Why patterns solve common tasks in Matplotlib - Challenge Your Understanding

Challenge - 5 Problems

❓ visualization

intermediate

Identify the correct pattern for plotting multiple lines

You want to plot three lines on the same graph using matplotlib. Which code pattern correctly plots all three lines with different colors?

Matplotlib

import matplotlib.pyplot as plt

x = [1, 2, 3, 4]
y1 = [1, 4, 9, 16]
y2 = [2, 3, 5, 7]
y3 = [3, 5, 7, 11]

A

plt.plot(x, y1, 'r')
plt.plot(x, y2, 'g')
plt.plot(x, y3, 'b')
plt.show()

B

plt.plot(x, y1)
plt.plot(x, y2)
plt.plot(x, y3)
plt.show()

C

plt.plot(x, y1, 'r', x, y2, 'g', x, y3, 'b')
plt.show()

D

plt.plot(y1, 'r')
plt.plot(y2, 'g')
plt.plot(y3, 'b')
plt.show()

💡 Hint

Check how multiple lines can be plotted in one call to plt.plot().

Option C uses a single plt.plot() call with x and y pairs for each line and color codes, which is an efficient pattern to plot multiple lines at once.

❓ Predict Output

intermediate

Output of a loop plotting pattern

What will be the output of this matplotlib code snippet?

Matplotlib

import matplotlib.pyplot as plt

x = [0, 1, 2]
for i in range(3):
    plt.plot(x, [j*(i+1) for j in x])
plt.show()

A Three lines plotted with slopes 1, 2, and 3 respectively

B One line plotted with slope 3

C Error because plt.plot inside loop is not allowed

D Three lines plotted but all overlap with slope 1

💡 Hint

Consider how the loop changes the y-values for each line.

The loop plots three lines, each with y-values scaled by 1, 2, and 3, resulting in lines with slopes 1, 2, and 3.

🔧 Debug

advanced

Find the error in this plotting pattern

What error does this code raise?

Matplotlib

import matplotlib.pyplot as plt

x = [1, 2, 3]
y = [4, 5]
plt.plot(x, y)
plt.show()

A ValueError: x and y must have same first dimension

B TypeError: unsupported operand type(s) for +

C SyntaxError: invalid syntax

D No error, plots a line

💡 Hint

Check if x and y lists have the same length.

Matplotlib requires x and y to have the same length. Here, x has 3 elements but y has 2, causing a ValueError.

🚀 Application

advanced

Choose the best pattern to add labels and legend

You want to plot two lines and add labels and a legend. Which code pattern correctly does this?

Matplotlib

import matplotlib.pyplot as plt

x = [1, 2, 3]
y1 = [2, 4, 6]
y2 = [1, 3, 5]

A

plt.plot(x, y1)
plt.plot(x, y2)
plt.show()

B

plt.plot(x, y1, label='Line 1')
plt.plot(x, y2, label='Line 2')
plt.legend()
plt.xlabel('X axis')
plt.ylabel('Y axis')
plt.show()

C

plt.plot(x, y1, label='Line 1')
plt.plot(x, y2, label='Line 2')
plt.show()

D

plt.plot(x, y1)
plt.plot(x, y2)
plt.legend(['Line 1', 'Line 2'])
plt.xlabel('X axis')
plt.ylabel('Y axis')
plt.show()

💡 Hint

Check how labels and legends are added in matplotlib.

Option B uses label in plot calls and calls plt.legend() to show them, plus axis labels, which is the correct pattern.

🧠 Conceptual

expert

Why use plotting patterns in data science?

Which statement best explains why using common plotting patterns is important in data science?

A They automatically clean data before plotting

B They guarantee the fastest execution time for plotting

C They allow plotting without importing any libraries

D They reduce code repetition and make plots easier to read and maintain

💡 Hint

Think about code clarity and efficiency.

Common plotting patterns help reduce repeated code and make it easier for others to understand and maintain visualizations.