NumPy version of “Exponential weighted moving average”, equivalent to pandas.ewm().mean()

Question

How do I get the exponential weighted moving average in NumPy just like the following in pandas?

import pandas as pd
import pandas_datareader as pdr
from dat         


        

Answer 1

Here is another solution O came up with in the meantime. It is about four times faster than the pandas solution.

def numpy_ewma(data, window):
    returnArray = np.empty((data.shape[0]))
    returnArray.fill(np.nan)
    e = data[0]
    alpha = 2 / float(window + 1)
    for s in range(data.shape[0]):
        e =  ((data[s]-e) *alpha ) + e
        returnArray[s] = e
    return returnArray

I used this formula as a starting point. I am sure that this can be improved even more, but it is at least a starting point.