EdgeFrame entropy¶
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entropy
(self, data_column, weights_column=None)¶ Calculate the Shannon entropy of a column.
Parameters: data_column : unicode
The column whose entropy is to be calculated.
weights_column : unicode (default=None)
The column that provides weights (frequencies) for the entropy calculation. Must contain numerical data. Default is using uniform weights of 1 for all items.
Returns: : float64
Entropy.
The data column is weighted via the weights column. All data elements of weight <= 0 are excluded from the calculation, as are all data elements whose weight is NaN or infinite. If there are no data elements with a finite weight greater than 0, the entropy is zero.
Examples
Consider the following sample data set in frame ‘frame’ containing several numbers.
Given a frame of coin flips, half heads and half tails, the entropy is simply ln(2):
>>> frame.inspect() [#] data weight ================= [0] 0 1 [1] 1 2 [2] 2 4 [3] 4 8 >>> entropy = frame.entropy("data", "weight") [===Job Progress===]
>>> "%0.8f" % entropy '1.13691659'
If we have more choices and weights, the computation is not as simple. An on-line search for “Shannon Entropy” will provide more detail.
Given a frame of coin flips, half heads and half tails, the entropy is simply ln(2):
>>> frame.inspect() [#] data ========= [0] H [1] T [2] H [3] T [4] H [5] T [6] H [7] T [8] H [9] T >>> entropy = frame.entropy("data") [===Job Progress===] >>> "%0.8f" % entropy '0.69314718'