#!/usr/bin/env python # -*- coding:utf-8 -*- """ Date: 2024/12/18 17:30 Desc: 东方财富网-数据中心-特色数据-股权质押 东方财富网-数据中心-特色数据-股权质押-股权质押市场概况: https://data.eastmoney.com/gpzy/marketProfile.aspx 东方财富网-数据中心-特色数据-股权质押-上市公司质押比例: https://data.eastmoney.com/gpzy/pledgeRatio.aspx 东方财富网-数据中心-特色数据-股权质押-重要股东股权质押明细: https://data.eastmoney.com/gpzy/pledgeDetail.aspx 东方财富网-数据中心-特色数据-股权质押-质押机构分布统计-证券公司: https://data.eastmoney.com/gpzy/distributeStatistics.aspx 东方财富网-数据中心-特色数据-股权质押-质押机构分布统计-银行: https://data.eastmoney.com/gpzy/distributeStatistics.aspx 东方财富网-数据中心-特色数据-股权质押-行业数据: https://data.eastmoney.com/gpzy/industryData.aspx """ import math import pandas as pd import requests from akshare.utils.tqdm import get_tqdm def stock_gpzy_profile_em() -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-股权质押-股权质押市场概况 https://data.eastmoney.com/gpzy/marketProfile.aspx :return: 股权质押市场概况 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "TRADE_DATE", "sortTypes": "-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_CSDC_STATISTICS", "columns": "ALL", "quoteColumns": "", "source": "WEB", "client": "WEB", } r = requests.get(url, params=params) data_json = r.json() total_page = data_json["result"]["pages"] big_df = pd.DataFrame() for page in range(1, total_page + 1): 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.columns = [ "交易日期", "质押总股数", "质押总市值", "沪深300指数", "涨跌幅", "A股质押总比例", "质押公司数量", "质押笔数", ] big_df = big_df[ [ "交易日期", "A股质押总比例", "质押公司数量", "质押笔数", "质押总股数", "质押总市值", "沪深300指数", "涨跌幅", ] ] big_df["交易日期"] = pd.to_datetime(big_df["交易日期"], errors="coerce").dt.date big_df["A股质押总比例"] = pd.to_numeric(big_df["A股质押总比例"], errors="coerce") big_df["质押公司数量"] = pd.to_numeric(big_df["质押公司数量"], errors="coerce") big_df["质押笔数"] = pd.to_numeric(big_df["质押笔数"], errors="coerce") big_df["质押总股数"] = pd.to_numeric(big_df["质押总股数"], errors="coerce") big_df["质押总市值"] = pd.to_numeric(big_df["质押总市值"], errors="coerce") big_df["沪深300指数"] = pd.to_numeric(big_df["沪深300指数"], errors="coerce") big_df["涨跌幅"] = pd.to_numeric(big_df["涨跌幅"], errors="coerce") big_df["A股质押总比例"] = big_df["A股质押总比例"] / 100 big_df["A股质押总比例"] = pd.to_numeric(big_df["A股质押总比例"], errors="coerce") big_df.sort_values(["交易日期"], inplace=True) big_df.reset_index(inplace=True, drop=True) return big_df def stock_gpzy_pledge_ratio_em(date: str = "20240906") -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-股权质押-上市公司质押比例 https://data.eastmoney.com/gpzy/pledgeRatio.aspx :param date: 指定交易日, 访问 https://data.eastmoney.com/gpzy/pledgeRatio.aspx 查询 :type date: str :return: 上市公司质押比例 :rtype: pandas.DataFrame """ trade_date = "-".join([date[:4], date[4:6], date[6:]]) url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "PLEDGE_RATIO", "sortTypes": "-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_CSDC_LIST", "columns": "ALL", "quoteColumns": "", "source": "WEB", "client": "WEB", "filter": f"(TRADE_DATE='{trade_date}')", } 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", "-", "股票代码", "股票简称", "交易日期", "质押比例", "质押股数", "质押笔数", "无限售股质押数", "限售股质押数", "质押市值", "所属行业", "近一年涨跌幅", "所属行业代码", "-", ] big_df = big_df[ [ "序号", "股票代码", "股票简称", "交易日期", "所属行业", "质押比例", "质押股数", "质押市值", "质押笔数", "无限售股质押数", "限售股质押数", "近一年涨跌幅", "所属行业代码", ] ] big_df["质押比例"] = pd.to_numeric(big_df["质押比例"], errors="coerce") big_df["质押股数"] = pd.to_numeric(big_df["质押股数"], errors="coerce") big_df["质押市值"] = pd.to_numeric(big_df["质押市值"], errors="coerce") big_df["质押笔数"] = pd.to_numeric(big_df["质押笔数"], errors="coerce") big_df["无限售股质押数"] = pd.to_numeric(big_df["无限售股质押数"], errors="coerce") big_df["限售股质押数"] = pd.to_numeric(big_df["限售股质押数"], errors="coerce") big_df["近一年涨跌幅"] = pd.to_numeric(big_df["近一年涨跌幅"], errors="coerce") big_df["交易日期"] = pd.to_datetime(big_df["交易日期"], errors="coerce").dt.date