Trigonometric functions (sin, cos, tan) in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the numpy function np.sin() compute?

The function np.sin() computes the sine of each element in the input array, where the input is in radians.

beginner

How is the cosine function represented in numpy?

The cosine function is represented by np.cos(), which calculates the cosine of each input value in radians.

beginner

What is the output of np.tan(np.pi / 4)?

The output is 1.0 because the tangent of 45 degrees (π/4 radians) is 1.

intermediate

Why do numpy trigonometric functions expect input in radians, not degrees?

Because radians are the standard unit for angles in mathematical functions and calculations, numpy functions like np.sin(), np.cos(), and np.tan() expect input in radians for accuracy and consistency.

beginner

How can you convert degrees to radians before using numpy trigonometric functions?

You can convert degrees to radians using np.radians(degrees), which converts degree values to radians for use in np.sin(), np.cos(), and np.tan().

What does np.cos(np.pi) return?

A 1.0

B 0.0

C Undefined

D -1.0

The cosine of π radians (180 degrees) is -1.0.

Which numpy function calculates the tangent of an angle?

A np.sin()

B np.arctan()

C np.tan()

D np.cos()

np.tan() calculates the tangent of each element in the input array.

If you have an angle in degrees, which function helps convert it to radians?

A np.degrees()

B np.radians()

C np.sin()

D np.tan()

np.radians() converts degrees to radians, which is needed for trigonometric functions.

What is the value of np.sin(0)?

A 0

B 1

C -1

D Undefined

The sine of 0 radians is 0.

Which unit should angles be in when using np.sin(), np.cos(), or np.tan()?

A Radians

B Degrees

C Gradians

D Turns

Numpy trigonometric functions expect angles in radians.

Explain how to calculate the sine, cosine, and tangent of an angle using numpy, including any necessary unit conversions.

Think about the input unit and the numpy functions for each trig function.

Describe a real-life example where you might use numpy's trigonometric functions in data science.

Consider situations involving cycles or angles.