Pandas rolling standard deviation

Question

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.

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.

This in in pandas 0.19.1. Any help would be appreciated.

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)

Answer 1

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)