A range array

np.arange() has especially useful applications in graphing. Your task is to create a scatter plot with the values from doubling_array on the y-axis.

doubling_array = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512]

Recall that a scatter plot can be created using the following code:

plt.scatter(x_values, y_values)
plt.show()

With doubling_array on the y-axis, you now need values for the x-axis, which you can create with np.arange()!

numpy is loaded for you as np, and matplotlib.pyplot is imported as plt.

This exercise is part of the course

Introduction to NumPy

Exercise instructions

Using np.arange(), create a 1D array called one_to_ten which holds all integers from one to ten (inclusive).
Create a scatterplot with doubling_array as the y values and one_to_ten as the x values.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Create an array of integers from one to ten
one_to_ten = ____

# Create your scatterplot
____
plt.show()

Edit and Run Code

This exercise is part of the course

Introduction to NumPy

BeginnerSkill Level

4.8+

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Meet the incredible NumPy array! Learn how to create and change array shapes to suit your needs. Finally, discover NumPy's many data types and how they contribute to speedy array operations.

Exercise 1: Introducing arrays Exercise 2: Your first NumPy array Exercise 3: Creating arrays from scratch Exercise 4: A range array

Current Exercise

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