#!/usr/bin/env python # -*- coding:utf-8 -*- """ Date: 2025/3/18 15:00 Desc: 东方财富网-数据中心-年报季报-分红送配 https://data.eastmoney.com/yjfp/ """ import pandas as pd import requests from akshare.utils.tqdm import get_tqdm def stock_fhps_em(date: str = "20231231") -> pd.DataFrame: """ 东方财富网-数据中心-年报季报-分红送配 https://data.eastmoney.com/yjfp/ :param date: 分红送配报告期 :type date: str :return: 分红送配 :rtype: pandas.DataFrame """ import warnings warnings.simplefilter(action="ignore", category=FutureWarning) url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "PLAN_NOTICE_DATE", "sortTypes": "-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_SHAREBONUS_DET", "columns": "ALL", "quoteColumns": "", "js": '{"data":(x),"pages":(tp)}', "source": "WEB", "client": "WEB", "filter": f"""(REPORT_DATE='{"-".join([date[:4], date[4:6], date[6:]])}')""", } r = requests.get(url, params=params) data_json = r.json() total_pages = int(data_json["result"]["pages"]) big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, total_pages + 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.columns = [ "_", "名称", "_", "_", "代码", "送转股份-送转总比例", "送转股份-送转比例", "送转股份-转股比例", "现金分红-现金分红比例", "预案公告日", "股权登记日", "除权除息日", "_", "方案进度", "_", "最新公告日期", "_", "_", "_", "每股收益", "每股净资产", "每股公积金", "每股未分配利润", "净利润同比增长", "总股本", "_", "现金分红-股息率", "-", "-", "-", ] big_df = big_df[ [ "代码", "名称", "送转股份-送转总比例", "送转股份-送转比例", "送转股份-转股比例", "现金分红-现金分红比例", "现金分红-股息率", "每股收益", "每股净资产", "每股公积金", "每股未分配利润", "净利润同比增长", "总股本", "预案公告日", "股权登记日", "除权除息日", "方案进度", "最新公告日期", ] ] big_df["送转股份-送转总比例"] = pd.to_numeric( big_df["送转股份-送转总比例"], errors="coerce" ) big_df["送转股份-送转比例"] = pd.to_numeric( big_df["送转股份-送转比例"], errors="coerce" ) big_df["送转股份-转股比例"] = pd.to_numeric( big_df["送转股份-转股比例"], errors="coerce" ) big_df["现金分红-现金分红比例"] = pd.to_numeric( big_df["现金分红-现金分红比例"], errors="coerce" ) big_df["现金分红-股息率"] = pd.to_numeric( big_df["现金分红-股息率"], errors="coerce" ) big_df["每股收益"] = pd.to_numeric(big_df["每股收益"], errors="coerce") big_df["每股净资产"] = pd.to_numeric(big_df["每股净资产"], errors="coerce") big_df["每股公积金"] = pd.to_numeric(big_df["每股公积金"], errors="coerce") big_df["每股未分配利润"] = pd.to_numeric(big_df["每股未分配利润"], errors="coerce") big_df["净利润同比增长"] = pd.to_numeric(big_df["净利润同比增长"], errors="coerce") big_df["总股本"] = pd.to_numeric(big_df["总股本"], errors="coerce") big_df["预案公告日"] = pd.to_datetime(big_df["预案公告日"], errors="coerce").dt.date big_df["股权登记日"] = pd.to_datetime(big_df["股权登记日"], errors="coerce").dt.date big_df["除权除息日"] = pd.to_datetime(big_df["除权除息日"], errors="coerce").dt.date big_df["最新公告日期"] = pd.to_datetime( big_df["最新公告日期"], errors="coerce" ).dt.date big_df.sort_values(["最新公告日期"], inplace=True, ignore_index=True) return big_df def stock_fhps_detail_em(symbol: str = "300073") -> pd.DataFrame: """ 东方财富网-数据中心-分红送配-分红送配详情 https://data.eastmoney.com/yjfp/detail/300073.html :param symbol: 股票代码 :type symbol: str :return: 分红送配详情 :rtype: pandas.DataFrame """ url = "https://datacenter-web.eastmoney.com/api/data/v1/get" params = { "sortColumns": "REPORT_DATE", "sortTypes": "-1", "pageSize": "500", "pageNumber": "1", "reportName": "RPT_SHAREBONUS_DET", "columns": "ALL", "quoteColumns": "", "js": '{"data":(x),"pages":(tp)}', "source": "WEB", "client": "WEB", "filter": f"""(SECURITY_CODE="{symbol}")""", } r = requests.get(url, params=params) data_json = r.json() total_pages = int(data_json["result"]["pages"]) big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, total_pages + 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.columns = [ "_", "-", "_", "_", "-", "送转股份-送转总比例", "送转股份-送股比例", "送转股份-转股比例", "现金分红-现金分红比例", "业绩披露日期", "股权登记日", "除权除息日", "报告期", "方案进度", "现金分红-现金分红比例描述", "最新公告日期", "-", "-", "-", "每股收益", "每股净资产", "每股公积金", "每股未分配利润", "净利润同比增长", "总股本", "预案公告日", "现金分红-股息率", "-", "-", "-", ] big_df = big_df[ [ "报告期", "业绩披露日期", "送转股份-送转总比例", "送转股份-送股比例", "送转股份-转股比例", "现金分红-现金分红比例", "现金分红-现金分红比例描述", "现金分红-股息率", "每股收益", "每股净资产", "每股公积金", "每股未分配利润", "净利润同比增长", "总股本", "预案公告日", "股权登记日", "除权除息日", "方案进度", "最新公告日期", ] ] big_df["报告期"] = pd.to_datetime(big_df["报告期"], errors="coerce").dt.date big_df["业绩披露日期"] = pd.to_datetime( big_df["业绩披露日期"], errors="coerce" ).dt.date big_df["预案公告日"] = pd.to_datetime(big_df["预案公告日"], errors="coerce").dt.date big_df["股权登记日"] = pd.to_datetime(big_df["股权登记日"], errors="coerce").dt.date big_df["除权除息日"] = pd.to_datetime(big_df["除权除息日"], errors="coerce").dt.date big_df["最新公告日期"] = pd.to_datetime( big_df["最新公告日期"], errors="coerce" ).dt.date big_df["送转股份-送转总比例"] = pd.to_numeric( big_df["送转股份-送转总比例"], errors="coerce" ) big_df["送转股份-送股比例"] = pd.to_numeric( big_df["送转股份-送股比例"], errors="coerce" ) big_df["送转股份-转股比例"] = pd.to_numeric( big_df["送转股份-转股比例"], errors="coerce" ) big_df["现金分红-现金分红比例"] = pd.to_numeric( big_df["现金分红-现金分红比例"], errors="coerce" ) big_df["现金分红-股息率"] = pd.to_numeric( big_df["现金分红-股息率"], errors="coerce" ) big_df["每股收益"] = pd.to_numeric(big_df["每股收益"], errors="coerce") big_df["每股净资产"] = pd.to_numeric(big_df["每股净资产"], errors="coerce") big_df["每股公积金"] = pd.to_numeric(big_df["每股公积金"], errors="coerce") big_df["每股未分配利润"] = pd.to_numeric(big_df["每股未分配利润"], errors="coerce") big_df["净利润同比增长"] = pd.to_numeric(big_df["净利润同比增长"], errors="coerce") big_df["总股本"] = pd.to_numeric(big_df["总股本"], errors="coerce") big_df.sort_values(["报告期"], inplace=True, ignore_index=True) return big_df if __name__ == "__main__": stock_fhps_em_df = stock_fhps_em(date="20231231") print(stock_fhps_em_df) stock_fhps_detail_em_df = stock_fhps_detail_em(symbol="000005") print(stock_fhps_detail_em_df)