Mplcursors for hover labels in Matplotlib - Time & Space Complexity

Time Complexity: Mplcursors for hover labels

O(n)

Understanding Time Complexity

When using mplcursors to add hover labels on plots, it's important to understand how the time to respond grows as the number of points increases.

We want to know how the hover label updates scale with more data points.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

import matplotlib.pyplot as plt
import mplcursors

n = 100  # Define n before using it
fig, ax = plt.subplots()
points = ax.scatter(range(n), range(n))
mplcursors.cursor(points)
plt.show()

This code creates a scatter plot with n points and enables hover labels using mplcursors.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Checking mouse position against each of the n points to detect hover.
• How many times: This check happens every time the mouse moves over the plot area.

How Execution Grows With Input

As the number of points n increases, the system checks more points for hover detection.

Input Size (n)	Approx. Operations per Hover
10	10 checks
100	100 checks
1000	1000 checks

Pattern observation: The number of checks grows linearly with the number of points.

Final Time Complexity

Time Complexity: O(n)

This means the time to detect which point is hovered grows directly with the number of points.

Common Mistake

[X] Wrong: "Hover detection time stays the same no matter how many points are plotted."

[OK] Correct: Each point must be checked to see if the mouse is over it, so more points mean more checks and longer detection time.

Interview Connect

Understanding how interactive plot features scale helps you design responsive visualizations and shows you can think about user experience and performance together.

Self-Check

What if we changed from scatter points to a heatmap? How would the time complexity of hover detection change?

Practice

1. What is the main purpose of using mplcursors in matplotlib plots?

easy

A. To save the plot as an image file

B. To change the color of the plot lines

C. To add interactive hover labels showing data values

D. To create 3D plots automatically

Solution

1. Step 1: Understand mplcursors functionality

   mplcursors is a tool that adds interactive hover labels to matplotlib plots, showing data values when you hover over points.

2. Step 2: Compare options with mplcursors purpose

   Changing colors, saving images, or creating 3D plots are not related to hover labels, so only adding interactive hover labels fits.

3. Final Answer:

   To add interactive hover labels showing data values -> Option C

4. Quick Check:

   mplcursors = interactive hover labels [OK]

Hint: Remember mplcursors = hover labels for data points [OK]

Common Mistakes:

• Confusing mplcursors with plot styling tools
• Thinking mplcursors saves files
• Assuming mplcursors creates 3D plots

2. Which of the following is the correct way to import mplcursors for use in a matplotlib plot?

easy

A. import mplcursors

B. from matplotlib import mplcursors

C. import matplotlib.mplcursors

D. import mpl_cursor

Solution

1. Step 1: Recall correct import syntax

   The mplcursors library is a separate package and is imported simply with import mplcursors.

2. Step 2: Check other options for errors

   from matplotlib import mplcursors is wrong because mplcursors is not part of matplotlib. import matplotlib.mplcursors is wrong because it's a separate package, not a submodule. import mpl_cursor is incorrect because the module name is mplcursors, not mpl_cursor.

3. Final Answer:

   import mplcursors -> Option A

4. Quick Check:

   Correct import = import mplcursors [OK]

Hint: Use simple import: import mplcursors [OK]

Common Mistakes:

• Trying to import mplcursors from matplotlib
• Thinking mplcursors is matplotlib.mplcursors submodule
• Using wrong module name like mpl_cursor

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

import matplotlib.pyplot as plt
import mplcursors

fig, ax = plt.subplots()
points = ax.plot([1, 2, 3], [4, 5, 6], 'o')
mplcursors.cursor(points)
plt.show()

medium

A. Plot shows points with hover labels displaying (x, y) values

B. Plot shows points but no hover labels appear

C. Code raises an error because cursor() needs extra arguments

D. Plot shows a line connecting points without markers

Solution

1. Step 1: Understand code components

   The code plots points at (1,4), (2,5), (3,6) with markers 'o'. Then mplcursors.cursor(points) adds interactive hover labels.

