moving average numpy
def moving_average(a, n=3) :
ret = np.cumsum(a, dtype=float)
ret[n:] = ret[n:] - ret[:-n]
return ret[n - 1:] / n
>>> a = np.arange(20)
>>> moving_average(a)
array([ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11.,
12., 13., 14., 15., 16., 17., 18.])
>>> moving_average(a, n=4)
array([ 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5,
10.5, 11.5, 12.5, 13.5, 14.5, 15.5, 16.5, 17.5])moving averages python
# option 1
df['data'].rolling(3).mean()
df['data'].shift(periods=1).rolling(3).mean()
# option 2: compute a 9-day simple moving average with pandas
BTC_USD['SMA_9'] = BTC_USD['Close'].rolling(window=9, min_periods=1).mean()Copyright © 2021 Codeinu
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