return big_df def _get_page_num_gpzy_market_pledge_ratio_detail() -> int: """ 东方财富网-数据中心-特色数据-股权质押-重要股东股权质押明细 https://data.eastmoney.com/gpzy/pledgeDetail.aspx :return: int 获取 重要股东股权质押明细 的总页数 """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "NOTICE_DATE", "sortTypes": "-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPTA_APP_ACCUMDETAILS", "columns": "ALL", "quoteColumns": "", "source": "WEB", "client": "WEB", } r = requests.get(url, params=params) data_json = r.json() total_page = math.ceil(int(data_json["result"]["count"]) / 500) return total_page def stock_gpzy_pledge_ratio_detail_em() -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-股权质押-重要股东股权质押明细 https://data.eastmoney.com/gpzy/pledgeDetail.aspx :return: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" total_page = _get_page_num_gpzy_market_pledge_ratio_detail() big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, total_page + 1), leave=False): params = { "sortColumns": "NOTICE_DATE", "sortTypes": "-1", "pageSize": "500", "pageNumber": page, "reportName": "RPTA_APP_ACCUMDETAILS", "columns": "ALL", "quoteColumns": "", "source": "WEB", "client": "WEB", } 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", "股票简称", "_", "股票代码", "股东名称", "_", "_", "_", "公告日期", "质押机构", "质押股份数量", "占所持股份比例", "占总股本比例", "质押日收盘价", "质押开始日期", "_", "_", "_", "_", "_", "_", "_", "预估平仓线", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "最新价", "_", "_", "_", "_", "_", "_", "_", "_", ] big_df = big_df[ [ "序号", "股票代码", "股票简称", "股东名称", "质押股份数量", "占所持股份比例", "占总股本比例", "质押机构", "最新价", "质押日收盘价", "预估平仓线", "质押开始日期", "公告日期", ] ] big_df["质押股份数量"] = pd.to_numeric(big_df["质押股份数量"], errors="coerce") big_df["占所持股份比例"] = pd.to_numeric(big_df["占所持股份比例"], errors="coerce") big_df["占总股本比例"] = pd.to_numeric(big_df["占总股本比例"], errors="coerce") big_df["最新价"] = pd.to_numeric(big_df["最新价"], errors="coerce") big_df["质押日收盘价"] = pd.to_numeric(big_df["质押日收盘价"], errors="coerce") big_df["预估平仓线"] = pd.to_numeric(big_df["预估平仓线"], errors="coerce") big_df["公告日期"] = pd.to_datetime(big_df["公告日期"], errors="coerce").dt.date big_df["质押开始日期"] = pd.to_datetime( big_df["质押开始日期"], errors="coerce" ).dt.date return big_df def stock_gpzy_distribute_statistics_company_em() -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-股权质押-质押机构分布统计-证券公司 https://data.eastmoney.com/gpzy/distributeStatistics.aspx :return: 质押机构分布统计-证券公司 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "ORG_NUM", "sortTypes": "-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_GDZY_ZYJG_SUM", "columns": "ALL", "quoteColumns": "", "source": "WEB", "client": "WEB", "filter": '(PFORG_TYPE="证券")', } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["result"]["data"]) temp_df.reset_index(inplace=True) temp_df["index"] = temp_df.index + 1 temp_df.columns = [ "序号", "_", "_", "_", "_", "质押机构", "_", "质押公司数量", "质押笔数", "质押数量", "未达预警线比例", "达到预警线未达平仓线比例", "达到平仓线比例", "_", "_", ] temp_df = temp_df[ [ "序号", "质押机构", "质押公司数量", "质押笔数", "质押数量", "未达预警线比例", "达到预警线未达平仓线比例", "达到平仓线比例", ] ] temp_df["质押公司数量"] = pd.to_numeric(temp_df["质押公司数量"], errors="coerce") temp_df["质押笔数"] = pd.to_numeric(temp_df["质押笔数"], errors="coerce") temp_df["质押数量"] = pd.to_numeric(temp_df["质押数量"], errors="coerce") temp_df["未达预警线比例"] = pd.to_numeric( temp_df["未达预警线比例"], errors="coerce" ) temp_df["达到预警线未达平仓线比例"] = pd.to_numeric( temp_df["达到预警线未达平仓线比例"], errors="coerce" ) temp_df["达到平仓线比例"] = pd.to_numeric( temp_df["达到平仓线比例"], errors="coerce" ) return