最新价"] = pd.to_numeric(big_df["最新价"], errors="coerce") big_df["涨跌幅"] = pd.to_numeric(big_df["涨跌幅"], errors="coerce") big_df["换手率"] = pd.to_numeric(big_df["换手率"], errors="coerce") big_df["市盈率"] = pd.to_numeric(big_df["市盈率"], errors="coerce") big_df["主力成本"] = pd.to_numeric(big_df["主力成本"], errors="coerce") big_df["机构参与度"] = pd.to_numeric(big_df["机构参与度"], errors="coerce") big_df["综合得分"] = pd.to_numeric(big_df["综合得分"], errors="coerce") big_df["上升"] = pd.to_numeric(big_df["上升"], errors="coerce") big_df["目前排名"] = pd.to_numeric(big_df["目前排名"], errors="coerce") big_df["关注指数"] = pd.to_numeric(big_df["关注指数"], errors="coerce") big_df["交易日"] = pd.to_datetime(big_df["交易日"], errors="coerce").dt.date return big_df def stock_comment_detail_zlkp_jgcyd_em(symbol: str = "600000") -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-千股千评-主力控盘-机构参与度 https://data.eastmoney.com/stockcomment/stock/600000.html :param symbol: 股票代码 :type symbol: str :return: 主力控盘-机构参与度 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "reportName": "RPT_DMSK_TS_STOCKEVALUATE", "filter": f'(SECURITY_CODE="{symbol}")', "columns": "ALL", "source": "WEB", "client": "WEB", "sortColumns": "TRADE_DATE", "sortTypes": "-1", } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["result"]["data"]) temp_df = temp_df[["TRADE_DATE", "ORG_PARTICIPATE"]] temp_df.columns = ["交易日", "机构参与度"] temp_df["交易日"] = pd.to_datetime(temp_df["交易日"], errors="coerce").dt.date temp_df.sort_values(["交易日"], inplace=True) temp_df.reset_index(inplace=True, drop=True) temp_df["机构参与度"] = pd.to_numeric(temp_df["机构参与度"], errors="coerce") * 100 return temp_df def stock_comment_detail_zhpj_lspf_em(symbol: str = "600000") -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-千股千评-综合评价-历史评分 https://data.eastmoney.com/stockcomment/stock/600000.html :param symbol: 股票代码 :type symbol: str :return: 综合评价-历史评分 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "filter": f'(SECURITY_CODE="{symbol}")', "columns": "ALL", "source": "WEB", "client": "WEB", "reportName": "RPT_STOCK_HISTORYMARK", "sortColumns": "DIAGNOSE_DATE", "sortTypes": "1", } r = requests.get(url=url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["result"]["data"]) temp_df.rename( columns={ "TOTAL_SCORE": "评分", "DIAGNOSE_DATE": "交易日", }, inplace=True, ) temp_df = temp_df[["交易日", "评分"]] temp_df["交易日"] = pd.to_datetime(temp_df["交易日"], errors="coerce").dt.date temp_df.sort_values(by=["交易日"], inplace=True) temp_df.reset_index(inplace=True, drop=True) temp_df["评分"] = pd.to_numeric(temp_df["评分"], errors="coerce") return temp_df def stock_comment_detail_scrd_focus_em(symbol: str = "600000") -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-千股千评-市场热度-用户关注指数 https://data.eastmoney.com/stockcomment/stock/600000.html :param symbol: 股票代码 :type symbol: str :return: 市场热度-用户关注指数 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "filter": f'(SECURITY_CODE="{symbol}")', "columns": "ALL", "source": "WEB", "client": "WEB", "reportName": "RPT_STOCK_MARKETFOCUS", "sortColumns": "TRADE_DATE", "sortTypes": "-1", "pageSize": "30", } r = requests.get(url=url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["result"]["data"]) temp_df.rename( columns={ "MARKET_FOCUS": "用户关注指数", "TRADE_DATE": "交易日", }, inplace=True, ) temp_df = temp_df[["交易日", "用户关注指数"]] temp_df["交易日"] = pd.to_datetime(temp_df["交易日"], errors="coerce").dt.date temp_df.sort_values(by=["交易日"], inplace=True) temp_df.reset_index(inplace=True, drop=True) temp_df["用户关注指数"] = pd.to_numeric(temp_df["用户关注指数"], errors="coerce") return temp_df def stock_comment_detail_scrd_desire_em( symbol: str = "600000", ) -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-千股千评-市场热度-市场参与意愿 https://data.eastmoney.com/stockcomment/stock/600000.html :param symbol: 股票代码 :type symbol: str :return: 市场热度-市场参与意愿 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "callback": f"jQuery11230899775623921407_{int(time.time() * 1000)}", "filter": f'(SECURITY_CODE="{symbol}")', "columns": "ALL", "source": "WEB", "client": "WEB", "reportName": "RPT_STOCK_PARTICIPATION", "sortColumns": "TRADE_DATE", "sortTypes": "-1", "pageSize": "30", "_": int(time.time() * 1000), } headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/91.0.4472.124 Safari/537.36", "Referer": "https://data.eastmoney.com/", "Accept": "*/*", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", } r = requests.get(url, params=params, headers=headers) jsonp_data = r.text json_str = re.search(r"\((.*)\)", jsonp_data).group(1) data_json = json.loads(json_str) data_list = data_json["result"]["data"] temp_df = pd.DataFrame(data_list) temp_df["TRADE_DATE"] = pd.to_datetime( temp_df["TRADE_DATE"], errors="coerce" ).dt.date column_mapping = { "SECURITY_INNER_CODE": "内部代码", "SECURITY_CODE": "股票代码", "TRADE_DATE": "交易日期", "PARTICIPATION_WISH": "参与意愿", "PARTICIPATION_WISH_5DAYS": "5日平均参与意愿", "PARTICIPATION_WISH_CHANGE": "参与意愿变化", "PARTICIPATION_WISH_5DAYSCHANGE": "5日平均变化", } temp_df = temp_df.rename(columns=column_mapping) column_order = [ "交易日期", "股票代码", "内部代码", "参与意愿", "5日平均参与意愿", "参与意愿变化", "5日平均变化", ] temp_df = temp_df[column_order] del temp_df["内部代码"] temp_df.sort_values(by=["交易日期"], ignore_index=True, inplace=True) return temp_df if __name__ == "__main__": stock_comment_em_df = stock_comment_em() print(stock_comment_em_df) stock_comment_detail_zlkp_jgcyd_em_df = stock_comment_detail_zlkp_jgcyd_em( symbol="600000" ) print(stock_comment_detail_zlkp_jgcyd_em_df) stock_comment_detail_zhpj_lspf_em_df = stock_comment_detail_zhpj_lspf_em( symbol="600000" ) print(stock_comment_detail_zhpj_lspf_em_df) stock_comment_detail_scrd_focus_em_df = stock_comment_detail_scrd_focus_em( symbol="600000" ) print(stock_comment_detail_scrd_focus_em_df) stock_comment_detail_scrd_desire_em_df = stock_comment_detail_scrd_desire_em( symbol="600000" ) print(stock_comment_detail_scrd_desire_em_df)