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.

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Este exercicio faz parte do curso

Introduction to Linear Modeling in Python

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Instruções do exercicio

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".

exercicio interativo prático

Tente este exercicio completando este código de exemplo.

# 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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