Highlight and annotate pattern in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib pyplot module with the common alias.

Matplotlib

import matplotlib.[1] as plt

Drag options to blanks, or click blank then click option'

Aplot

Bpyplot

Cgraph

Dcharts

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'plot' instead of 'pyplot' causes import errors.

Trying to import 'graph' or 'charts' which are not matplotlib modules.

The matplotlib module for plotting is called pyplot. We import it as plt to use its plotting functions easily.

2fill in blank

medium

Complete the code to plot a line graph using x and y data.

Matplotlib

plt.[1](x, y)
plt.show()

Drag options to blanks, or click blank then click option'

Ahist

Bscatter

Cbar

Dplot

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'scatter' plots points but does not connect them with lines.

Using 'bar' or 'hist' creates different chart types.

The plot function draws a line graph connecting points from x and y data.

3fill in blank

hard

Fix the error in the code to add an annotation at point (2, 4) with text 'Peak'.

Matplotlib

plt.annotate('Peak', xy=(2, 4), xytext=[1], arrowprops=dict(facecolor='black'))
plt.show()

Drag options to blanks, or click blank then click option'

A(3, 5)

B[3, 5]

C'3, 5'

D3, 5

Attempts:

3 left

💡 Hint

Common Mistakes

Using a list instead of a tuple for xytext.

Passing coordinates as a string or separate arguments.

The xytext parameter expects a tuple for the text position, so (3, 5) is correct.

4fill in blank

hard

Fill both blanks to highlight the region between x=1 and x=3 with a light blue color.

Matplotlib

plt.fill_between(x, y, where=(x [1] 1) & (x [2] 3), color='lightblue', alpha=0.5)
plt.show()

Drag options to blanks, or click blank then click option'

A>=

B<=

C<

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' or '>' incorrectly reverses the highlighted region.

Not using both conditions combined with &.

To highlight between x=1 and x=3, we select points where x is greater or equal to 1 and less or equal to 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each word to its length only if the length is greater than 3.

Matplotlib

lengths = { [1]: [2] for [3] in words if len([3]) > 3 }

Drag options to blanks, or click blank then click option'

Aword

Blen(word)

Dw

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names inconsistently.

Not filtering words by length > 3.

The dictionary comprehension uses word as the key, len(word) as the value, and iterates over word in words. The condition filters words longer than 3 characters.

Practice

1. What is the main purpose of using highlight and annotate in a matplotlib plot?

easy

A. To save the plot as an image file

B. To change the color scheme of the entire plot

C. To draw attention to important parts and add notes explaining data points

D. To remove grid lines from the plot

Solution

1. Step 1: Understand the role of highlight

   Highlighting is used to emphasize important areas on a graph to make them stand out.

2. Step 2: Understand the role of annotate

   Annotations add notes with arrows to explain or give more information about specific data points.

3. Final Answer:

   To draw attention to important parts and add notes explaining data points -> Option C

4. Quick Check:

   Highlight + annotate = emphasize + explain [OK]

Hint: Highlight = focus, annotate = explain with notes [OK]

Common Mistakes:

• Thinking highlight changes entire plot color
• Confusing annotate with saving files
• Assuming highlight removes grid lines

2. Which of the following is the correct syntax to add an annotation with an arrow pointing to point (2, 4) in matplotlib?

easy

A. plt.annotate('Note', xy=(2, 4), xytext=(3, 5), arrowprops=dict(facecolor='black'))

B. plt.annotate('Note', point=(2, 4), text=(3, 5), arrow=True)

C. plt.annotation('Note', xy=(2, 4), xytext=(3, 5), arrowprops=True)

D. plt.annotate('Note', xy=(2, 4), text=(3, 5), arrowprops=dict(color='red'))

Solution

1. Step 1: Check the function name and parameters

   The correct function is plt.annotate with parameters xy for point and xytext for text location.

2. Step 2: Verify arrow properties

   arrowprops must be a dictionary specifying arrow style, e.g., dict(facecolor='black').

