entropy

entropy(close, length=None, base=None, offset=None, **kwargs)

Entropy (ENTP)

Introduced by Claude Shannon in 1948, entropy measures the unpredictability of the data, or equivalently, of its average information. A die has higher entropy (p=1/6) versus a coin (p=1/2).

Sources:

https://en.wikipedia.org/wiki/Entropy_(information_theory)

Calculation:

Default Inputs:

length=10, base=2

P = close / SUM(close, length) E = SUM(-P * npLog(P) / npLog(base), length)

Args:

close (pd.Series): Series of ‘close’s length (int): It’s period. Default: 10 base (float): Logarithmic Base. Default: 2 offset (int): How many periods to offset the result. Default: 0

Kwargs:

fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method

Returns:

pd.Series: New feature generated.