You want to plot a 3D scatter plot with points colored by their z-value. Which code snippet correctly creates the 3D axes and colors the points accordingly?

hard📝 Application Q15 of 15

Matplotlib - 3D Plotting

Afig = plt.figure() ax = fig.add_subplot(111, projection='3d') z = [1, 2, 3] ax.scatter([1,2,3], [4,5,6], z) plt.show()

Bfig = plt.figure() ax = plt.axes(projection='3d') z = [1, 2, 3] ax.scatter([1,2,3], [4,5,6], z, color='z') plt.show()

Cfig = plt.figure() ax = fig.add_subplot(111) z = [1, 2, 3] ax.scatter([1,2,3], [4,5,6], z, c=z) plt.show()

Dfig = plt.figure() ax = fig.add_subplot(111, projection='3d') z = [1, 2, 3] ax.scatter([1,2,3], [4,5,6], z, c=z, cmap='viridis') plt.show()

Step-by-Step Solution

Solution:

Step 1: Create 3D axes correctly
Use fig.add_subplot(111, projection='3d') to create 3D axes linked to the figure.
Step 2: Color points by z-value
Pass c=z and a colormap like cmap='viridis' to scatter() to color points based on z.
Final Answer:
fig = plt.figure() ax = fig.add_subplot(111, projection='3d') z = [1, 2, 3] ax.scatter([1,2,3], [4,5,6], z, c=z, cmap='viridis') plt.show() -> Option D
Quick Check:
3D axes + c=z + cmap = fig = plt.figure() ax = fig.add_subplot(111, projection='3d') z = [1, 2, 3] ax.scatter([1,2,3], [4,5,6], z, c=z, cmap='viridis') plt.show() [OK]

Quick Trick: Use c=z and cmap for coloring in 3D scatter [OK]

Common Mistakes:

Using color='z' instead of c=z
Creating 2D axes for 3D data
Not specifying projection='3d'

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You want to plot a 3D scatter plot with points colored by their z-value. Which code snippet correctly creates the 3D axes and colors the points accordingly?

Step 1: Create 3D axes correctly

Step 2: Color points by z-value

Final Answer:

Quick Check:

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