NumPy: Array of evaluations of function on array-CodePudding

Consider the following code.

import numpy as np
list = ["blabla.com","blabla.org","blibli.com"]
array1 = np.array(list)
array2 = array == "blabla.com"
print(array2)
# array2 is the one-element array containing only "blabla.com",
# but I would have expected it to contain the boolean False
array3 = array.endswith(".com")
print(array3)
# error

The error I get is

AttributeError: 'numpy.ndarray' object has no attribute 'endswith'

and I obviously agree.

What I don't understand, is the following: when I write

array == "blabla.com"

how does NumPy know that I want the array consisting of the boolean values of the according test on all elements of the array, and not the result of the test <<is array equal to "blabla.com"?>>?

And why does NumPy believe that when I write

array.endswith("blabla.com")

I want to use the (unexistent) attribute .endswith of numpy.ndarray?

I mean, it looks that in one case, NumPy is clever enough to understand an abuse of notation, and in the other case, it just reads what is explicitely written?

CodePudding user response：

numpy normally does an equality test, element by element, when given '=='. That's true to string dtype as well as the more common numeric dtypes.

In [14]: alist = ["blabla.com","blabla.org","blibli.com"]
    ...: array1 = np.array(alist)
    ...: array2 = array1 == "blabla.com"
In [15]: array1
Out[15]: array(['blabla.com', 'blabla.org', 'blibli.com'], dtype='<U10')
In [16]: array2
Out[16]: array([ True, False, False])

But .endswith is a method, not an operator. Methods have to be defined to the class. That's true for string, but not arrays. Hence the AttributeError.

In [18]: array1[0]
Out[18]: 'blabla.com'

In [19]: type(_)
Out[19]: numpy.str_

In [20]: array1[0].endswith('com')
Out[20]: True

There is a group of functions in np.char that do apply string methods to elements of a string dtype array:

In [21]: np.char.endswith(array1, 'org')
Out[21]: array([False,  True, False])

This doesn't involve special numpy coding. [astr.endswith('org') for astr in array1] does just as well.