Storytelling with visualization sequence in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib library for plotting.

Matplotlib

import [1] as plt

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

Amatplotlib.pyplot

Bmatplotlib

Cmpl

Dpyplot

Attempts:

3 left

💡 Hint

Common Mistakes

Importing just 'matplotlib' does not give direct access to plotting functions.

Using 'pyplot' without 'matplotlib.' prefix causes an error.

We import matplotlib.pyplot as plt to use plotting functions easily.

2fill in blank

medium

Complete the code to create a line plot of x and y data.

Matplotlib

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

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

Abar

Bplot

Cscatter

Dhist

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'scatter' creates points without connecting lines.

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

The plot function creates a line plot connecting points.

3fill in blank

hard

Fix the error in the code to add a title to the plot.

Matplotlib

plt.title([1])

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

AStory of Sales"

BStory of Sales

C'Story of Sales

D"Story of Sales"

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting quotes causes a NameError.

Using mismatched quotes causes syntax errors.

The title text must be a string enclosed in quotes.

4fill in blank

hard

Fill both blanks to create a bar chart with labels and show the plot.

Matplotlib

plt.[1](categories, values)
plt.[2]()

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

Abar

Bshow

Cplot

Dtitle

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'plot' instead of 'bar' creates a line plot.

Forgetting 'show' means the plot won't appear.

Use bar to create a bar chart and show to display it.

5fill in blank

hard

Fill all three blanks to create a scatter plot with labels and a title.

Matplotlib

plt.[1](x, y)
plt.xlabel([2])
plt.title([3])
plt.show()

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

Ascatter

B"Time (days)"

C"Growth over Time"

Dplot

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'plot' instead of 'scatter' changes the plot type.

Forgetting quotes around labels causes errors.

Use scatter for scatter plot, label x-axis with xlabel, and add a title with title.

Practice

1. What is the main purpose of using multiple plots in a storytelling visualization sequence?

easy

A. To make the plot colors more vibrant

B. To reduce the size of the data

C. To break data into parts and explain it step-by-step

D. To avoid using titles and labels

Solution

1. Step 1: Understand storytelling with visualization

   Storytelling with visualization means showing data in parts to explain it clearly.

2. Step 2: Purpose of multiple plots

   Using multiple plots helps break the data into smaller pieces to tell a clear story step-by-step.

3. Final Answer:

   To break data into parts and explain it step-by-step -> Option C

4. Quick Check:

   Storytelling = breaking data into parts [OK]

Hint: Multiple plots show data in steps for clear explanation [OK]

Common Mistakes:

• Thinking colors are the main reason for multiple plots
• Believing multiple plots reduce data size
• Ignoring the importance of titles and labels

2. Which of the following is the correct way to create two plots side by side using matplotlib?

easy

A. plt.subplot(2, 1, 1) and plt.subplot(2, 1, 3)

B. plt.subplot(1, 2, 1) and plt.subplot(1, 2, 2)

C. plt.subplot(1, 1, 1) and plt.subplot(1, 1, 2)

D. plt.subplot(3, 1, 1) and plt.subplot(3, 1, 2)

Solution

1. Step 1: Understand plt.subplot parameters

   plt.subplot(rows, columns, plot_number) arranges plots in a grid.

2. Step 2: Create two side-by-side plots

   One row and two columns means plt.subplot(1, 2, 1) and plt.subplot(1, 2, 2) for two plots side by side.

3. Final Answer:

   plt.subplot(1, 2, 1) and plt.subplot(1, 2, 2) -> Option B

4. Quick Check:

   One row, two columns = plt.subplot(1, 2, x) [OK]

Hint: Use plt.subplot(1, 2, x) for two side-by-side plots [OK]

Common Mistakes:

• Using wrong plot numbers like 3 in a 2-plot layout
• Mixing rows and columns incorrectly
• Trying to create more plots than grid allows

3. What will be the output arrangement of the following code?

import matplotlib.pyplot as plt
plt.subplot(2, 1, 1)
plt.title('Top Plot')
plt.subplot(2, 1, 2)
plt.title('Bottom Plot')
plt.show()

medium

A. Error because plt.title() is used twice

B. Two plots side by side with titles 'Top Plot' and 'Bottom Plot'

C. One plot with both titles overlapping

D. Two plots stacked vertically with titles 'Top Plot' and 'Bottom Plot'

Solution

1. Step 1: Understand plt.subplot(2, 1, x)

   This creates 2 rows and 1 column, stacking plots vertically.

2. Step 2: Titles assigned to each subplot

   First plot gets 'Top Plot', second gets 'Bottom Plot', shown stacked vertically.

3. Final Answer:

   Two plots stacked vertically with titles 'Top Plot' and 'Bottom Plot' -> Option D

4. Quick Check:

   2 rows, 1 column = vertical stack [OK]

Hint: Rows first, columns second in plt.subplot for layout [OK]

Common Mistakes:

• Thinking plots are side by side with (2,1,x)
• Assuming plt.title() causes error if used twice
• Expecting one plot instead of two

4. Identify the error in this code that tries to create a 2x2 grid of plots:

import matplotlib.pyplot as plt
plt.subplot(2, 2, 1)
plt.plot([1,2,3])
plt.subplot(2, 2, 5)
plt.plot([3,2,1])
plt.show()

medium

A. Using subplot number 5 in a 2x2 grid causes an error

B. plt.plot() cannot be used inside subplot

C. Missing plt.figure() before subplots

D. No error, code runs fine

Solution

1. Step 1: Understand subplot numbering in 2x2 grid

   2 rows and 2 columns means subplot numbers 1 to 4 only.

2. Step 2: Check subplot number 5 usage

   Using subplot(2, 2, 5) is invalid and causes an error.

3. Final Answer:

   Using subplot number 5 in a 2x2 grid causes an error -> Option A

4. Quick Check:

   Max subplot number = rows*columns = 4 [OK]

Hint: Subplot number must be ≤ rowsxcolumns [OK]

Common Mistakes:

• Thinking plt.plot() can't be inside subplot
• Believing plt.figure() is mandatory before subplots
• Ignoring subplot numbering limits

5. You want to tell a story showing sales growth over 3 years with separate plots for each year. Which approach best helps your audience understand the story clearly?

hard

A. Create 3 subplots in one column using plt.subplot(3, 1, x) with clear titles and labels

B. Plot all years on one plot without labels

C. Create 1 subplot and plot only the last year's data

D. Use plt.subplot(1, 3, x) but skip titles and labels

Solution

1. Step 1: Choose subplot layout for storytelling

   Using 3 rows and 1 column (plt.subplot(3, 1, x)) stacks plots vertically, showing each year clearly.

2. Step 2: Importance of titles and labels

   Clear titles and labels help the audience understand each year's data easily.

3. Final Answer:

   Create 3 subplots in one column using plt.subplot(3, 1, x) with clear titles and labels -> Option A

4. Quick Check:

   Separate plots + clear labels = better storytelling [OK]

Hint: Stack plots vertically with titles for clear story [OK]

Common Mistakes:

• Plotting all data in one plot without labels
• Skipping titles and labels reduces clarity
• Showing only last year's data misses story