pandas 熊猫滚动标准差
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Pandas rolling standard deviation
提问by Sam
Is anyone else having trouble with the new rolling.std()in pandas? The deprecated method was rolling_std(). The new method runs fine but produces a constant number that does not roll with the time series.
有没有其他人对 Pandas 的新功能有问题rolling.std()？不推荐使用的方法是rolling_std(). 新方法运行良好，但会产生一个不随时间序列滚动的常数。
Sample code is below. If you trade stocks, you may recognize the formula for Bollinger bands. The output I get from rolling.std()tracks the stock day by day and is obviously not rolling.
示例代码如下。如果您交易股票，您可能会认识布林带的公式。我得到的输出rolling.std()每天都在跟踪库存，显然没有滚动。
This in in pandas 0.19.1. Any help would be appreciated.
这在Pandas 0.19.1 中。任何帮助，将不胜感激。
import datetime
import pandas as pd
import pandas_datareader.data as web
start = datetime.datetime(2012,1,1)
end = datetime.datetime(2012,12,31)
g = web.DataReader(['AAPL'], 'yahoo', start, end)
stocks = g['Close']
stocks['Date'] = pd.to_datetime(stocks.index)
stocks['AAPL_LO'] = stocks['AAPL'] - stocks['AAPL'].rolling(20).std() * 2
stocks['AAPL_HI'] = stocks['AAPL'] + stocks['AAPL'].rolling(20).std() * 2
stocks.dropna(axis=0, how='any', inplace=True)
回答by Abhishek Kulkarni
import pandas as pd
from pandas_datareader import data as pdr
import numpy as np
import datetime
end = datetime.date.today()
begin=end-pd.DateOffset(365*10)
st=begin.strftime('%Y-%m-%d')
ed=end.strftime('%Y-%m-%d')
data = pdr.get_data_yahoo("AAPL",st,ed)
def bollinger_strat(data, window, no_of_std):
rolling_mean = data['Close'].rolling(window).mean()
rolling_std = data['Close'].rolling(window).std()
df['Bollinger High'] = rolling_mean + (rolling_std * no_of_std)
df['Bollinger Low'] = rolling_mean - (rolling_std * no_of_std)
bollinger_strat(data,20,2)
