Basic Numpy Concepts

What is Numpy in Python?

• Numpy is a data visualization tool in Python.

• Numpy is a game development framework in Python.

• Numpy is a web framework for building APIs in Python.

• Numpy is a library in Python used for numerical computing, offering support for large, multi-dimensional arrays and matrices.

How do you create a Numpy array?

• Call numpy.new_array() for Numpy array creation.

• Invoke numpy.make_array() to build a Numpy array.

• Use numpy.create() to generate a Numpy array.

• Use numpy.array() to create a Numpy array.

What function is used to find the shape of an array?

• dimensions

• length

• size

• shape

How can you access elements in a Numpy array?

• Use indexing and slicing to access elements in a Numpy array.

• Elements can only be accessed through functions.

• Access elements by their data type only.

• Use loops to access elements in a Numpy array.

What is the difference between a list and a Numpy array?

• A list can contain mixed data types; a Numpy array requires all elements to be of the same type.

• A list is a fixed size, whereas a Numpy array can grow dynamically.

• A Numpy array can only contain integers, while a list can contain any type.

• A list is faster for numerical operations than a Numpy array.

What is the output type of np.array([1, 2, 3])?

• a) List

• b) DataFrame

• c) ndarray

• d) Series.

What does NumPy stand for?

• a) Numerical Python

• b) Numbers in Python

• c) Number Processing

• d) None of the above

How do you import the NumPy library in Python?

• a) import numpy

• b) import numpy as np

• c) import NumPy

• d) include numpy

Which function returns evenly spaced values within a given interval?

• a) np.linspace()

• b) np.arange()

• c) np.spacing()

• d) np.range()

What does the dtype attribute of a NumPy array represent?

• a) Default type

• b) Data type of elements

• c) Dimension type

• d) Description type