Numpy (Wk 3 UCSD / DataCamp)

Question 1

How does a (numpy) array differ from a list?

Answer 1

You can perform mathematical operations element wise on the array (vector arithmetic)

Question 2

How do you create a numpy array?

Answer 2

np_array = np.array(list) OR np.array([x, y, z])

Question 3

What happens if you divide 2 np arrays (of the same size)

Answer 3

the output is the an array of the same size, w/ each element the respective quotients

Question 4

What happens if you create a numpy array of multiple types?

Answer 4

it will convert all to one type (aka type coercion)

Question 5

what’s the output of np_array > X

Answer 5

Array of Booleans element wise [True, False, etc]

Question 6

What’s the output of np_array[ np_array > X]

Answer 6

Returns element wise values that meet the condition (product w/ Boolean result)

Question 7

When do you use parentheses with an array?

Answer 7

When you’re instantiating only (eg, not when you’re setting or sub-setting

Question 8

How do you create a multi-dimensional np array?

Answer 8

np_array = np.array(list1, list2) OR = np.array( [ [1,2,3], [4,5,6] ] )

Question 9

How do you get the number of rows and columns of an array?

Answer 9

np_array.shape (attribute of the array)

Question 10

How do return 2nd element from 3rd row of a 2d np array?

Answer 10

np_array[2,1] OR np_array[2][1]

Question 11

How do you sub-set multi-dimensional np arrays?

Answer 11

np_array[ x:y, k:j ]

Question 12

using subsetting, return the entire second row of a np array

Answer 12

np_array[ 1, : ]

Question 13

How does arithmetic work with multi-dim arrays?

Answer 13

can do all operations. Array X Array, or Array X Vector(s)

Question 14

Get the mean of the first column of data in a 2D np array

Answer 14

np.mean(np_array[ : , 0]

Question 15

summary stats functions np arrays

Answer 15

np.mean(), np.median(), np.std()

Question 16

check the corrleation between column 1 and column 2 in a 2D array

Answer 16

np.corrcoef( np_array[ : , 0] , np_array[ : , 1] )

Question 17

How to generate an array with normally distributed random numbers

Answer 17

np.random.normal(mean, std, num of values to generate)

Question 18

how to merge two 1D arrays into a single 2D array

Answer 18

np_2d = np.column_stack(( np1, np2))

Question 19

create arrays full of 0s, 1s, diagonal 1

Answer 19

np.zeros, np.ones, np,eye

Question 20

create 2d array with all value 9

Answer 20

np_array = np.full((2,2), 9.0)

Question 21

create a 2d array with random floats between 0 and 1

Answer 21

np_array = np.random.random((2,2))

Question 22

What does a sub-set of an array like a_slice = np_array[1:3 , 1:3 ]

Answer 22

a 2x2 array that you can reference with the new indices (eg 0,0; 0,1; etc), but points to the same data as the original array

Question 23

how do you make a new data structure using a slice

Answer 23

new_slice = np.array(np_array[1:2, 2:3]

Question 24

explicitly declare the data type in an array

Answer 24

x = np.array(list1, dtype=float64)&raquo_space; forces to the dtype, can use various types

Question 25

get the mean by row, or by col, of an array

Answer 25

arr.mean(axis=1)&raquo_space; row; arr.mean(axis=2)&raquo_space; column

Question 26

print just the unique values of an array

Answer 26

print(np.unique(np_array))

Question 27

what happens if you add a 1,3 array to a 3,3 array

Answer 27

broadcasting - eg, python adds the 1,3 row to each row (will works same column wise)