Pick events for data interaction in Matplotlib - Mini Project: Build & Apply

Pick Events for Data Interaction with Matplotlib

📖 Scenario: You are working with a simple scatter plot showing sales data points for different products. You want to make the plot interactive so that when you click on a point, it shows the product name and sales value.

🎯 Goal: Create a scatter plot with clickable points using Matplotlib's pick events. When a point is clicked, display the product name and sales value in the console.

📋 What You'll Learn

Create a dictionary called sales_data with product names as keys and sales numbers as values

Create a variable called fig, ax to set up the Matplotlib figure and axes

Plot the sales data as a scatter plot with picker=True to enable picking

Define a function called on_pick that prints the product name and sales value when a point is clicked

Connect the pick event to the on_pick function

Display the plot with plt.show()

💡 Why This Matters

🌍 Real World

Interactive plots help users explore data visually by clicking on points to get more details, useful in sales analysis, scientific data, and dashboards.

💼 Career

Data scientists and analysts often create interactive visualizations to communicate insights clearly and allow stakeholders to explore data dynamically.

1

Create the sales data dictionary

Create a dictionary called sales_data with these exact entries: 'Apples': 50, 'Bananas': 75, 'Cherries': 30, 'Dates': 90, 'Elderberries': 45.

Matplotlib

# Create the sales_data dictionary with product names and sales values
# Your code here

Hint

Use curly braces {} to create a dictionary with the exact keys and values.

2

Set up the Matplotlib figure and axes

Import matplotlib.pyplot as plt. Create a figure and axes using fig, ax = plt.subplots().

Matplotlib

sales_data = {'Apples': 50, 'Bananas': 75, 'Cherries': 30, 'Dates': 90, 'Elderberries': 45}

# Import matplotlib.pyplot as plt and create fig, ax
# Your code here

Hint

Use import matplotlib.pyplot as plt and then plt.subplots() to create the figure and axes.

3

Plot the scatter plot with picker enabled

Plot the sales data as a scatter plot on ax using ax.scatter(). Use the product indices as x-values and sales values as y-values. Set picker=True to enable picking.

Matplotlib

import matplotlib.pyplot as plt

sales_data = {'Apples': 50, 'Bananas': 75, 'Cherries': 30, 'Dates': 90, 'Elderberries': 45}

fig, ax = plt.subplots()

# Plot scatter with picker=True
# Your code here

Hint

Convert the dictionary keys and values to lists. Use range(len(products)) for x-values and sales for y-values. Enable picking with picker=True.

4

Add pick event handler and show plot

Define a function called on_pick(event) that prints the product name and sales value of the clicked point. Connect this function to the figure's pick event using fig.canvas.mpl_connect('pick_event', on_pick). Finally, call plt.show() to display the plot.

Matplotlib

import matplotlib.pyplot as plt

sales_data = {'Apples': 50, 'Bananas': 75, 'Cherries': 30, 'Dates': 90, 'Elderberries': 45}

fig, ax = plt.subplots()

products = list(sales_data.keys())
sales = list(sales_data.values())
scatter = ax.scatter(range(len(products)), sales, picker=True)
ax.set_xticks(range(len(products)))
ax.set_xticklabels(products)

# Define on_pick function and connect pick event
# Your code here

Hint

Use event.ind[0] to get the index of the clicked point. Print the product and sales using that index. Connect the event with fig.canvas.mpl_connect.

Practice

1. What does setting the picker parameter on a plot element in matplotlib do?

easy

A. Removes the plot element from the figure

B. Makes the plot element respond to mouse clicks for interaction

C. Saves the plot element as an image file

D. Changes the color of the plot element

Solution

1. Step 1: Understand the role of the picker parameter

   The picker parameter enables a plot element to detect mouse clicks or pick events.

2. Step 2: Connect picker to interaction

   When picker is set, the element becomes clickable, allowing interaction like showing data details.

3. Final Answer:

   Makes the plot element respond to mouse clicks for interaction -> Option B

4. Quick Check:

   picker enables click interaction = D [OK]

Hint: picker makes plot elements clickable for interaction [OK]

Common Mistakes:

• Confusing picker with color or style changes
• Thinking picker saves images
• Assuming picker removes elements

2. Which of the following is the correct way to connect a pick event handler function named on_pick to a matplotlib figure fig?

easy

A. fig.mpl_connect('pick_event', on_pick)

B. fig.connect('pick_event', on_pick)

C. fig.canvas.mpl_connect('pick_event', on_pick)

D. fig.canvas.connect('pick_event', on_pick)

Solution

1. Step 1: Recall the correct method to connect events in matplotlib

   Events are connected using mpl_connect on the figure's canvas object.

