Spine charts concept in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of a basic spine chart plot

What will be the output of the following Python code using matplotlib to create a spine chart?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

labels = ['A', 'B', 'C', 'D']
values = [10, 15, 7, 12]

fig, ax = plt.subplots()
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_position(('outward', 10))
ax.spines['bottom'].set_position(('outward', 10))
ax.plot(labels, values, marker='o')
plt.show()

A A line plot with markers but all spines visible in default positions.

B A bar chart with bars for A, B, C, D and all four spines visible in default positions.

C A scatter plot with points at A, B, C, D and all spines hidden.

D A line plot with markers connecting points A, B, C, D and only left and bottom spines visible, shifted outward by 10 points.

💡 Hint

Look at which spines are set visible and their positions.

The code hides the top and right spines, and moves the left and bottom spines outward by 10 points. The plot is a line plot with markers connecting the points labeled A to D.

❓ data_output

intermediate

Number of visible spines after customization

After running this code, how many spines are visible on the plot?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(True)
ax.spines['bottom'].set_visible(True)
plt.show()

A 2

B 3

C 4

D 1

💡 Hint

Check which spines are set to visible True or False.

Only the left and bottom spines are visible; top and right are hidden.

🔧 Debug

advanced

Identify the error in spine position setting

What error will this code raise when trying to set spine position?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.spines['left'].set_position('outward', 10)
plt.show()

A No error, the code runs successfully

B TypeError: set_position() takes 2 positional arguments but 3 were given

C ValueError: spine position must be a tuple or string

D AttributeError: 'Spine' object has no attribute 'set_position'

💡 Hint

Check the method signature for set_position in matplotlib spines.

The set_position method expects a single argument which can be a string or a tuple. Passing two separate arguments causes a TypeError.

❓ visualization

advanced

Effect of spine position on plot appearance

Which option best describes the visual effect of setting the bottom spine position to ('axes', 0.5)?

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.spines['bottom'].set_position(('axes', 0.5))
ax.plot([0, 1], [0, 1])
plt.show()

A The bottom spine moves to the middle of the plot area horizontally at half the axes height.

B The bottom spine moves outside the plot area by 0.5 inches.

C The bottom spine stays at the default position at the bottom edge.

D The bottom spine disappears from the plot.

💡 Hint

The 'axes' coordinate system ranges from 0 (bottom) to 1 (top) vertically.

Setting position to ('axes', 0.5) moves the spine to the vertical center of the axes area.

🧠 Conceptual

expert

Purpose of spine customization in data visualization

Why would a data scientist customize spines in a plot? Choose the best reason.

A To change the data values shown on the plot axes.

B To increase the plot size automatically based on data range.

C To improve plot readability by emphasizing important axes and reducing clutter.

D To add interactive features like zoom and pan to the plot.

💡 Hint

Think about how visual design affects understanding of data.

Customizing spines helps highlight key axes and remove unnecessary lines, making plots clearer and easier to read.