Mplcursors lets you add labels that appear when you hover over points on a plot. This helps you see details without cluttering the graph.
Mplcursors for hover labels in Matplotlib
Start learning this pattern below
Jump into concepts and practice - no test required
or
Test this pattern10 questions across easy, medium, and hard to know if this pattern is strong
Introduction
Syntax
Matplotlib
import mplcursors cursor = mplcursors.cursor(plot_elements) cursor.connect("add", lambda sel: sel.annotation.set_text('your label text'))
mplcursors.cursor() activates hover labels on given plot elements like lines or scatter points.
The connect method lets you customize the label text when hovering.
Examples
Matplotlib
import matplotlib.pyplot as plt import mplcursors fig, ax = plt.subplots() points = ax.scatter([1, 2, 3], [4, 5, 6]) cursor = mplcursors.cursor(points) cursor.connect("add", lambda sel: sel.annotation.set_text(f"Point: {sel.target}")) plt.show()
Matplotlib
import matplotlib.pyplot as plt import mplcursors fig, ax = plt.subplots() line, = ax.plot([1, 2, 3], [4, 5, 6], marker='o') cursor = mplcursors.cursor(line) cursor.connect("add", lambda sel: sel.annotation.set_text(f"Index: {sel.index}\nValue: {sel.target[1]}")) plt.show()
Sample Program
This program creates a scatter plot and shows x and y values when you hover over each point.
Matplotlib
import matplotlib.pyplot as plt import mplcursors # Create a scatter plot fig, ax = plt.subplots() x = [10, 20, 30, 40] y = [1, 4, 9, 16] scatter = ax.scatter(x, y) # Add hover labels showing x and y values cursor = mplcursors.cursor(scatter) cursor.connect("add", lambda sel: sel.annotation.set_text(f"x={sel.target[0]}\ny={sel.target[1]}")) plt.title('Scatter plot with hover labels') plt.xlabel('X axis') plt.ylabel('Y axis') plt.show()
Important Notes
Make sure you have mplcursors installed: run pip install mplcursors.
Hover labels only appear when you move the mouse over the plot points.
You can customize the label text fully using the connect method.
Summary
Mplcursors adds interactive hover labels to matplotlib plots.
Use it to show details about points without cluttering the graph.
Customize labels easily with a simple function.
Practice
1. What is the main purpose of using
mplcursors in matplotlib plots?easy
Solution
Step 1: Understand mplcursors functionality
mplcursorsis a tool that adds interactive hover labels to matplotlib plots, showing data values when you hover over points.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.Final Answer:
To add interactive hover labels showing data values -> Option CQuick 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
Solution
Step 1: Recall correct import syntax
The mplcursors library is a separate package and is imported simply withimport mplcursors.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.Final Answer:
import mplcursors -> Option AQuick 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
Solution
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.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.Final Answer:
Plot shows points with hover labels displaying (x, y) values -> Option AQuick 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
Solution
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.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.Final Answer:
The plot command is missing marker style to show points -> Option BQuick 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
Solution
Step 1: Understand how to filter hover labels
mplcursors allows connecting to events like 'add' to customize annotation visibility based on data values.Step 2: Analyze options for filtering by y > 5
Usemplcursors.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 withmplcursors.cursor(points, hover=True, filter=lambda sel: sel.target[1] > 5)uses a non-existent 'filter' argument. Usemplcursors.cursor(points).remove()for points with y <= 5 tries to remove cursor which is not valid for selective filtering.Final Answer:
Use mplcursors.cursor(points).connect('add', lambda sel: sel.annotation.set_visible(sel.target[1] > 5)) -> Option DQuick 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
