def data_standardize_money163(stock_code, index_code='000001.SH'):
# 1.读取万得的股票数据
stock_data = Functions.import_stock_data_money163(stock_code)
# 2.读取指数数据
index_data = Functions.import_index_data_wande(index_code=index_code)
# 3.个股数据除权处理, 默认后复权，直接替换OLHC列
stock_data = Functions.cal_adjust_price(stock_data)
# 3.合并个股数据和指数数据
stock_data = Functions.merge_with_index_data(stock_data, index_data)
# 4.添加涨跌停列
stock_data = Functions.limit_up_down(stock_data)
return stock_data
def data_standardize_xbx(code):
# 1.读取万得的股票数据
stock_data = Functions.import_stock_data_xbx(code)
# 2.读取指数数据
index_data = Functions.import_index_data_xbx()
# 3.个股数据除权处理, 默认后复权，直接替换OLHC列
stock_data = Functions.cal_adjust_price(stock_data)
# 3.合并个股数据和指数数据
stock_data = Functions.merge_with_index_data(stock_data, index_data)
# 4.添加涨跌停列
stock_data = Functions.limit_up_down(stock_data)
return stock_data
def data_standardize_money163(df,
index_code='000001.SH',
return_type=1,
start_date='19890101'):
# 1.读取万得的股票数据
# stock_data = Functions.import_stock_data_money163(stock_code)
stock_data = df.copy()
# 2.读取指数数据
index_data = Functions.import_index_data_wande(index_code=index_code)
# 3.个股数据除权处理, 默认后复权，直接替换OLHC列
stock_data = Functions.cal_adjust_price(stock_data,
return_type=return_type)
# 3.合并个股数据和指数数据
stock_data = Functions.merge_with_index_data(stock_data, index_data)
# 4.添加涨跌停列
stock_data = Functions.limit_up_down(stock_data)
# 取得指定时间范围的数据
stock_data = stock_data[stock_data['date'] >= pd.to_datetime(start_date)]
return stock_data
# print Functions.get_stock_code_list_in_one_dir_wande(file_path) # 4.2 从xbx的数据读取股票列表 file_path = 'D:/all_trading_data/data/input_data/stock_data' # print Functions.get_stock_code_list_in_one_dir_xbx(file_path) # exit() # ==== 5 个股数据和指数数据合并，日周期 stock_data = Functions.merge_with_index_data(stock_data_adjust, index_data) # print stock_data # exit() # ==== 6 周期转换 stock_data = Functions.transfer_to_period_data(stock_data, period_type='m') print stock_data exit() # print stock_data # 涨跌停信号添加 stock_data = Functions.limit_up_down(stock_data) # stock_data.ix[stock_data['open'] > stock_data['close'].shift(1) * 1.097, 'limit_up'] = 1 print stock_data exit() # 获得所有股票数据 # df = Functions.get_all_stock_data(load_type='orginal') # print df import random random = random.random() print random