def get_sharp_ratio_for_each_year(net_value_list):
sharpRatioList = []
startYear = DateUtil.datetime2_year_str(net_value_list.index[0])
endYear = DateUtil.datetime2_year_str(net_value_list.index[-1])
for year in range(int(startYear), int(endYear) + 1, 1):
yearStr = str(year)
# print("yearStr:" + str(yearStr))
# 把总列表按年切分成子列表
subNetValueList = net_value_list.ix[yearStr]
ss = subNetValueList['changePCT']
sharpRatio = get_sharp_ratio_common_day(ss)
sharpRatioDict = {'year': yearStr, 'sharpRatio': sharpRatio}
sharpRatioList.append(sharpRatioDict)
# 非时间序列DF
df = pd.DataFrame(sharpRatioList)
return df
def main(net_value_list):
#startYear = DateUtil.datetime2YearStr(netValueList.index[0])
#endYear = DateUtil.datetime2YearStr(netValueList.index[-1]) #len(netValueList) - 1
net_value_list['year'] = DateUtil.datetime2_year_str(net_value_list.index)
#print(netValueList)
#['netValue']
stockYearList = net_value_list.groupby(net_value_list['year']).apply(
get_year_profit, 'netValue')
# 非时间序列DF
df = pd.DataFrame(stockYearList, columns=['profit'])
return df
def get_max_drop_for_each_year(net_value_list):
#netValueList2 = pd.DataFrame(data=netValueList,columns=['netValue','hightestNetValue'])
#netValueList2['hightestNetValue'] = 0;
stock_trade_result_max_drop_list = []
start_year = DateUtil.datetime2_year_str(net_value_list.index[0])
end_year = DateUtil.datetime2_year_str(net_value_list.index[-1])
for year in range(int(start_year), int(end_year) + 1, 1):
year_str = str(year)
#print("yearStr:" + str(yearStr))
#把总列表按年切分成子列表
sub_net_value_list = net_value_list.ix[year_str]
max_drop_dict = get_max_drop(sub_net_value_list)
max_drop_dict.setdefault("year", year_str)
#print(maxDropDict)
stock_trade_result_max_drop_list.append(max_drop_dict)
#非时间序列DF
df = pd.DataFrame(stock_trade_result_max_drop_list)
return df