NumPy

Question 1

What is NumPy and why is it useful?

Answer 1

• A powerful Python library for scientific computing
• It provides a multidimensional array object, and allows fast operations on arrays including mathematical, logical, array manipulation, sorting and selecting
• Mathematical operations are up to 50x faster on ndarray objects and require fewer lines of code than Python lists.
• It contains built-in functions for working with arrays and maths, such as linear algebra and array transformations.

Question 2

What are Numpy arrays?

Answer 2

Numpy arrays are the central data structure of the NumPy library. They are a grid of values which may have one or more dimensions:

Vectors: one dimension arrays
Matrices: two-dimensional arrays (2D) represent matrices.
Tensors: higher dimensional arrays

Question 3

NumPy array creation functions

Answer 3

range, array, copy, empty, eye, linespace, ones, zeros

Question 4

NumPy conversions

Answer 4

astype, mat

Question 5

NumPy manipulations

Answer 5

array_split, column_stack, concatenate, hsplit, hstack, reshape, vsplit, vstack

Question 6

NumPy questions

Answer 6

all, any, nonzero, where

Question 7

NumPy ordering

Answer 7

argmax, argmin, max, min, sort

Question 8

NumPy Operators

Answer 8

ndarray.fill, prod, sum

Question 9

NumPy Statistics

Answer 9

mean, std, var

Question 10

Get help on Numpy

Answer 10

np.lookfor(‘search’)

Question 11

Array shape, dimensions, and size in bytes

Answer 11

arr.shape
arr.ndim
arr.itemsize

Question 12

2.Create a 5X2 integer array from a range between 100 to 200, such that the difference between each element is 10

Answer 12

arr = np.arange(100,200,10).reshape((5, 2))

Question 13

sample_array = np.array([[11 ,22, 33], [44, 55, 66], [77, 88, 99]])

Return array of items by taking the third column from all rows

Answer 13

sample_array[:,2]

Question 14

4.Create a result array by adding the following two NumPy arrays.
# Next, modify the result array by calculating the square of each element.

GIVEN

arrayOne = np.array([[5, 6, 9], [21 ,18, 27]])
arrayTwo = np.array([[15 ,33, 24], [4 ,7, 1]])

Answer 14

arrayThree = arrayOne + arrayTwo
arraySquared = arrayThree ** 2

Question 15

Split an array into four equal-sized sub-arrays

arr = np.arange(24).reshape(8,3)

Answer 15

new_arr = np.array_split(arr,4)

Question 16

Numpy Where
# b will be all elements of a whenever the condition holds true (i.e only positive elements)
# Otherwise, set it as 0

Answer 16

b = np.where(a > 0, a, 0)

Question 17

Sort Numpy Array
- Ascending order
- Descending order

Answer 17

arr2 = np.sort(arr)
arr3 = np.sort(arr)[::-1]

Question 18

Add or delete values from an array

Answer 18

np.append()
np.delete()

Question 19

What is broadcasting in Numpy?

Answer 19

Broadcasting is the name given to the method that NumPy uses to allow array arithmetic between arrays with a different shape or size.