Complex number type in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a complex number in numpy?

A complex number in numpy has a real part and an imaginary part. It is represented as a + bj, where a is the real part and b is the imaginary part.

beginner

How do you create a complex number array in numpy?

You can create a complex number array using numpy.array with complex values, for example: np.array([1+2j, 3+4j]).

intermediate

What numpy data types represent complex numbers?

Numpy uses complex64 and complex128 to represent complex numbers. complex64 uses 32 bits for real and 32 bits for imaginary parts, while complex128 uses 64 bits for real and 64 bits for imaginary parts.

beginner

How can you access the real and imaginary parts of a numpy complex array?

Use the .real attribute to get the real parts and .imag attribute to get the imaginary parts of a numpy complex array.

intermediate

Why are complex numbers useful in data science?

Complex numbers help in fields like signal processing, quantum computing, and electrical engineering where data has both magnitude and phase information.

Which numpy data type is used for complex numbers with 64-bit real and imaginary parts?

A complex64

B complex128

C float64

D int64

complex128 uses 64 bits for both real and imaginary parts.

How do you get the imaginary part of a numpy complex array named z?

A z.imag

B z.real

C imag(z)

D z.imaginary

The correct attribute to access the imaginary part is .imag.

What does the complex number 3 + 4j represent?

A Magnitude 3, phase 4

B Real part 4, imaginary part 3

C Imaginary part 3, real part 4

D Real part 3, imaginary part 4

In a + bj, a is real and b is imaginary.

Which numpy function can create an array of complex numbers?

A np.array

B np.complex

C np.complex_array

D np.complex64

You create complex arrays using np.array with complex values.

Why might data scientists use complex numbers?

A To store only real numbers

B To speed up sorting algorithms

C To represent data with magnitude and phase

D To reduce memory usage

Complex numbers represent data with both magnitude and phase, useful in many scientific fields.

Explain how to create and access parts of a complex number array in numpy.

Think about how you write complex numbers and how numpy stores them.

Describe the difference between complex64 and complex128 in numpy.

Consider how many bits are used for each part.