calcu_3year_average_pe.py 文件源码

def filter_stock_by_average_pe(min, max):
    path = os.path.join(current_folder, '3????????????%s.csv' % today)
    if not os.path.exists(path):  # ?????3???????
        calcu_all_stocks_3year_average_profit(calcu_average_profit_end_year)

    gplb = pd.read_csv(path, index_col=0, encoding='utf-8')

    # ????????
    price_path = os.path.join(current_folder, today + '????.csv')
    if not os.path.exists(price_path):
        ts.get_today_all().set_index('code').to_csv(price_path, encoding="utf-8")

    current_price = pd.read_csv(price_path, encoding="utf-8", index_col=0)
    current_price = current_price[['trade']]
    current_price.columns = ['??']
    gplb = gplb[
        ['??', '??', '??', '????', '???', '???(?)', '????', '????', '????', '???', '????',
         '????']]

    data = pd.merge(gplb, current_price, left_index=True, right_index=True)
    # ??????????????????????????????
    data['?????'] = data['???'] * data['??'] * 10000 / data['????']
    print('%s:' % today)
    print()
    print('%d???' % data.shape[0])
    print('3???????%.1f' % round(data['?????'].median(), 1))
    print('3???????%.1f' % round(data['???'].median(), 1))
    data = data[data['?????'] < max]
    data = data[data['?????'] > min]
    data['?????'] = data['?????'].round(1)
    data['????'] = data['????'].round()
    data['???'] = data['???'].round(1)
    data['????'] = data['????'].round()
    data['????'] = data['????'].round()
    data['???'] = data['???'].round()
    data['????'] = data['????'].round()
    average_pe_file = os.path.join(current_folder, today + '-3???????%s?%s?????.xlsx' % (min, max))
    data.to_excel(average_pe_file)