优矿基本面数据

未分类

1. 登入优矿Notebook用数据API获取数据保存为EXCEL
2. 下载到本地转存至本地MongoDB

登入优矿Notebook用数据API获取数据

import pandas as pd
#获取HS300所有股票的secID
HS300_list = set_universe('HS300')
#保存为excel的文件名
writer = pd.ExcelWriter("HS300_factors.xlsx")
for ticker in HS300_list:
    data = DataAPI.MktStockFactorsDateRangeGet(secID=ticker, beginDate='20160101',  field=['tradeDate','secID', 'close', 'ROE', 'PE', 'PB', 'PS'])
    data.to_excel(writer, ticker[0:6])
writer.save()

下载到本地转存至本地MongoDB
只需要将你文件的路径复制至path即可

from fxdayu_data.data.handler.mongo_handler import MongoHandler
import pandas as pd
from datetime import timedelta
path = "C:\\Users\\small\\Desktop\\YouQuant_Data\\HS300_factors.xlsx"
DAY_END = timedelta(hours=15)
#存储至本地
mh = MongoHandler(db='YouQuant_Fundamental')
#存储至服务器
# mh = MongoHandler("192.168.0.103", 30000, db='Basic')
def coder(code):
    if code.startswith("6"):
        return "sh" + code
    elif code.startswith("0") or code.startswith("3"):
        return "sz" + code
    else:
        return code
def standard(frame):
    frame['datetime'] = pd.to_datetime(frame.pop("tradeDate")) + DAY_END
    frame.pop("secID")
    return frame
def read_sheets(excel_file):
    sheets = excel_file.sheet_names
    print sheets
    for sheet in sheets:
        yield sheet, excel_file.parse(sheet)
def save_basic(file_path):
    ef = pd.ExcelFile(file_path)
    for code, frame in read_sheets(ef):
        print mh.inplace(
            standard(frame),
            coder(code)
        )
if __name__ == '__main__':
    save_basic(path)

任务
1. 将沪深300， 中小板， 创业板分类下载至Mongodb
2. 研究优矿公开的130个因子，保存最常的20个基本面因子
3. 由于优矿的数据处理量有限，需要将时间以年为单位分批存入，需要10年至今的