Season 5 #Spaic Python Weekly Quiz

How to create an array using Numpy for this list (np.nan as the first element, and the next element are integers from 2 to 5)

• array(np.nan,2,3,4,5)

• array([np.nan,2,3,4,5])

• np.array([np.nan,2,3,4,5])

• All the above

To create c copy of an array a = np.array([0, 1])

in Numpy

• c = a

• c = a.copy()

• All the above

How to create an array using Numpy for a list from 0 to 4

• arr=np.array([0,1,2,3,4])

• arr = np.arange(5)

• arr = np.arange(0, 5, 1)

• arr=np.array(0,1,2,3,4)

How to specifie the number of element to return in an array using NumPy

• np.linspace(a, b, num=c)

• np.array(a, b, num=c)

To transpose the value of an array in Numpy (arr = np.arange(8)) we can use (transposed = np.transpose(arr))

• True

• False

How to create an array of 5 elements, all of which are 0/1 in Numpy

• np.zeros(5) / np.ones(5)

• np.array([0,0,0,0,0] )/ np.array([1,1,1,1,1])

• np.arange(0)/np.arange(1)

What does the arange function do in Numpy?

• Returns a 1-D array of numbers based on a a given range and interval

• Returns a random array

• Squares each value of an array

• Returns the largest element of an array

What happens if we try to use np.save on a file without a .npy extension in Numpy?

• The function raises an exception

• The data is saved to the file without the .npy extension

• The function automatically adds the .npy extension

• The function does nothing

What is the difference between np.sum and np.cumsum in Numpy?

• The former is computationally more expensive than the latter

• Both perform the same thing

• The former is significantly slower than the latter

• The former produces the overall sum while the latter calculates cumulative sums

Consider the 2-D array, arr. What is the output of np.sum(arr, axis=1)?

• A 1-D array containing the column sums of arr

• A 1-D array containing the row sums of arr

• A 2-D array containing the cumulative column sums of arr

• A 1-D array containing the cumulative row sums of arr