Plotting the Model on the Data

Continuing with the same measured data from the previous exercise, your goal is to use a predefined model() and measured data times and measured_distances to compute modeled distances, and then plot both measured and modeled data on the same axis.

context figure

This exercise is part of the course

Introduction to Linear Modeling in Python

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Exercise instructions

Use model_distances = model(times, measured_distances) to compute the modeled values.
Use plt.subplots() to create figure and axis objects.
Use axis.plot() to plot times vs measured_distances with options linestyle=" ", marker="o", color="black".
Use axis.plot() to also plot times vs model_distances with options linestyle="-", color="red".

Hands-on interactive exercise

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

# Pass times and measured distances into model
model_distances = model(____, ____)

# Create figure and axis objects and call axis.plot() twice to plot data and model distances versus times
fig, axis = plt.subplots()
axis.plot(____, ____, linestyle="____", marker="____", color="____", label="Measured")
axis.plot(____, ____, linestyle="____", marker=None, color="____", label="Modeled")

# Add grid lines and a legend to your plot, and then show to display
axis.grid(True)
axis.legend(loc="best")
plt.show()

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