Stock Exchange for python programmers by Vieira Rodrigues Paulo Leonardo

Author:Vieira Rodrigues, Paulo Leonardo [Vieira Rodrigues, Paulo Leonardo]
Language: eng
Format: epub
Published: 2020-02-17T16:00:00+00:00

aapl_avg = aapl . Close . rolling(window = window) . mean() . dropna()

aapl_std = aapl . Close . rolling(window = window) . std() . dropna()

With the basic data calculated, we can build the final dataframe for Bollinger Bands values. This dataframe consist of values for the upper band, the lower band and the middle band.

aapl_bollinger = pd . DataFrame(index = aapl_avg . index)

aapl_bollinger[ 'mband' ] = aapl_avg

aapl_bollinger[ 'uband' ] = aapl_avg + aapl_std . apply( lambda x: (x * 2 ))

aapl_bollinger[ 'lband' ] = aapl_avg - aapl_std . apply( lambda x: (x * 2 ))

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