4 w = attribute_history(security = '000001.XSHE', count = 5, fields = ['high']) print(w) ten = w.T hightem = ten.values[0] avghigh = 0 for ele in hightem: avghigh = avghigh + ele avghigh = avghigh/5 print(avghigh)

stocks = get_index_stocks('000001.XSHG') q = query(valuation.code).filter(valuation.code.in_(stocks)).order_by(valuation.market_cap.desc()).limit(5) w = get_fundamentals(q) codes = w.values codelist = [] for ele in codes: codelist.append(ele[0]) print(codelist)

max_cap = query(valuation.code,valuation.market_cap).filter(valuation.market_cap>2000).\ order_by(valuation.market_cap.desc()).limit(5) w = get_fundamentals(max_cap) code = w['code'] codelist = [] for i in code: codelist.append(i) print(codelist)

``` w=attribute_history('000001.XSHE',5,fields='high') avghcost=mean(w.values) print(avghcost) stock=get_index_stocks('000001.XSHG') q=query(valuation.code,valuation.market_cap).filter(valuation.code.in_(stock))\ .order_by(valuation.market_cap.desc()).limit(5) gp=get_fundamentals(q) print(gp) print(gp.iloc[:,[0]]) ```

遇到一个问题，似乎jqdatasdk里并没有history和attribute_history这两个函数，只有history_engine和attribute_history_engine，但是用法和history和attribute_history完全不一样。是什么问题？ 我下的是最新1.7.3的包。 ``` w=jq.attribute_history('000001.XSHE',5,fields='high') Traceback (most recent call last): File "< ipython-input-4-a290c8807a45>", line 1, in < module> w=jq.attribute_history('000001.XSHE',5,fields='high') AttributeError: module 'jqdatasdk' has no attribute 'attribute_history' jq.attribute_history_engine( code ```

h=attribute_history('000001.XSHE',5, unit='5d',fields='high') average=sum(h.values)/len(h.values) print(average) stocks = get_index_stocks('000300.XSHG') q=query(valuation.code).filter(valuation.code.in_(stocks)).order_by(valuation.market_cap.desc()).limit(5) w=get_fundamentals(q) print(w)

学习了，谢谢！

@诸葛胖 请问您是怎么解决的，我也遇到同样的问题

@雨荷的爹 这两个函数，在本地的python里调jqdatasdk是没有的，在http版的研究环境才有(主页，策略研究，研究环境。notebook里 from jqdata import *

看不到内容呀？？？清除缓存也看不到。

获取任一股票最近5个交易日最高价的平均价。 ``` fid='000001.XSHE' hist_max5_v1= history(5,security_list=fid,field='high', df=False)[fid].mean() hist_max5_v2= attribute_history(fid,5,fields=['high'],df=False)['high'].mean() ``` 生成一个list，list中为上证指数成分股中流通市值最大的5个股票的股票代码。 ``` stock=get_index_stocks('000001.XSHG') q=query(valuation.code,valuation.market_cap)\ .filter(valuation.code.in_(stock))\ .order_by(valuation.circulating_market_cap.desc())\ .limit(5) gp=get_fundamentals(q) print(gp['code'].tolist()) ```

为什么会显示name 'history' is not defined？

@TerryZhang 流通市值应取valuation.circulating_market_cap

@Alan_Bi 谢谢，已经修正！

``` w=history(count=5, field='high', security_list=['000001.XSHE'],df=False)['000001.XSHE'].mean() print(w) df = get_index_weights('000001.XSHG') kk = df.sort_values(by='weight', ascending=False).head(5) print(list(kk.index)) ```

请问一下，为什么我照抄案例代码，仍然出现 global name ‘order_by’ is not defined,谢谢解答

学习

``` from jqdata import * def initialize(context): g.security = ['000001.XSHE', '000002.XSHE'] run_daily(period, time='every_bar') ''' 获取任一股票最近5个交易日最高价的平均价。 生成一个list，list中为上证指数成分股中流通市值最大的5个股票的股票代码。 ''' def period(context): #w = history(5, '1d', 'high', g.security) w = attribute_history(g.security[0], 5, '1d', ['high']) ma5 = w['high'].mean() print(ma5) qry = query( valuation.code, valuation.circulating_market_cap ).filter( ).order_by( valuation.circulating_market_cap.desc() ).limit(5) ret = get_fundamentals(qry) print(ret['code']) # df 对象 ''' for item in ret['code']: name = get_security_info(item) print("%s, %s" % (item, name.display_name)) ''' ```

``` # 导入函数库 from jqdata import * # 初始化函数，设定基准等等 def initialize(context): # 设定沪深300作为基准 set_benchmark('000300.XSHG') # 开启动态复权模式(真实价格) set_option('use_real_price', True) # 输出内容到日志 log.info() log.info('初始函数开始运行且全局只运行一次') # 过滤掉order系列API产生的比error级别低的log # log.set_level('order', 'error') ### 股票相关设定 ### # 股票类每笔交易时的手续费是：买入时佣金万分之三，卖出时佣金万分之三加千分之一印花税, 每笔交易佣金最低扣5块钱 set_order_cost(OrderCost(close_tax=0.001, open_commission=0.0003, close_commission=0.0003, min_commission=5), type='stock') # 用history函数查 w = history(5,unit='1d',field='high',security_list=['300498.XSHE']) #print(w) print(w.values.mean()) # 用attribute_history函数查 w1 = attribute_history('300498.XSHE',5,unit='1d',fields=['high','low']) #print(w1); print(w1['high'].mean()); # 获取 市值表.股票代码，资产负债表.未分配利润 q=query(valuation.code,valuation.circulating_market_cap # 从上证综指中查询 ).filter(#valuation.code=='000001' # 排序 按市值从大到小排 ).order_by(valuation.circulating_market_cap.desc() # 数量 上限10条数据 ).limit(5) ret = get_fundamentals(q) print(ret['code']) for code in ret['code']: print(get_security_info(code).display_name) ```