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I find this very weird. Can someone tell me whats going on here?
>>>a = [1,0,1]
>>>np.mean(a)
0.66666666666666663
>>>2.0/3
0.6666666666666666
What's up with the 3 in the end of the output of np.mean(a)? Why isn't it a 6 like the line below it or a 7(when rounding off)?
695
np. mean always computes an arithmetic mean, and has some additional options for input and output (e.g. what datatypes to use, where to place the result). np. average can compute a weighted average if the weights parameter is supplied.
You can use np. floor() , np. trunc() , np. ceil() , etc. to round up and down the elements of a NumPy array ndarray .
You need to use Numpy function mean() with "axis=0" to compute average by column. To compute average by row, you need to use "axis=1". array([ 7., 8., 9., 10.])
This is just a case of a different string representation of two different types:
In [17]: a = [1, 0, 1]
In [18]: mean(a)
Out[18]: 0.66666666666666663
In [19]: type(mean(a))
Out[19]: numpy.float64
In [20]: 2.0 / 3
Out[20]: 0.6666666666666666
In [21]: type(2.0 / 3)
Out[21]: float
In [22]: mean(a).item()
Out[22]: 0.6666666666666666
They compare equal:
In [24]: mean(a) == 2.0 / 3
Out[24]: True
In [25]: mean(a).item() == 2.0 / 3
Out[25]: True
Now might be the time to read about numpy scalars and numpy dtypes.
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