2. Step 2: Match the syntax for pick events

   The correct syntax is fig.canvas.mpl_connect('pick_event', handler_function).

3. Final Answer:

   fig.canvas.mpl_connect('pick_event', on_pick) -> Option C

4. Quick Check:

   Use fig.canvas.mpl_connect for events = A [OK]

Hint: Use fig.canvas.mpl_connect to link pick events [OK]

Common Mistakes:

• Using fig.connect instead of fig.canvas.mpl_connect
• Calling mpl_connect on fig instead of fig.canvas
• Using connect instead of mpl_connect

3. Consider the code below:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
line, = ax.plot([1, 2, 3], [4, 5, 6], picker=5)
def on_pick(event):
    print(f"Picked point: {event.ind}")
fig.canvas.mpl_connect('pick_event', on_pick)
plt.show()

What will happen when you click near the second point on the line?

medium

A. The program prints 'Picked point: [1]' indicating the second point was picked

B. Nothing happens because picker=5 is invalid

C. An error occurs because on_pick is not connected properly

D. The plot closes immediately

Solution

1. Step 1: Understand picker=5 meaning

   Setting picker=5 means clicks within 5 points of the line points trigger pick events.

2. Step 2: Analyze on_pick behavior on clicking second point

   Clicking near the second point triggers on_pick, printing the index of that point, which is 1 (zero-based).

3. Final Answer:

   The program prints 'Picked point: [1]' indicating the second point was picked -> Option A

4. Quick Check:

   picker=5 triggers pick near points = C [OK]

Hint: picker=5 allows clicks near points to trigger events [OK]

Common Mistakes:

• Thinking picker=5 is invalid
• Assuming event.ind is not available
• Believing on_pick is not connected

4. The following code is intended to print the index of a picked point on a scatter plot, but it raises an error:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
sc = ax.scatter([1,2,3], [4,5,6], picker=True)
def on_pick(event):
    print(event.ind)
fig.mpl_connect('pick_event', on_pick)
plt.show()

What is the main error causing the failure?

medium

A. Calling mpl_connect on fig instead of fig.canvas

B. Using picker=True instead of a numeric tolerance

C. Not defining on_pick before connecting it

D. Using scatter instead of plot for pick events

Solution

1. Step 1: Check how event connection is done

   The code calls fig.mpl_connect, but the correct method is fig.canvas.mpl_connect.

2. Step 2: Understand impact of wrong connection

   Because mpl_connect is not a method of fig, this causes an AttributeError and failure.

3. Final Answer:

   Calling mpl_connect on fig instead of fig.canvas -> Option A

4. Quick Check:

   Use fig.canvas.mpl_connect, not fig.mpl_connect = A [OK]

Hint: Always connect events on fig.canvas, not fig [OK]

Common Mistakes:

• Using picker=True is allowed, not an error
• Assuming on_pick must be defined before connection
• Thinking scatter can't use pick events

5. You want to create an interactive matplotlib scatter plot where clicking a point highlights it by changing its color. Which approach correctly combines pick events and updating the plot?

hard

A. Set picker on scatter points, connect pick_event to a function that prints point coordinates only

B. Set picker on the figure, not on points, and change colors in the handler

C. Use plt.show() inside the pick event handler to refresh the plot

D. Set picker on scatter points, connect pick_event to a function that changes the point's color and calls fig.canvas.draw()

Solution

1. Step 1: Enable picking on scatter points

   Set the picker parameter on scatter plot points to detect clicks on them.

2. Step 2: Update point color and redraw figure in handler

   In the pick event handler, change the color of the selected point and call fig.canvas.draw() to update the display.

3. Final Answer:

   Set picker on scatter points, connect pick_event to a function that changes the point's color and calls fig.canvas.draw() -> Option D

4. Quick Check:

   picker + color change + canvas.draw() = B [OK]

Hint: Change color in handler and redraw with fig.canvas.draw() [OK]

Common Mistakes:

• Only printing coordinates without updating plot
• Calling plt.show() inside event handler causes errors
• Setting picker on figure instead of points