2. Step 2: Predict output behavior

   When running plt.show(), the plot appears with points. Hovering over points shows labels with their coordinates because mplcursors is activated correctly.

3. Final Answer:

   Plot shows points with hover labels displaying (x, y) values -> Option A

4. Quick Check:

   mplcursors.cursor(points) = hover labels shown [OK]

Hint: mplcursors.cursor() adds hover labels to plotted points [OK]

Common Mistakes:

• Thinking cursor() needs extra arguments
• Expecting no hover labels without extra setup
• Confusing line plot with marker plot

4. Identify the error in this code that prevents hover labels from showing:

import matplotlib.pyplot as plt
import mplcursors

fig, ax = plt.subplots()
line, = ax.plot([1, 2, 3], [4, 5, 6])
mplcursors.cursor(line)
plt.show()

medium

A. The variable 'line' should be a list, not a single Line2D object

B. The plot command is missing marker style to show points

C. mplcursors is not imported correctly

D. mplcursors.cursor() must be called before plotting

Solution

1. Step 1: Analyze plot and cursor usage

   The code plots a line without markers. Hover labels appear on points, but here points are not visible because no markers are set.

2. Step 2: Identify why hover labels don't show

   mplcursors works on plotted points. Without markers, the line is continuous and no discrete points exist to hover on, so labels don't appear.

3. Final Answer:

   The plot command is missing marker style to show points -> Option B

4. Quick Check:

   Missing markers = no hover labels [OK]

Hint: Add markers to plot for mplcursors hover labels [OK]

Common Mistakes:

• Thinking mplcursors must be called before plot
• Assuming single Line2D object is invalid input
• Believing import error causes no labels

5. You want to show hover labels only for points where y > 5 in this plot. Which code change achieves this?

import matplotlib.pyplot as plt
import mplcursors

fig, ax = plt.subplots()
x = [1, 2, 3, 4]
y = [4, 5, 6, 7]
points = ax.plot(x, y, 'o')
# Add hover labels only for y > 5
mplcursors.cursor(points)

hard

A. Use mplcursors.cursor(points).remove() for points with y <= 5

B. Filter points before plotting: ax.plot([xi for xi, yi in zip(x,y) if yi>5], [yi for yi in y if yi>5], 'o')

C. Set cursor with mplcursors.cursor(points, hover=True, filter=lambda sel: sel.target[1] > 5)

D. Use mplcursors.cursor(points).connect('add', lambda sel: sel.annotation.set_visible(sel.target[1] > 5))

Solution

1. Step 1: Understand how to filter hover labels

   mplcursors allows connecting to events like 'add' to customize annotation visibility based on data values.

2. Step 2: Analyze options for filtering by y > 5

   Use mplcursors.cursor(points).connect('add', lambda sel: sel.annotation.set_visible(sel.target[1] > 5)) uses a lambda to set annotation visible only if y > 5, which is correct. Filter points before plotting: ax.plot([xi for xi, yi in zip(x,y) if yi>5], [yi for yi in y if yi>5], 'o') filters points before plotting but does not use mplcursors filtering. Set cursor with mplcursors.cursor(points, hover=True, filter=lambda sel: sel.target[1] > 5) uses a non-existent 'filter' argument. Use mplcursors.cursor(points).remove() for points with y <= 5 tries to remove cursor which is not valid for selective filtering.

3. Final Answer:

   Use mplcursors.cursor(points).connect('add', lambda sel: sel.annotation.set_visible(sel.target[1] > 5)) -> Option D

4. Quick Check:

   Connect 'add' event to filter hover labels [OK]

Hint: Use cursor.connect('add', lambda sel: condition) to filter labels [OK]

Common Mistakes:

• Trying to filter points only by plotting
• Using unsupported 'filter' argument in cursor()
• Attempting to remove cursor for selective points