Numpy

Question 1

How do you create a numpy array?

Answer 1

import numpy as np

np.array([1,2,3])

Question 2

How do you create an array with a range of elements?

Answer 2

np.arrange(4)

Question 3

How do you create an array with evenly spaced elements

Answer 3

np.arrange(2,9,2)

Question 4

How do you sort an array?

Answer 4

np.sort(array)

Question 5

How do you change the shape of an array?

Answer 5

array.reshape(rows,cols)

Question 6

Can you select a subset of numpy arrays?

Answer 6

Yes; create a boolean and then insert it in the slicer

criteria = y < 3
y[criteria]

Question 7

How do you create a matrix of zeros?

Answer 7

np.zeros((5,5))

Question 8

How do you create a matrix of ones?

Answer 8

np.ones((2,10))

Question 9

Does np.zeros(()) create integers or floats?

Answer 9

Floats

Question 10

How do you create random numbers?J

Answer 10

np.random.randint(0,100)

Question 11

How do you create random numbers in a matrix?

Answer 11

np.random.randint(0,100,(5,5))

Question 12

How do you get numbers that are spaced evenly?

Answer 12

np.linspace(0,10,101)

Question 13

What does np.linspace(0,10,101) mean?

Answer 13

101 numbers between 0 to 10 that are equally spaced

Question 14

How do you get consistent random numbers?

Answer 14

np.random.seed(x)

Question 15

Does seed persistent beyond the next row?

Answer 15

No

Question 16

How do you get the maximum value in an array?

Answer 16

arrayname.max()

Question 17

How do you find out where in an array the max value is?

Answer 17

arrayname.argmax()

Question 18

How do you change the shape of an array?

Answer 18

arrayname.reshape(2,5)

Question 19

How do you slice on rows / columns?

Answer 19

arrayname[5,2]

Question 20

How does numpy format arrays?

Answer 20

makes each number the same size as the biggest number by adding spaces

Question 21

What is faster, numpy or lists?

Answer 21

Numpy

Question 22

How do you access the dimensions of an array?

Answer 22

name. ndim

Question 23

How do you access the number of rows and columns in an array

Answer 23

name.shape

Question 24

What does shape give you for a 1 dimensional array?

Answer 24

Gives the number of elements

Question 25

What are .dtype and .shape

Answer 25

Attributes - has to be on an objective (i.e. they are not functions)

Question 26

How do you get the number of elements in a 2 dimensional array?

Answer 26

name.size

Question 27

How do you remove dimensionality from an array?

Answer 27

name.flat iterate over

Question 28

How do you create an array?

Answer 28

np.array([]) - must be a list of lists if it is multidimensional

Question 29

Do you feed 5,2 or (5,2) to np.ones()?

Answer 29

A tuple i.e. np.ones((5,2))

Question 30

Can you get integers instead of floats in np.ones()?

Answer 30

Yes np.ones((5,2), dtype = int)

Question 31

How do you get a array of numbers of any number?

Answer 31

np.full((3,5),13)

Question 32

How do you create an arrange of items 0 to 4?

Answer 32

np.arange(5)

Question 33

How many elements does lin space take and what are they?

Answer 33

start, end and num = | np.linspace(0,1,num = 5)

Question 34

How do you specify the shape of an array using a range?

Answer 34

np.arange(0,21).reshape(4,5)

Question 35

Is reshape in place?

Answer 35

No

Question 36

If you do operators on a numpy array - is it in place?

Answer 36

No

Question 37

Do you need to iterate over items to do things to an array?

Answer 37

No anarray * 2 works

Question 38

Can you do augmented assignments in numpy?

Answer 38

Yes numbers += 10 adds 10 to every element

Question 39

Can you multiply arrays together?

Answer 39

Yes

Question 40

What happens if you multiply arrays together that are not the same shape?

Answer 40

Error if you use *. You can use * or np.multipy(array1, array2) if the arrays are different sizes but only if one is the same length as a row.

Question 41

Can you do comparisons on numpy arrays?

Answer 41

Yes numbers >= 13 will produce an array of booleans

Question 42

How do you see what methods are available for the array type?

Answer 42

arrayname. then press tab

Question 43

What are some of the methods available for arrays?

Answer 43

sum() min() max() mean()

Question 44

How do you calculate the mean of a column in an array?

Answer 44

arrayname.mean(axis = 0)

Question 45

Axis = 0 is column or row?

Answer 45

column

Question 46

How do you access universal functions eg. sqrt?

Answer 46

Using the module name so if you import numpy as np then np.sqrt()

Question 47

what is the main difference between indexing lists and numpy in multidimensions?

Answer 47

list[1][2] | array [1,2]

Question 48

How do you select not continuous rows / columns in an array?

Answer 48

myarray[[1,3]]

Question 49

What is a shallow copy?

Answer 49

Where you create a new object in memory but it points to the original object where the data is actually sorted?

Question 50

How do you create a shallow copy of an array?

Answer 50

myarray.view()

Question 51

If you change the original object, does the new object change?

Answer 51

Yes as it's pointing to the original still

Question 52

If you take a slice of an array - is it a view or is it a completely new object?

Answer 52

It is a view, so if you change the original object it will change

Question 53

How do you create a deep copy (i.e. new object) of an array?

Answer 53

x = myarray.copy()

Question 54

Reshape vs resize, which is a view and which modifies the original array?

Answer 54

Reshape is a view

Question 55

Is resize a view?

Answer 55

No

Question 56

How many dimensions does this array have? np.array[[1,2,3,4]]

Answer 56

2 - double square brackets

Question 57

How do you reduce dimensions of an array?

Answer 57

myarray.flatten()

Question 58

Flatten or ravel, which is a view?

Answer 58

Ravel is a view

Question 59

Can you filter an array?

Answer 59

Yes just like a dataframe arr[array % 2 != 0]

Question 60

How can you determine if an array contains an element?

Answer 60

np.any(arrayname)

Question 61

How do you reverse an array?

Answer 61

np.flip(arrayname, axis = )

Question 62

How do you find elements that are non zero?

Answer 62

np.nonzero(arrayname)

Question 63

How do you create an identity matrix?

Answer 63

np.identity(3)

Question 64

How do you create a specific set of values on a diagonal?

Answer 64

np.diag([1,2,3],k = 0) k means the diagonal - 0 is the main - 1 is below

Question 65

How do you get the coordinates from a flat index?

Answer 65

np.unravel_index(indexyouwant, [dimensions of array])

Question 66

How do you do matrix multiplication

Answer 66

np.dot()

Question 67

np.nonzero(arrayname) or arrayname.nonzero()

Answer 67

np.nonzero(arrayname)

Question 68

What does np.where() do?

Answer 68

Evaluates if a condition is true, and if it is does something (or not)

Question 69

What arguments does np.where() take?

Answer 69

np.where(x <4 , x, 5)

Question 70

What is the output of np.where()

Answer 70

Typically an array of number unless you tell it booleaons

Question 71

How can you test AND conditions in numpy?

Answer 71

np.logical_and(test1,test2)

Question 72

np.where() or arrayname.where()

Answer 72

np.where()