Introduction to NumPy

Sample questions

Real questions from this chapter, as the app sets them. Tap Answer to see the answer and working.

Section A · multiple choice

1. 1.

   NumPy stands for:

   1. New Python
   2. Natural Python
   3. Number Python
   4. Numerical Python

   Answer

   (d) Numerical Python

2. 2.

   What does this print? import numpy as np a = np.array([72, 54, 74, 71]) print(a.ndim)

   1. 4
   2. 2
   3. 1
   4. 3

   Answer

   (c) 1

   a flat list gives a 1-D array

3. 3.

   What does this print? import numpy as np a = np.array([[87, 41, 27, 51, 33], [45, 46, 49, 96, 66]]) print(a.shape)

   1. (10,)
   2. (5, 2)
   3. (2,)
   4. (2, 5)

   Answer

   (d) (2, 5)

   2 rows, 5 columns

Section B · short answer

1. 4.

   Give two differences between a Python list and a NumPy array.

   Answer

   A list may hold items of different types; an array holds one type. Arrays support element-wise arithmetic and use less memory; lists do not.

2. 5.

   What does each print show? Give (a) the first line (b) the second. import numpy as np L = [5, 8, 6] A = np.array(L) print(L * 3) print(A * 3)

   Answer

   (a) [5, 8, 6, 5, 8, 6, 5, 8, 6]; (b) [15 24 18]

   a list repeats; an array multiplies each element

Section C · long answer

1. 6.

   Explain five attributes of a NumPy array with an example for a = np.array([[2, 4, 6], [1, 3, 5]]).

   Answer

   ndim = 2 (dimensions); shape = (2, 3) (rows, columns); size = 6 (elements); dtype = an integer type (int32 or int64, depending on the system); itemsize = bytes per element (4 for int32, 8 for int64).

Fresh sheets for your child

In the app, every Introduction to NumPy sheet is new: the app remembers the questions your child has already had and leaves them out. Print the sheet as a PDF, or use notebook mode and write the answers in a notebook.

Coming soon for Android and iPhone.

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