3. Final Answer:

   plt.annotate('Note', xy=(2, 4), xytext=(3, 5), arrowprops=dict(facecolor='black')) -> Option A

4. Quick Check:

   Correct annotate syntax uses xy, xytext, arrowprops dict [OK]

Hint: Use xy and xytext with arrowprops dict for annotation [OK]

Common Mistakes:

• Using wrong parameter names like point or text
• Passing arrowprops as True instead of dict
• Using plt.annotation instead of plt.annotate

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

import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.plot(x, y)
plt.axvspan(2, 3, color='yellow', alpha=0.3)
plt.annotate('Peak', xy=(3, 25), xytext=(3.5, 27), arrowprops=dict(facecolor='blue'))
plt.show()

medium

A. A line plot with a red shaded area between x=2 and x=3 and no annotation

B. A line plot with a yellow shaded area between x=2 and x=3 and an annotation 'Peak' pointing at (3, 25)

C. A scatter plot with points highlighted in yellow and annotation at (3.5, 27)

D. A line plot with no shading and annotation text 'Peak' at (3, 25) without arrow

Solution

1. Step 1: Understand plt.axvspan usage

   plt.axvspan(2, 3, color='yellow', alpha=0.3) creates a translucent yellow vertical highlight between x=2 and x=3.

2. Step 2: Understand plt.annotate usage

   plt.annotate('Peak', xy=(3, 25), xytext=(3.5, 27), arrowprops=dict(facecolor='blue')) adds an annotation 'Peak' with an arrow pointing at (3, 25).

3. Final Answer:

   A line plot with a yellow shaded area between x=2 and x=3 and an annotation 'Peak' pointing at (3, 25) -> Option B

4. Quick Check:

   axvspan = highlight, annotate = note with arrow [OK]

Hint: axvspan highlights vertical area, annotate adds arrow note [OK]

Common Mistakes:

• Confusing axvspan color or range
• Thinking annotation text appears without arrow
• Mistaking line plot for scatter plot

4. Identify the error in this code that tries to highlight and annotate a point:

import matplotlib.pyplot as plt
x = [1, 2, 3]
y = [5, 7, 9]
plt.plot(x, y)
plt.axhspan(6, 8, color='green')
plt.annotate('Important', xy=(2, 7), xytext=(2, 9), arrowprops='->')
plt.show()

medium

A. plt.axhspan should use x values, not y values

B. plt.plot should use scatter instead for annotation

C. xytext coordinates must be inside the plot range

D. arrowprops should be a dictionary, not a string

Solution

1. Step 1: Check plt.axhspan usage

   plt.axhspan(6, 8, color='green') is correct to highlight horizontal area between y=6 and y=8.

2. Step 2: Check plt.annotate arrowprops parameter

   arrowprops must be a dictionary describing arrow style, not a string like '->'.

3. Final Answer:

   arrowprops should be a dictionary, not a string -> Option D

4. Quick Check:

   arrowprops = dict(...) not string [OK]

Hint: arrowprops needs dict, not string like '->' [OK]

Common Mistakes:

• Passing arrowprops as string instead of dict
• Confusing axhspan with axvspan usage
• Thinking xytext must be inside plot limits

5. You want to highlight the time period between 10 and 15 seconds on a line plot and annotate the highest point in that range with a label 'Max'. Which code snippet correctly achieves this?

hard

A. plt.axvspan(10, 15, color='lightblue', alpha=0.4)
max_x = 12
max_y = 50
plt.annotate('Max', xy=(max_x, max_y), xytext=(max_x+1, max_y+5), arrowprops=dict(facecolor='red'))

B. plt.axhspan(10, 15, color='lightblue', alpha=0.4)
max_x = 12
max_y = 50
plt.annotate('Max', xy=(max_x, max_y), xytext=(max_x-1, max_y-5), arrowprops='->')

C. plt.axvspan(10, 15, color='lightblue')
max_x = 12
max_y = 50
plt.annotate('Max', xy=(max_x, max_y), xytext=(max_x, max_y), arrowprops=dict(color='green'))

D. plt.axvspan(10, 15, color='yellow', alpha=0.4)
max_x = 12
max_y = 50
plt.annotate('Max', xy=(max_x, max_y), xytext=(max_x+2, max_y+2))

Solution

1. Step 1: Highlight the time period on x-axis

   plt.axvspan(10, 15, color='lightblue', alpha=0.4) correctly highlights between 10 and 15 seconds with transparency.

2. Step 2: Annotate the highest point with arrow

   Using plt.annotate with arrowprops=dict(facecolor='red') adds a red arrow pointing to (12, 50) with text offset at (13, 55).

3. Final Answer:

   plt.axvspan(10, 15, color='lightblue', alpha=0.4) max_x = 12 max_y = 50 plt.annotate('Max', xy=(max_x, max_y), xytext=(max_x+1, max_y+5), arrowprops=dict(facecolor='red')) -> Option A

4. Quick Check:

   axvspan for x-range, annotate with arrowprops dict [OK]

Hint: Use axvspan for x-range highlight and dict arrowprops for arrow [OK]

Common Mistakes:

• Using axhspan instead of axvspan for time range
• Passing arrowprops as string instead of dict
• Not setting alpha for transparency in highlight