3D scatter plots in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the 3D plotting toolkit from matplotlib.

Matplotlib

from mpl_toolkits.mplot3d import [1]

Drag options to blanks, or click blank then click option'

AAxes2D

BAxes3D

Cscatter3d

Dplot3d

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'plot3d' which is not a valid import.

Confusing 2D and 3D axes names.

The 3D plotting toolkit in matplotlib is called Axes3D. Importing it allows us to create 3D plots.

2fill in blank

medium

Complete the code to create a 3D subplot in matplotlib.

Matplotlib

fig = plt.figure()
ax = fig.add_subplot(111, projection=[1])

Drag options to blanks, or click blank then click option'

A'2d'

B'scatter'

C'3d'

D'plot3d'

Attempts:

3 left

💡 Hint

Common Mistakes

Using '2d' projection which creates a 2D plot.

Using 'scatter' or 'plot3d' which are not valid projection strings.

To create a 3D subplot, the projection argument must be set to '3d'.

3fill in blank

hard

Fix the error in the code to plot a 3D scatter plot with x, y, z data.

Matplotlib

ax.scatter([1], y, z)

Drag options to blanks, or click blank then click option'

Az

B[x]

CX

Dx

Attempts:

3 left

💡 Hint

Common Mistakes

Using uppercase 'X' which is undefined.

Passing a list with brackets which is unnecessary.

Passing 'z' instead of 'x' for the x-axis.

The variable x must be passed exactly as it is to the scatter function to plot the x-coordinates.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length if the length is greater than 3.

Matplotlib

{word: [1] for word in words if [2]

Drag options to blanks, or click blank then click option'

Alen(word)

Blen(word) > 3

Cword > 3

Dlen(words) > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word > 3' which compares a string to a number.

Using 'len(words) > 3' which checks the length of the whole list.

The dictionary comprehension maps each word to its length using len(word). The condition filters words with length greater than 3 using len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their values if the value is greater than 0.

Matplotlib

{ [1]: [2] for k, v in data.items() if [3] }

Drag options to blanks, or click blank then click option'

Ak.upper()

Bv

Cv > 0

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using k.lower() instead of uppercase.

Filtering with k > 0 which compares string to number.

Mapping keys to keys instead of values.

The dictionary comprehension maps the uppercase version of the key k.upper() to its value v, filtering only those pairs where the value is greater than zero v > 0.

Practice

1. What is the main purpose of using a 3D scatter plot in matplotlib?

easy

A. To display text annotations in 3D space

B. To visualize data points in three dimensions and observe patterns

C. To plot a line graph with three lines

D. To create a bar chart with three bars

Solution

1. Step 1: Understand the role of 3D scatter plots

   3D scatter plots show points in three dimensions, helping to see relationships among three variables.

2. Step 2: Compare with other plot types

   Bar charts and line graphs do not show points in 3D space, and text annotations are not the main purpose.

3. Final Answer:

   To visualize data points in three dimensions and observe patterns -> Option B

4. Quick Check:

   3D scatter plots = visualize points in 3D [OK]

Hint: 3D scatter plots show points in 3D space [OK]

Common Mistakes:

• Confusing 3D scatter with bar or line plots
• Thinking 3D scatter is for text annotations
• Assuming 3D scatter plots show continuous surfaces

2. Which of the following is the correct way to create a 3D scatter plot axis in matplotlib?

easy

A. ax = plt.axes(projection='3d')

B. ax = plt.subplots(projection='3d')

C. ax = plt.figure(projection='3d')

D. ax = plt.subplot(projection='3d')

Solution

1. Step 1: Recall how to create 3D axes

   In matplotlib, plt.axes(projection='3d') creates a 3D axes object.

2. Step 2: Check other options

   plt.subplot and plt.subplots do not accept projection directly; plt.figure creates a figure, not axes.

3. Final Answer:

   ax = plt.axes(projection='3d') -> Option A

4. Quick Check:

   Use plt.axes with projection='3d' for 3D axes [OK]

Hint: Use plt.axes(projection='3d') to get 3D axes [OK]

Common Mistakes:

• Using plt.subplot instead of plt.axes for 3D
• Passing projection to plt.figure instead of axes
• Confusing plt.subplots with plt.subplot

3. What will be the output of this code snippet?

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter([1, 2], [3, 4], [5, 6], c='r', marker='o')
plt.show()

medium

A. A 3D scatter plot with two red circular points at coordinates (1,3,5) and (2,4,6)

B. A 2D scatter plot with red points

C. A syntax error due to missing import

D. An empty plot with no points

Solution

1. Step 1: Analyze the code for 3D scatter plot creation

   The code creates a figure, adds a 3D subplot, and plots two points with coordinates (1,3,5) and (2,4,6) in red circles.

2. Step 2: Confirm the plot output

   The points will appear in 3D space as red circles; no errors occur.

3. Final Answer:

   A 3D scatter plot with two red circular points at coordinates (1,3,5) and (2,4,6) -> Option A

4. Quick Check:

   3D scatter with given points = red circles at (1,3,5) and (2,4,6) [OK]

Hint: Check coordinates and color for scatter points [OK]

Common Mistakes:

• Thinking it creates 2D plot instead of 3D
• Assuming syntax error without checking imports
• Expecting no points plotted

4. Identify the error in this code that tries to plot a 3D scatter plot:

import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter([1,2,3], [4,5,6], [7,8,9])
plt.show()

medium

A. scatter function does not accept three arguments

B. The lists for x, y, z have different lengths

C. plt.figure() is not imported correctly

D. Missing projection='3d' in add_subplot, so 3D plotting fails

Solution

1. Step 1: Check subplot creation for 3D

   The code uses fig.add_subplot(111) without projection='3d', so it creates a 2D axes.

2. Step 2: Understand scatter with 3D data

   On 2D axes, passing three lists to scatter will treat the third list as point sizes instead of z-coordinates, producing a 2D scatter plot rather than 3D.

3. Final Answer:

   Missing projection='3d' in add_subplot, so 3D plotting fails -> Option D

4. Quick Check:

   3D scatter needs projection='3d' [OK]

Hint: Always add projection='3d' for 3D plots [OK]

Common Mistakes:

• Forgetting projection='3d' in add_subplot
• Thinking scatter can't take three arguments
• Assuming list length mismatch causes error

5. You want to plot a 3D scatter plot with points colored by their z-value using a colormap. Which code snippet correctly achieves this?

hard

A. ax.scatter(x, y, z, c='z', colormap='viridis')

B. ax.scatter(x, y, z, color='z', cmap='viridis')

C. ax.scatter(x, y, z, c=z, cmap='viridis')

D. ax.scatter(x, y, z, colors=z, cmap='viridis')

Solution

1. Step 1: Understand color mapping in scatter

   To color points by a variable, pass that variable to c= and specify cmap for colormap.

2. Step 2: Check correct parameter names

   c is correct for colors; color or colors with string 'z' or colormap are incorrect.

3. Final Answer:

   ax.scatter(x, y, z, c=z, cmap='viridis') -> Option C

4. Quick Check:

   Use c=variable and cmap='name' for color mapping [OK]

Hint: Use c=values and cmap='name' to color points [OK]

Common Mistakes:

• Using color='z' instead of c=z
• Using colormap instead of cmap
• Passing colors=z which is invalid