Comments (15)
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2016-10-12 13.58
2016-10-13 13.70
2016-10-14 13.70
2016-10-17 13.30
2016-10-18 13.54
2016-10-19 13.50
2016-10-20 13.46
2016-10-21 13.36
2016-10-24 13.37
2016-10-25 13.35
2016-10-26 13.44
2016-10-27 13.35
2016-10-28 13.50
2016-10-31 13.22
2016-11-01 13.14
2016-11-02 12.89
2016-11-03 12.87
2016-11-04 12.95
2016-11-07 13.14
2016-11-08 13.10
2016-11-09 13.10
2016-11-10 13.10
2016-11-11 13.10
2016-11-14 13.26
2016-11-15 13.31
2016-11-16 13.29
2016-11-17 13.27
2016-11-18 13.26
2016-11-21 13.15
2016-11-22 13.15
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注意2016-11-04 ~ 2016-11-11.....
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这只股票11月9号到11号是停牌的,我们用停牌之前的数据进行了补齐。
2016-11-22 12:55 GMT+08:00 好个飞飞 [email protected]:
注意2016-11-04 ~ 2016-11-11.....
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from rqalpha.
close = data_proxy.history("600325.XSHG", day, 30, "1d", "close")
volume = data_proxy.history("600325.XSHG", day, 30, "1d", "volume")
# 删除掉停牌的数据
close = close.reindex(volume[volume.values != 0].index)
这样处理下好像可以了.... 我只是想从外部使用rqalpha提供的日线数据
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新版本有什么计划吗。。?
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@haogefeifei 新版本已经更新,能麻烦再试一下看看是否还有这个问题吗?
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我看看
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3.x代码变化挺大的,花了点时间消化更新的代码,已经不用自己剔除停牌数据了,外部使用日线数据的代码改了下
import os
import datetime
from rqalpha.data.data_proxy import DataProxy
from rqalpha.data.base_data_source import BaseDataSource
data_bundle_path = os.path.expanduser("~/.rqalpha/bundle")
data_proxy = DataProxy(BaseDataSource(data_bundle_path))
day = datetime.date.today()
dates = data_proxy.history("600325.XSHG", 30, "1d", "close", day)
print(dates)
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但还是有点小问题的样子,比如执行如上代码取600325的日线,打印出来
2017-01-13 12.8699
这天的收盘价实际上应该是12.87
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@haogefeifei 这个价格也算不上是小问题,因为考虑到复权数据 可能往前的价格会很小,所以两位小数容易产生较大的偏差,所以价格增加至4位,然后12.8699属于浮点数精度截取后的结果,不影响使用。
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@haogefeifei 童鞋 我有给你发邮件 你有收到吗?
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@wh1100717 不好意思,才看到
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那这样的话数据就没什么问题了
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