np.choose() for conditional selection in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does np.choose() do in simple terms?

np.choose() picks values from several options based on an index array. Think of it like choosing from different boxes depending on a list of numbers.

beginner

How do you use np.choose() to select elements conditionally?

You provide an index array that tells which choice to pick for each position, and a list of arrays to choose from. np.choose() returns an array with elements picked accordingly.

intermediate

What types of arrays can be passed as choices to np.choose()?

Choices can be lists or arrays of the same shape or broadcastable shapes. np.choose() picks elements from these arrays based on the index array.

intermediate

What happens if the index array in np.choose() contains values outside the range of choices?

It causes an error because np.choose() expects index values between 0 and the number of choices minus one.

beginner

Give a real-life example where np.choose() can be useful.

Imagine you have weather data for sunny, rainy, and snowy days. Using np.choose(), you can pick the right temperature array based on the weather condition index for each day.

What does the index array in np.choose() represent?

A Which choice array to select from for each element

B Positions to pick from each choice array

C The shape of the output array

D The data type of the output

The index array tells np.choose() which choice array to pick from for each element.

If you have 3 choice arrays, what is the valid range of values in the index array for np.choose()?

A 1 to 3

B 0 to 3

C 0 to 2

D -1 to 2

Index values must be between 0 and number_of_choices - 1, so 0 to 2 for 3 choices.

What will happen if the index array contains a value 5 but there are only 3 choices?

A It will pick the first choice

B It will pick the last choice

C It will ignore the value

D It will raise an error

Index out of range causes an error in np.choose().

Which of these is a correct way to call np.choose()?

A np.choose(index_array, [choice1, choice2])

B np.choose(choice1, choice2, index_array)

C np.choose([choice1, choice2], index_array)

D np.choose(index_array, choice1, choice2)

The second argument must be a list or tuple of choice arrays.

What is the shape of the output from np.choose()?

A Always 1D

B Same as the index array

C Same as the first choice array

D Depends on the number of choices

The output shape matches the index array shape after broadcasting.

Explain how np.choose() works for conditional selection with an example.

Think about picking items from different boxes based on a list of numbers.

What are the common errors to watch out for when using np.choose()?

Consider what happens if the index array has invalid values or incompatible shapes.