temp_df def stock_gpzy_distribute_statistics_bank_em() -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-股权质押-质押机构分布统计-银行 https://data.eastmoney.com/gpzy/distributeStatistics.aspx :return: 质押机构分布统计-银行 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "ORG_NUM", "sortTypes": "-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_GDZY_ZYJG_SUM", "columns": "ALL", "quoteColumns": "", "source": "WEB", "client": "WEB", "filter": '(PFORG_TYPE="银行")', } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["result"]["data"]) temp_df.reset_index(inplace=True) temp_df["index"] = temp_df.index + 1 temp_df.columns = [ "序号", "_", "_", "_", "_", "质押机构", "_", "质押公司数量", "质押笔数", "质押数量", "未达预警线比例", "达到预警线未达平仓线比例", "达到平仓线比例", "_", "_", ] temp_df = temp_df[ [ "序号", "质押机构", "质押公司数量", "质押笔数", "质押数量", "未达预警线比例", "达到预警线未达平仓线比例", "达到平仓线比例", ] ] temp_df["质押公司数量"] = pd.to_numeric(temp_df["质押公司数量"], errors="coerce") temp_df["质押笔数"] = pd.to_numeric(temp_df["质押笔数"], errors="coerce") temp_df["质押数量"] = pd.to_numeric(temp_df["质押数量"], errors="coerce") temp_df["未达预警线比例"] = pd.to_numeric( temp_df["未达预警线比例"], errors="coerce" ) temp_df["达到预警线未达平仓线比例"] = pd.to_numeric( temp_df["达到预警线未达平仓线比例"], errors="coerce" ) temp_df["达到平仓线比例"] = pd.to_numeric( temp_df["达到平仓线比例"], errors="coerce" ) return temp_df def stock_gpzy_industry_data_em() -> pd.DataFrame: """ 东方财富网-数据中心-特色数据-股权质押-上市公司质押比例-行业数据 https://data.eastmoney.com/gpzy/industryData.aspx :return: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "AVERAGE_PLEDGE_RATIO", "sortTypes": "-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_CSDC_INDUSTRY_STATISTICS", "columns": "INDUSTRY_CODE,INDUSTRY,TRADE_DATE,AVERAGE_PLEDGE_RATIO,ORG_NUM,PLEDGE_TOTAL_NUM," "TOTAL_PLEDGE_SHARES,PLEDGE_TOTAL_MARKETCAP", "quoteColumns": "", "source": "WEB", "client": "WEB", } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["result"]["data"]) temp_df.reset_index(inplace=True) temp_df["index"] = temp_df.index + 1 temp_df.columns = [ "序号", "-", "行业", "统计时间", "平均质押比例", "公司家数", "质押总笔数", "质押总股本", "最新质押市值", ] temp_df = temp_df[ [ "序号", "行业", "平均质押比例", "公司家数", "质押总笔数", "质押总股本", "最新质押市值", "统计时间", ] ] temp_df["统计时间"] = pd.to_datetime(temp_df["统计时间"], errors="coerce").dt.date temp_df["平均质押比例"] = pd.to_numeric(temp_df["平均质押比例"], errors="coerce") temp_df["公司家数"] = pd.to_numeric(temp_df["公司家数"], errors="coerce") temp_df["质押总笔数"] = pd.to_numeric(temp_df["质押总笔数"], errors="coerce") temp_df["质押总股本"] = pd.to_numeric(temp_df["质押总股本"], errors="coerce") temp_df["最新质押市值"] = pd.to_numeric(temp_df["最新质押市值"], errors="coerce") return temp_df if __name__ == "__main__": stock_gpzy_profile_em_df = stock_gpzy_profile_em() print(stock_gpzy_profile_em_df) stock_em_gpzy_pledge_ratio_df = stock_gpzy_pledge_ratio_em(date="20241220") print(stock_em_gpzy_pledge_ratio_df) stock_gpzy_pledge_ratio_detail_em_df = stock_gpzy_pledge_ratio_detail_em() print(stock_gpzy_pledge_ratio_detail_em_df) stock_em_gpzy_distribute_statistics_company_df = ( stock_gpzy_distribute_statistics_company_em() ) print(stock_em_gpzy_distribute_statistics_company_df) stock_em_gpzy_distribute_statistics_bank_df = ( stock_gpzy_distribute_statistics_bank_em() ) print(stock_em_gpzy_distribute_statistics_bank_df) stock_gpzy_industry_data_em_df = stock_gpzy_industry_data_em() print(stock_gpzy_industry_data_em_df)