NumPy array foundation review in SciPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a NumPy array?

A NumPy array is a grid of values, all of the same type, indexed by a tuple of nonnegative integers. It is like a list but faster and can handle large data efficiently.

beginner

How do you create a NumPy array from a Python list?

Use numpy.array() function. For example, np.array([1, 2, 3]) creates a 1D array with elements 1, 2, and 3.

beginner

What is the difference between a Python list and a NumPy array?

Python lists can hold different data types and are slower. NumPy arrays hold elements of the same type and are optimized for numerical operations, making them faster and more memory efficient.

beginner

What does the shape attribute of a NumPy array tell you?

The shape attribute shows the size of the array in each dimension. For example, a shape of (3, 4) means 3 rows and 4 columns.

beginner

How can you access the element in the second row and third column of a 2D NumPy array?

Use zero-based indexing: array[1, 2] accesses the element in the second row and third column.

Which function creates a NumPy array from a list?

A np.create()

B np.list()

C np.array()

D np.make_array()

The correct function to create a NumPy array from a list is np.array().

What is the data type requirement for elements in a NumPy array?

A Elements can be of any type

B Only strings are allowed

C Only integers are allowed

D All elements must be of the same type

NumPy arrays require all elements to be of the same data type for efficient computation.

If a NumPy array has shape (4, 5), how many elements does it contain?

A 20

B 9

C 10

D 5

The total elements are rows × columns = 4 × 5 = 20.

How do you access the first element of a 1D NumPy array named arr?

A arr[0]

B arr[1]

C arr.first()

D arr.get(0)

NumPy arrays use zero-based indexing, so the first element is accessed with arr[0].

Which of these is NOT a benefit of using NumPy arrays over Python lists?

A Faster numerical operations

B Supports mixed data types

C Uses less memory

D Supports multi-dimensional arrays

NumPy arrays do NOT support mixed data types; all elements must be the same type.

Explain what a NumPy array is and why it is useful compared to a Python list.

Think about how computers handle numbers and speed.

Describe how to create a 2D NumPy array and how to find its shape.

Use nested lists and check the size with a property.