[amp_mcq option1=”arange” option2=”aspace” option3=”aline” option4=”all of the mentioned” correct=”option1″]<\/p>\n
The correct answer is A. arange.<\/p>\n
NumPy provides a function called where:<\/p>\n For example, the following code will create an array of numbers from 0 to 10, with a step size of 1:<\/p>\n “`<\/p>\n import numpy as np The “`<\/p>\n np.arange(0, 10, 0.5) The The other options, [amp_mcq option1=”arange” option2=”aspace” option3=”aline” option4=”all of the mentioned” correct=”option1″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[738],"tags":[],"class_list":["post-59288","post","type-post","status-publish","format-standard","hentry","category-data-science-miscellaneous","no-featured-image-padding"],"yoast_head":"\narange<\/code> which is analogous to range<\/code> in Python. It returns an array of numbers, instead of a list. The syntax for arange<\/code> is as follows:<\/p>\nnumpy.arange(start, stop, step)<\/code><\/p>\n\n
start<\/code> is the starting value of the sequence.<\/li>\nstop<\/code> is the ending value of the sequence.<\/li>\nstep<\/code> is the increment value of the sequence.<\/li>\n<\/ul>\n\n
\n
\n
\nnp.arange(0, 10, 1)
\narray([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
\n“`<\/p>\n<\/blockquote>\n<\/blockquote>\n<\/blockquote>\narange<\/code> function can also be used to create sequences of numbers with a step size that is not a positive integer. For example, the following code will create an array of numbers from 0 to 10, with a step size of 0.5:<\/p>\n\n
\n
\n
\narray([ 0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. , 5.5, 6. , 6.5, 7. , 7.5, 8. , 8.5, 9. , 9.5])
\n“`<\/p>\n<\/blockquote>\n<\/blockquote>\n<\/blockquote>\narange<\/code> function is a very versatile tool that can be used to create a variety of sequences of numbers. It is one of the most commonly used functions in NumPy.<\/p>\naspace<\/code> and aline<\/code>, are not functions in NumPy.<\/p>\n","protected":false},"excerpt":{"rendered":"