Dashboard layout patterns in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a figure with a grid layout of 2 rows and 2 columns.

Matplotlib

fig, axs = plt.subplots([1], 2)

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

A2

B4

C3

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using 1 row instead of 2.

Confusing rows and columns.

Using plt.subplots(2, 2) creates a 2x2 grid layout for the dashboard.

2fill in blank

medium

Complete the code to set the figure size to 10 inches wide and 8 inches tall.

Matplotlib

fig, axs = plt.subplots(2, 2, figsize=([1], 8))

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

A12

B8

C10

D6

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping width and height values.

Using too small or too large numbers.

The figsize parameter takes width and height in inches. Here, width is 10.

3fill in blank

hard

Fix the error in the code to add a title to the first subplot.

Matplotlib

axs[0, 0].[1]('Sales Over Time')

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

Atitle

Bset_title

Cadd_title

Dplot_title

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'title' instead of 'set_title'.

Trying to use non-existent methods like 'add_title'.

Use set_title method to set the title of a subplot in matplotlib.

4fill in blank

hard

Fill both blanks to adjust spacing between subplots and add a main title to the figure.

Matplotlib

fig.[1](hspace=0.5)
fig.[2]('Dashboard Overview')

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

Asubplots_adjust

Bsuptitle

Cset_title

Dtight_layout

Attempts:

3 left

💡 Hint

Common Mistakes

Using set_title on the figure instead of suptitle.

Trying to adjust spacing with tight_layout without parameters.

subplots_adjust changes spacing between subplots. suptitle adds a main title to the figure.

5fill in blank

hard

Fill all three blanks to create a 3-row, 1-column layout, set figure size, and add a title to the last subplot.

Matplotlib

fig, axs = plt.subplots([1], [2], figsize=([3], 12))
axs[2].set_title('Profit Analysis')

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

A3

B1

C10

D2

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping rows and columns values.

Using wrong figure size dimensions.

We want 3 rows and 1 column, so plt.subplots(3, 1). The figure width is set to 10 inches.

Practice

1. What is the main purpose of using dashboard layout patterns in matplotlib?

easy

A. To organize multiple charts clearly for easy understanding

B. To change the color of charts automatically

C. To add animations to charts

D. To export charts as PDF files

Solution

1. Step 1: Understand dashboard layout purpose

   Dashboard layouts help arrange multiple charts so viewers can understand data easily.

2. Step 2: Identify the correct purpose in options

   Only To organize multiple charts clearly for easy understanding mentions organizing charts clearly, which matches the purpose.

3. Final Answer:

   To organize multiple charts clearly for easy understanding -> Option A

4. Quick Check:

   Dashboard layout = organize charts clearly [OK]

Hint: Dashboards arrange charts clearly for easy reading [OK]

Common Mistakes:

• Confusing layout with color or animation features
• Thinking layout changes export formats
• Assuming layout adds interactivity automatically

2. Which of the following is the correct way to create a 2x2 grid of charts using matplotlib?

easy

A. plt.figure(2, 2)

B. plt.grid(2, 2)

C. plt.subplots(2, 2)

D. plt.plot(2, 2)

Solution

1. Step 1: Recall the function for grid layout

   plt.subplots() creates a grid of subplots; parameters define rows and columns.

2. Step 2: Match correct syntax

   plt.subplots(2, 2) creates a 2 by 2 grid; other options do not create grids.

3. Final Answer:

   plt.subplots(2, 2) -> Option C

4. Quick Check:

   Grid layout = plt.subplots(rows, cols) [OK]

Hint: Use plt.subplots(rows, cols) for grid layouts [OK]

Common Mistakes:

• Using plt.grid() which controls gridlines, not layout
• Confusing plt.figure() with subplot grid creation
• Using plt.plot() which draws single charts only

3. What will be the output layout when running this code?

fig, axs = plt.subplots(1, 3)
for ax in axs:
    ax.plot([1, 2, 3], [1, 4, 9])
plt.tight_layout()
plt.show()

medium

A. Three rows with one chart each stacked vertically

B. A single row with three side-by-side line charts

C. One chart only with three lines overlapping

D. An error because plt.tight_layout() is missing parameters

Solution

1. Step 1: Analyze plt.subplots(1, 3)

   This creates 1 row and 3 columns, so three charts side by side.

2. Step 2: Understand the loop plotting

   Each axis plots the same line chart, so three separate charts appear horizontally.

3. Final Answer:

   A single row with three side-by-side line charts -> Option B

4. Quick Check:

   1 row, 3 cols = 3 charts side by side [OK]

Hint: Rows x cols in plt.subplots defines chart grid shape [OK]

Common Mistakes:

• Thinking 1,3 means 3 rows stacked vertically
• Assuming all lines plot on one chart
• Believing plt.tight_layout() causes errors without args

4. Identify the error in this code snippet for creating a 2x2 dashboard layout:

fig, axs = plt.subplots(2, 2)
axs.plot([1, 2, 3], [3, 2, 1])
plt.show()

medium

A. plt.subplots() cannot create 2x2 grids

B. The plot data lists have different lengths

C. plt.show() is missing parentheses

D. axs is an array; calling axs.plot() causes an error

Solution

1. Step 1: Understand axs type from plt.subplots(2, 2)

   axs is a 2x2 array of axes, not a single axis object.

2. Step 2: Identify incorrect method call

   Calling axs.plot() tries to call plot on the array, which causes an error; must call plot on individual axes.

3. Final Answer:

   axs is an array; calling axs.plot() causes an error -> Option D

4. Quick Check:

   Array of axes needs individual plot calls [OK]

Hint: Call plot on each axis, not on the axes array [OK]

Common Mistakes:

• Calling plot on the whole axs array instead of elements
• Thinking plt.subplots can't create 2x2 grids
• Forgetting plt.show() needs parentheses

5. You want to create a dashboard with 3 charts: one large chart on the left and two smaller stacked charts on the right. Which matplotlib layout pattern best fits this requirement?

hard

A. Use GridSpec to create a 2-column layout with different row spans

B. Use plt.subplots(3, 1) for three stacked charts vertically

C. Use plt.subplots(1, 3) for three charts side by side equally sized

D. Use plt.subplot() three times with default sizes

Solution

1. Step 1: Understand layout needs

   One large chart on left and two smaller stacked on right means uneven grid with row spans.

2. Step 2: Identify suitable layout tool

   GridSpec allows flexible grid with different row/column spans, perfect for this layout.

3. Step 3: Eliminate other options

   plt.subplots(3,1) stacks vertically; plt.subplots(1,3) makes equal columns; plt.subplot() default sizes lack control.

4. Final Answer:

   Use GridSpec to create a 2-column layout with different row spans -> Option A

5. Quick Check:

   Complex layouts need GridSpec flexibility [OK]

Hint: Use GridSpec for uneven dashboard layouts [OK]

Common Mistakes:

• Using plt.subplots with equal-sized grids only
• Stacking all charts vertically when layout differs
• Using plt.subplot() without size control