# -*- coding:utf-8 -*- # !/usr/bin/env python """ Date: 2025/8/7 18:30 Desc: 财新数据-指数报告-数字经济指数 https://yun.ccxe.com.cn/indices/dei """ import pandas as pd import requests def index_pmi_com_cx() -> pd.DataFrame: """ 财新数据-指数报告-财新中国 PMI-综合 PMI https://yun.ccxe.com.cn/indices/pmi :return: 财新中国 PMI-综合 PMI :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "com"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "综合PMI", "日期"] temp_df = temp_df[ [ "日期", "综合PMI", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_pmi_man_cx() -> pd.DataFrame: """ 财新数据-指数报告-财新中国 PMI-制造业 PMI https://yun.ccxe.com.cn/indices/pmi :return: 财新中国 PMI-制造业 PMI :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "man"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "制造业PMI", "日期"] temp_df = temp_df[ [ "日期", "制造业PMI", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_pmi_ser_cx() -> pd.DataFrame: """ 财新数据-指数报告-财新中国 PMI-服务业 PMI https://yun.ccxe.com.cn/indices/pmi :return: 财新中国 PMI-服务业 PMI :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "ser"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "服务业PMI", "日期"] temp_df = temp_df[ [ "日期", "服务业PMI", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_dei_cx() -> pd.DataFrame: """ 财新数据-指数报告-数字经济指数 https://yun.ccxe.com.cn/indices/dei :return: 数字经济指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "dei"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "数字经济指数", "日期"] temp_df = temp_df[ [ "日期", "数字经济指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_ii_cx() -> pd.DataFrame: """ 财新数据-指数报告-产业指数 https://yun.ccxe.com.cn/indices/dei :return: 产业指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "ii"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "产业指数", "日期"] temp_df = temp_df[ [ "日期", "产业指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_si_cx() -> pd.DataFrame: """ 财新数据-指数报告-溢出指数 https://yun.ccxe.com.cn/indices/dei :return: 溢出指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "si"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "溢出指数", "日期"] temp_df = temp_df[ [ "日期", "溢出指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_fi_cx() -> pd.DataFrame: """ 财新数据-指数报告-融合指数 https://yun.ccxe.com.cn/indices/dei :return: 融合指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "fi"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "融合指数", "日期"] temp_df = temp_df[ [ "日期", "融合指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_bi_cx() -> pd.DataFrame: """ 财新数据-指数报告-基础指数 https://yun.ccxe.com.cn/indices/dei :return: 基础指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "bi"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "基础指数", "日期"] temp_df = temp_df[ [ "日期", "基础指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_nei_cx() -> pd.DataFrame: """ 财新数据-指数报告-中国新经济指数 https://yun.ccxe.com.cn/indices/nei :return: 中国新经济指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "nei"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "中国新经济指数", "日期"] temp_df = temp_df[ [ "日期", "中国新经济指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_li_cx() -> pd.DataFrame: """ 财新数据-指数报告-劳动力投入指数 https://yun.ccxe.com.cn/indices/nei :return: 劳动力投入指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "li"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "劳动力投入指数", "日期"] temp_df = temp_df[ [ "日期", "劳动力投入指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_ci_cx() -> pd.DataFrame: """ 财新数据-指数报告-资本投入指数 https://yun.ccxe.com.cn/indices/nei :return: 资本投入指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "ci"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "资本投入指数", "日期"] temp_df = temp_df[ [ "日期", "资本投入指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_ti_cx() -> pd.DataFrame: """ 财新数据-指数报告-科技投入指数 https://yun.ccxe.com.cn/indices/nei :return: 科技投入指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "ti"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "科技投入指数", "日期"] temp_df = temp_df[ [ "日期", "科技投入指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_neaw_cx() -> pd.DataFrame: """ 财新数据-指数报告-新经济行业入职平均工资水平 https://yun.ccxe.com.cn/indices/nei :return: 新经济行业入职平均工资水平 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "neaw"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "新经济行业入职平均工资水平", "日期"] temp_df = temp_df[ [ "日期", "新经济行业入职平均工资水平", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_awpr_cx() -> pd.DataFrame: """ 财新数据-指数报告-新经济入职工资溢价水平 https://yun.ccxe.com.cn/indices/nei :return: 新经济入职工资溢价水平 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = {"type": "awpr"} r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "新经济入职工资溢价水平", "日期"] temp_df = temp_df[ [ "日期", "新经济入职工资溢价水平", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_cci_cx() -> pd.DataFrame: """ 财新数据-指数报告-大宗商品指数 https://yun.ccxe.com.cn/indices/nei :return: 大宗商品指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = { "type": "cci", "code": "1000050", "month": "-1", } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化值", "大宗商品指数", "日期"] temp_df = temp_df[ [ "日期", "大宗商品指数", "变化值", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_qli_cx() -> pd.DataFrame: """ 财新数据-指数报告-高质量因子 https://yun.ccxe.com.cn/indices/qli :return: 高质量因子 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = { "type": "qli", "code": "1000050", "month": "-1", } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化幅度", "高质量因子指数", "日期"] temp_df = temp_df[ [ "日期", "高质量因子指数", "变化幅度", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_ai_cx() -> pd.DataFrame: """ 财新数据-指数报告-AI策略指数 https://yun.ccxe.com.cn/indices/ai :return: AI策略指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = { "type": "ai", "code": "1000050", "month": "-1", } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化幅度", "AI策略指数", "日期"] temp_df = temp_df[ [ "日期", "AI策略指数", "变化幅度", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_bei_cx() -> pd.DataFrame: """ 财新数据-指数报告-基石经济指数 https://yun.ccxe.com.cn/indices/bei :return: 基石经济指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = { "type": "ind", "code": "930927", "month": "-1", } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化幅度", "基石经济指数", "日期"] temp_df = temp_df[ [ "日期", "基石经济指数", "变化幅度", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df def index_neei_cx() -> pd.DataFrame: """ 财新数据-指数报告-新动能指数 https://yun.ccxe.com.cn/indices/neei :return: 新动能指数 :rtype: pandas.DataFrame """ url = "https://yun.ccxe.com.cn/api/index/pro/cxIndexTrendInfo" params = { "type": "ind", "code": "930928", "month": "1", } r = requests.get(url, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["data"]) temp_df.columns = ["变化幅度", "新动能指数", "日期"] temp_df = temp_df[ [ "日期", "新动能指数", "变化幅度", ] ] temp_df["日期"] = ( pd.to_datetime(temp_df["日期"], unit="ms", utc=True) .dt.tz_convert("Asia/Shanghai") .dt.date ) return temp_df if __name__ == "__main__": index_pmi_com_cx_df = index_pmi_com_cx() print(index_pmi_com_cx_df) index_pmi_man_cx_df = index_pmi_man_cx() print(index_pmi_man_cx_df) index_pmi_ser_cx_df = index_pmi_ser_cx() print(index_pmi_ser_cx_df) index_dei_cx_df = index_dei_cx() print(index_dei_cx_df) index_ii_cx_df = index_ii_cx() print(index_ii_cx_df) index_si_cx_df = index_si_cx() print(index_si_cx_df) index_fi_cx_df = index_fi_cx() print(index_fi_cx_df) index_bi_cx_df = index_bi_cx() print(index_bi_cx_df) index_nei_cx_df = index_nei_cx() print(index_nei_cx_df) index_li_cx_df = index_li_cx() print(index_li_cx_df) index_ci_cx_df = index_ci_cx() print(index_ci_cx_df) index_ti_cx_df = index_ti_cx() print(index_ti_cx_df) index_neaw_cx_df = index_neaw_cx() print(index_neaw_cx_df) index_awpr_cx_df = index_awpr_cx() print(index_awpr_cx_df) index_cci_cx_df = index_cci_cx() print(index_cci_cx_df) index_qli_cx_df = index_qli_cx() print(index_qli_cx_df) index_ai_cx_df = index_ai_cx() print(index_ai_cx_df) index_bei_cx_df = index_bei_cx() print(index_bei_cx_df) index_neei_cx_df = index_neei_cx() print(index_neei_cx_df)