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We can use the pandas. DataFrame. ewm() function to calculate the exponentially weighted moving average for a certain number of previous periods.
Finally, the following formula is used to calculate the current EMA: EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
Exponential Moving Averages (EMA) is a type of Moving Averages. It helps users to filter noise and produce a smooth curve. In Moving Averages 2 are very popular. Simple Moving Average just calculates the average value by performing a mean operation on given data but it changes from interval to interval.
I try to calculate ema with pandas but the result is not good. I try 2 techniques to calculate :
The first technique is the panda's function ewn:
window = 100
c = 2 / float(window + 1)
df['100ema'] = df['close'].ewm(com=c).mean()
But the last result of this function gives. 2695.4 but the real result is 2656.2
The second technique is
window = 100
c = 2 / float(window + 1)
df['100sma'] = df['close'].rolling(window).mean()
df['100ema'] = (c * df['close']) + ((1 - c) * df['100sma'])
The result is 2649.1 it's closer than first technique but is always not good
The sma function give the good result
** EDIT **
The response is
df['100ema'] = pd.Series.ewm(df['close'], span=window).mean()
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