【发布时间】：2016-06-15 10:41:12
【问题描述】：
以下是我现在正在处理的数据 data image for easy understanding
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以下是代码
buying_list = data[data['Buying']==1] selling_list = data[data['Selling']==1] data['Cut_Off_Signal']=0 # Buying & Selling & Cut off signal process def test(data): data_index = list(data.index) buying_list_index = list(buying_list.index) for i in range(len(data_index)): for j in range(len(buying_list_index)): if buying_list_index[j]<=data_index[i]: #data.loc[(data['Cut_Off_Price'][j] < data['Close'][i]) & (data['Cut_Off_Price'][j] >= 1), 'Cut_Off_Signal'] = 1 data['Cut_Off_Signal'][i] = np.where((data['Cut_Off_Price'][j] < data['Close'][i]) & (data['Cut_Off_Price']>=1) , 1, 0) #data.loc[(data['Cut_Off_Price'][:i] < data['Close'][i]) & (data['Cut_Off_Price']!= 0), 'Cut_Off_Signal'] = 1 return data -
数据
Date Open High Low Close Volume Adj Close Buying Cut_Off_Price Selling Cut_Off_Signal 2015-10-13 256000 257000 255000 256000 161200 245982.6 0 0 0 0 2015-10-14 257000 260000 256000 257500 147700 247423.91 0 0 0 0 2015-10-15 257500 260500 256000 259000 139700 248865.21 0 0 0 0 2015-10-16 258000 260000 256500 258000 120400 247904.34 0 0 0 0 2015-10-19 258000 261500 257000 260500 89200 250306.52 0 0 0 0 2015-10-20 258500 260500 257500 259500 93400 249345.65 0 0 0 0 2015-10-21 260000 262000 259000 260000 93700 249826.08 0 0 0 0 2015-10-22 259500 260000 250000 251500 192200 241658.69 0 0 0 0 2015-10-23 252500 254500 249500 250000 147600 240217.39 0 0 0 0 2015-10-26 252000 255500 251500 254000 160900 244060.87 0 0 0 0 2015-10-27 254000 258500 251500 252000 149000 242139.13 1 228000 0 0 2015-10-28 253000 254500 248500 249000 128000 239256.52 0 0 0 0 2015-10-29 247500 250000 240000 242500 349000 233010.87 1 215050 0 0 2015-10-30 243500 245500 241000 241000 250200 231569.56 0 0 0 0 2015-11-02 243500 244000 235500 238500 541300 229167.39 0 0 0 0 2015-11-03 237000 237500 224500 230000 1054600 221000 0 0 0 0 2015-11-04 227500 237000 225500 231000 539400 221960.87 0 0 0 0 2015-11-05 233000 234500 230500 230500 189300 221480.43 0 0 0 0 2015-11-06 230500 231000 226000 227000 226700 218117.39 0 0 0 1 2015-11-09 227000 231000 226500 229000 173100 220039.13 0 0 0 0 2015-11-10 228500 229000 226000 227000 175000 218117.39 0 0 0 0 2015-11-11 225500 233000 222500 229000 342700 220039.13 0 0 0 0 2015-11-12 230000 234500 230000 232000 210700 222921.74 0 0 0 0 2015-11-13 231000 235000 230000 232000 202700 222921.74 0 0 0 0 2015-11-16 228000 234500 228000 233500 191300 224363.04 0 0 0 0 2015-11-17 233500 234500 230500 231500 215400 222441.3 0 0 0 0 2015-11-18 231000 232000 228000 230000 207000 221000 0 0 0 0 2015-11-19 231500 233500 229500 232000 141900 222921.74 0 0 0 0 2015-11-20 230000 233500 230000 233000 105600 223882.61 0 0 0 0 2015-11-23 232000 232500 231000 232500 98700 223402.17 0 0 0 0 2015-11-24 231000 233500 230500 233000 132100 223882.61 0 0 0 0 我想要的结果是
1) 每天比较收盘价和Cut_Off_Price
2) 如果收盘价低于 Cut_Off_Price，则将 Cut_Off_Signal 设为“1”
3) 并且从第二次出现在 Cut_Off_Price 下，然后忽略。 （我还没有编码，但我打算在“buying_list”中删除这个价格
以上代码没有产生任何 Cut_Off_Signal。能给个建议吗？
4 我尝试解决这个问题，但仍然失败。
def test(data)
for i in range(len(list(data.index))):
data.loc[(data[:i][data['Buying']==1)['Cut_Off_Price']<=data['Close'][i],'Cut_Off_Signal']=1
return data
面临的错误信息是 "IndexingError: Unalignalbe boolean Series key provided"
我真的不知道是什么问题。非常感谢您的建议。
【问题讨论】：
标签： pandas dataframe iteration trading