Lecture 1 - Numpy Operations 1

Question 1

How to convert a list to np array?

Answer 1

np.array(list)
this can also be used to copy another np array

Question 2

Are np ndarrays mutable?

Answer 2

Yes, be careful with this and copy when necessary using np.array

Question 3

Does np support ragged arrays?

Answer 3

No

Question 4

How to create a blank np array?

Answer 4

• np.empty
• np.zeroes
• np.ones
• np.full

Question 5

How to generate random numbers in np ndarrays?

Answer 5

np.random.randint(a,b,shape)
np.random.uniform(a,b,shape)
np.random.normal(mean,std,shape)

Question 6

Generate sequence like np ndarrays.

Answer 6

np.arange(a,b,step) - exclusive
np.linspace(a,b,step) - inclusive

Question 7

How to save to file using numpy?

Answer 7

np.savetcxt(arr,name)

Question 8

slicing format

Answer 8

start : end: step

Question 9

Rules for indexing

Answer 9

no colon - take specific
one colon - take range
two colons - range with step

Question 10

Difference between slicing and indexing?

Answer 10

slicing doesn’t change the rank of the array, it picks a subset
indexing typically does reduce a rank, it selects a rectangular region with ranks less

Question 11

x[::-1]

Answer 11

Reversing

Question 12

x[:,0]

Answer 12

All rows, first column

Question 13

x[0,:]

Answer 13

First row all columns