#!/usr/bin/env python # -*- coding:utf-8 -*- """ Date: 2024/9/20 15:30 Desc: 东方财富-数据中心-年报季报-业绩快报-三大报表 资产负债表 https://data.eastmoney.com/bbsj/202003/zcfz.html 利润表 https://data.eastmoney.com/bbsj/202003/lrb.html 现金流量表 https://data.eastmoney.com/bbsj/202003/xjll.html """ import pandas as pd import requests from akshare.utils.tqdm import get_tqdm def stock_zcfz_em(date: str = "20240331") -> pd.DataFrame: """ 东方财富-数据中心-年报季报-业绩快报-资产负债表 https://data.eastmoney.com/bbsj/202003/zcfz.html :param date: choice of {"20200331", "20200630", "20200930", "20201231", "..."}; 从 20100331 开始 :type date: str :return: 资产负债表 :rtype: pandas.DataFrame """ import warnings warnings.filterwarnings(action="ignore", category=FutureWarning) url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "NOTICE_DATE,SECURITY_CODE", "sortTypes": "-1,-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_DMSK_FN_BALANCE", "columns": "ALL", "filter": f"""(SECURITY_TYPE_CODE in ("058001001","058001008"))(TRADE_MARKET_CODE!="069001017") (REPORT_DATE='{"-".join([date[:4], date[4:6], date[6:]])}')""", } r = requests.get(url, params=params) data_json = r.json() page_num = data_json["result"]["pages"] big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, page_num + 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], join="outer", 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", "_", "_", "_", "_", "_", "_", "_", "公告日期", "_", "资产-总资产", "_", "资产-货币资金", "_", "资产-应收账款", "_", "资产-存货", "_", "负债-总负债", "负债-应付账款", "_", "负债-预收账款", "_", "股东权益合计", "_", "资产-总资产同比", "负债-总负债同比", "_", "资产负债率", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", ] big_df = big_df[ [ "序号", "股票代码", "股票简称", "资产-货币资金", "资产-应收账款", "资产-存货", "资产-总资产", "资产-总资产同比", "负债-应付账款", "负债-预收账款", "负债-总负债", "负债-总负债同比", "资产负债率", "股东权益合计", "公告日期", ] ] big_df["资产-货币资金"] = pd.to_numeric(big_df["资产-货币资金"], errors="coerce") big_df["资产-应收账款"] = pd.to_numeric(big_df["资产-应收账款"], errors="coerce") big_df["资产-存货"] = pd.to_numeric(big_df["资产-存货"], errors="coerce") big_df["资产-总资产"] = pd.to_numeric(big_df["资产-总资产"], errors="coerce") big_df["资产-总资产同比"] = pd.to_numeric( big_df["资产-总资产同比"], errors="coerce" ) big_df["负债-应付账款"] = pd.to_numeric(big_df["负债-应付账款"], errors="coerce") big_df["负债-预收账款"] = pd.to_numeric(big_df["负债-预收账款"], errors="coerce") big_df["负债-总负债"] = pd.to_numeric(big_df["负债-总负债"], errors="coerce") big_df["负债-总负债同比"] = pd.to_numeric( big_df["负债-总负债同比"], errors="coerce" ) big_df["资产负债率"] = pd.to_numeric(big_df["资产负债率"], errors="coerce") big_df["股东权益合计"] = pd.to_numeric(big_df["股东权益合计"], errors="coerce") big_df["股东权益合计"] = pd.to_numeric(big_df["股东权益合计"], errors="coerce") big_df["公告日期"] = pd.to_datetime(big_df["公告日期"], errors="coerce").dt.date return big_df def stock_zcfz_bj_em(date: str = "20240331") -> pd.DataFrame: """ 东方财富-数据中心-年报季报-业绩快报-资产负债表 https://data.eastmoney.com/bbsj/202003/zcfz.html :param date: choice of {"20200331", "20200630", "20200930", "20201231", "..."