Introduction to Python - Data Science, Quantitative Finance (2.0) by Li Lilan

Author:Li, Lilan [Li, Lilan]
Language: eng
Format: epub
Published: 2021-09-27T00:00:00+00:00

Now we have a 2D ndarray and we try to do some operations on each column and row:

>>> b.sum(axis=0) # sum of each column

array([12, 15, 18, 21])

>>>

>>> b.min(axis=1) # min of each row

array([0, 4, 8])

>>>

>>> b.cumsum(axis=1) # cumulative sum along each row

array([[ 0, 1, 3, 6],

[ 4, 9, 15, 22],

[ 8, 17, 27, 38]])

>>> b.prod(axis = 0) # matrix product for each column

array([ 0, 45, 120, 231])

Since the ndarray is a 2D, if we set axis = 2 , it will return error:

>>> b.prod(axis = 2)

AxisError: axis 2 is out of bounds for array of dimension 2

NumPy also provides familiar mathematical functions such as sin , cos , exp and sqrt . In NumPy, these are called 'universal functions'(ufunc).

>>> a = 2.4

>>> np.sqrt(a)

1.5491933384829668

>>> np.exp(a)

11.023176380641601

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