}; 从 20100331 开始 :type date: str :return: 资产负债表 :rtype: pandas.DataFrame """ import warnings warnings.filterwarnings(action="ignore", category=FutureWarning) url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "NOTICE_DATE,SECURITY_CODE", "sortTypes": "-1,-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_DMSK_FN_BALANCE", "columns": "ALL", "filter": f"""(TRADE_MARKET_CODE="069001017") (REPORT_DATE='{"-".join([date[:4], date[4:6], date[6:]])}')""", } r = requests.get(url, params=params) data_json = r.json() page_num = data_json["result"]["pages"] big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, page_num + 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], join="outer", 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", "_", "_", "_", "_", "_", "_", "_", "公告日期", "_", "资产-总资产", "_", "资产-货币资金", "_", "资产-应收账款", "_", "资产-存货", "_", "负债-总负债", "负债-应付账款", "_", "负债-预收账款", "_", "股东权益合计", "_", "资产-总资产同比", "负债-总负债同比", "_", "资产负债率", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", ] big_df = big_df[ [ "序号", "股票代码", "股票简称", "资产-货币资金", "资产-应收账款", "资产-存货", "资产-总资产", "资产-总资产同比", "负债-应付账款", "负债-预收账款", "负债-总负债", "负债-总负债同比", "资产负债率", "股东权益合计", "公告日期", ] ] big_df["资产-货币资金"] = pd.to_numeric(big_df["资产-货币资金"], errors="coerce") big_df["资产-应收账款"] = pd.to_numeric(big_df["资产-应收账款"], errors="coerce") big_df["资产-存货"] = pd.to_numeric(big_df["资产-存货"], errors="coerce") big_df["资产-总资产"] = pd.to_numeric(big_df["资产-总资产"], errors="coerce") big_df["资产-总资产同比"] = pd.to_numeric( big_df["资产-总资产同比"], errors="coerce" ) big_df["负债-应付账款"] = pd.to_numeric(big_df["负债-应付账款"], errors="coerce") big_df["负债-预收账款"] = pd.to_numeric(big_df["负债-预收账款"], errors="coerce") big_df["负债-总负债"] = pd.to_numeric(big_df["负债-总负债"], errors="coerce") big_df["负债-总负债同比"] = pd.to_numeric( big_df["负债-总负债同比"], errors="coerce" ) big_df["资产负债率"] = pd.to_numeric(big_df["资产负债率"], errors="coerce") big_df["股东权益合计"] = pd.to_numeric(big_df["股东权益合计"], errors="coerce") big_df["股东权益合计"] = pd.to_numeric(big_df["股东权益合计"], errors="coerce") big_df["公告日期"] = pd.to_datetime(big_df["公告日期"], errors="coerce").dt.date return big_df def stock_lrb_em(date: str = "20240331") -> pd.DataFrame: """ 东方财富-数据中心-年报季报-业绩快报-利润表 https://data.eastmoney.com/bbsj/202003/lrb.html :param date: choice of {"20200331", "20200630", "20200930", "20201231", "..."}; 从 20100331 开始 :type date: str :return: 利润表 :rtype: pandas.DataFrame """ import warnings warnings.filterwarnings(action="ignore", category=FutureWarning) url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "NOTICE_DATE,SECURITY_CODE", "sortTypes": "-1,-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_DMSK_FN_INCOME", "columns": "ALL", "filter": f"""(SECURITY_TYPE_CODE in ("058001001","058001008"))(TRADE_MARKET_CODE!="069001017") (REPORT_DATE='{"-".join([date[:4], date[4:6], date[6:]])}')""", } r = requests.get(url, params=params) data_json = r.json() page_num = data_json["result"]["pages"] big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, page_num + 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", "_", "_", "_", "_", "_", "_", "_", "公告日期", "_", "净利润", "营业总收入", "营业总支出-营业总支出", "_", "营业总支出-营业支出", "_", "_", "营业总支出-销售费用", "营业总支出-管理费用", "营业总支出-财务费用", "营业利润", "利润总额", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "营业总收入同比", "_", "净利润同比", "_", "_", ] big_df = big_df[ [ "序号", "股票代码", "股票简称", "净利润", "净利润同比", "营业总收入", "营业总收入同比", "营业总支出-营业支出", "营业总支出-销售费用", "营业总支出-管理费用", "营业总支出-财务费用", "营业总支出-营业总支出", "营业利润", "利润总额", "公告日期", ] ] big_df["净利润"] = pd.to_numeric(big_df["净利润"], errors="coerce") big_df["净利润同比"] = pd.to_numeric(big_df["净利润同比"], errors="coerce") big_df["营业总收入"] = pd.to_numeric(big_df["营业总收入"], errors="coerce") big_df["营业总收入同比"] = pd.to_numeric(big_df["营业总收入同比"], errors="coerce") big_df["营业总支出-营业支出"] = pd.to_numeric( big_df["营业总支出-营业支出"], errors="coerce" ) big_df["营业总支出-销售费用"] = pd.to_numeric( big_df["营业总支出-销售费用"], errors="coerce" ) big_df["营业总支出-管理费用"] = pd.to_numeric( big_df["营业总支出-管理费用"], errors="coerce" ) big_df["营业总支出-财务费用"] = pd.to_numeric( big_df["营业总支出-财务费用"], errors="coerce" ) big_df["营业总支出-营业总支出"] = pd.to_numeric( big_df["营业总支出-营业总支出"], errors="coerce" ) big_df["营业利润"] = pd.to_numeric(big_df["营业利润"], errors="coerce") big_df["利润总额"] = pd.to_numeric(big_df["利润总额"], errors="coerce") big_df["公告日期"] = pd.to_datetime(big_df["公告日期"], errors="coerce").dt.date return big_df def stock_xjll_em(date: str = "20240331") -> pd.DataFrame: """ 东方财富-数据中心-年报季报-业绩快报-现金流量表 https://data.eastmoney.com/bbsj/202003/xjll.html :param date: choice of {"20200331", "20200630", "20200930", "20201231", "..."}; 从 20100331 开始 :type date: str :return: 现金流量表 :rtype: pandas.DataFrame """ import warnings warnings.filterwarnings(action="ignore", category=FutureWarning) url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "NOTICE_DATE,SECURITY_CODE", "sortTypes": "-1,-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_DMSK_FN_CASHFLOW", "columns": "ALL", "filter": f"""(SECURITY_TYPE_CODE in ("058001001","058001008"))(TRADE_MARKET_CODE!="069001017") (REPORT_DATE='{"-".join([date[:4], date[4:6], date[6:]])}')""", } r = requests.get(url, params=params) data_json = r.json() page_num = data_json["result"]["pages"] big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, page_num + 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", "_", "_", "_", "_", "_", "_", "_", "公告日期", "_", "经营性现金流-现金流量净额", "经营性现金流-净现金流占比", "_", "_", "_", "_", "投资性现金流-现金流量净额", "投资性现金流-净现金流占比", "_", "_", "_", "_", "融资性现金流-现金流量净额", "融资性现金流-净现金流占比", "净现金流-净现金流", "净现金流-同比增长", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", "_", ] big_df = big_df[ [ "序号", "股票代码", "股票简称", "净现金流-净现金流", "净现金流-同比增长", "经营性现金流-现金流量净额", "经营性现金流-净现金流占比", "投资性现金流-现金流量净额", "投资性现金流-净现金流占比", "融资性现金流-现金流量净额", "融资性现金流-净现金流占比", "公告日期", ] ] big_df["净现金流-净现金流"] = pd.to_numeric( big_df["净现金流-净现金流"], errors="coerce" ) big_df["净现金流-同比增长"] = pd.to_numeric( big_df["净现金流-同比增长"], errors="coerce" ) big_df["经营性现金流-现金流量净额"] = pd.to_numeric( big_df["经营性现金流-现金流量净额"], errors="coerce" ) big_df["经营性现金流-净现金流占比"] = pd.to_numeric( big_df["经营性现金流-净现金流占比"], errors="coerce" ) big_df["投资性现金流-现金流量净额"] = pd.to_numeric( big_df["投资性现金流-现金流量净额"], errors="coerce" ) big_df["投资性现金流-净现金流占比"] = pd.to_numeric( big_df["投资性现金流-净现金流占比"], errors="coerce" ) big_df["融资性现金流-现金流量净额"] = pd.to_numeric( big_df["融资性现金流-现金流量净额"], errors="coerce" ) big_df["融资性现金流-净现金流占比"] = pd.to_numeric( big_df["融资性现金流-净现金流占比"], errors="coerce" ) big_df["公告日期"] = pd.to_datetime(big_df["公告日期"], errors="coerce").dt.date return big_df if __name__ == "__main__": stock_zcfz_em_df = stock_zcfz_em(date="20240331") print(stock_zcfz_em_df) stock_zcfz_bj_em_df = stock_zcfz_bj_em(date="20240331") print(stock_zcfz_bj_em_df) stock_lrb_em_df = stock_lrb_em(date="20240331") print(stock_lrb_em_df) stock_xjll_em_df = stock_xjll_em(date="20240331") print(stock_xjll_em_df)