Inline display in Jupyter notebooks in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to enable inline plotting in a Jupyter notebook.

Matplotlib

%[1] matplotlib inline

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

Amatplotlib

Bmatplotlib.pyplot

Cmatplotlib_inline

Dmatplotlib_inline.backend_inline

Attempts:

3 left

💡 Hint

Common Mistakes

Using '%matplotlib.pyplot inline' which is invalid.

Forgetting the % sign before the command.

Using '%matplotlib_inline' which is not a valid magic command.

The magic command %matplotlib inline enables plots to be shown inside the notebook.

2fill in blank

medium

Complete the code to import the plotting library commonly used with inline display.

Matplotlib

import [1] as plt

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

Amatplotlib.pyplot

Bnumpy

Cpandas

Dseaborn

Attempts:

3 left

💡 Hint

Common Mistakes

Importing numpy instead of matplotlib.pyplot.

Importing pandas which is for data manipulation, not plotting.

Importing seaborn without matplotlib.pyplot.

matplotlib.pyplot is the module used for plotting in Python and is commonly imported as plt.

3fill in blank

hard

Fix the error in the code to display a simple plot inline.

Matplotlib

plt.plot([1, 2, 3], [4, 5, 6])
plt.[1]()

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

Aplot

Bdisplay

Cshow

Ddraw

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.display() which is not a valid function.

Using plt.plot() again instead of plt.show().

Using plt.draw() which is less common and may not display inline.

The plt.show() function displays the plot in the output cell.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps numbers to their squares and filters for squares greater than 10.

Matplotlib

{x: x[1]2 for x in range(1, 6) if x[2]2 > 10}

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

A**

B%

C*

D+

Attempts:

3 left

💡 Hint

Common Mistakes

Using '%' instead of '**' for power.

Using '+' instead of '*' in the condition.

Mixing up operators causing wrong filtering.

The operator ** is used for exponentiation (power), and * is multiplication. The condition checks if the square (x * 2) is greater than 10.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths, filtering words longer than 3 characters.

Matplotlib

{ [1]: [2] for word in words if len(word) [3] 3 }

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

Aword.upper()

Blen(word)

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word' instead of 'word.upper()' for keys.

Using '<' instead of '>' in the condition.

Using 'word' instead of 'len(word)' for values.

The dictionary keys are uppercase words (word.upper()), values are their lengths (len(word)), and the filter keeps words longer than 3 characters (> 3).

Practice

1. What does the command %matplotlib inline do in a Jupyter notebook?

easy

A. It displays matplotlib plots directly inside the notebook cells.

B. It saves matplotlib plots as image files on disk.

C. It disables matplotlib plotting in the notebook.

D. It opens matplotlib plots in a new external window.

Solution

1. Step 1: Understand the purpose of %matplotlib inline

   This magic command tells Jupyter to show plots inside the notebook cells instead of separate windows.

2. Step 2: Compare options with this behavior

   Only It displays matplotlib plots directly inside the notebook cells. matches this behavior; others describe saving, disabling, or external windows.

3. Final Answer:

   It displays matplotlib plots directly inside the notebook cells. -> Option A

4. Quick Check:

   Inline plotting = display inside notebook [OK]

Hint: Inline means plots show inside notebook cells [OK]

Common Mistakes:

• Thinking it saves plots to files
• Confusing inline with external window display
• Believing it disables plotting

2. Which of the following is the correct way to enable inline plotting in a Jupyter notebook?

easy

A. %matplotlib inline

B. matplotlib.inline()

C. plt.inline()

D. import matplotlib inline

Solution

1. Step 1: Recall the magic command syntax

   The correct syntax to enable inline plotting is the magic command starting with % followed by matplotlib inline.

2. Step 2: Check each option

   Only %matplotlib inline uses the correct magic command syntax. Others are invalid Python or matplotlib syntax.

3. Final Answer:

   %matplotlib inline -> Option A

4. Quick Check:

   Magic command starts with % [OK]

Hint: Magic commands start with % in Jupyter [OK]

Common Mistakes:

• Trying to call inline as a function
• Using import incorrectly
• Missing the % sign

3. What will be the output when running this code in a Jupyter notebook without any magic command?

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.show()

medium

A. The plot will display inside the notebook cell.

B. No plot will display and no error occurs.

C. The plot will open in a separate window.

D. A syntax error will occur.

Solution

1. Step 1: Understand default matplotlib behavior without inline

   Without %matplotlib inline, matplotlib opens plots in external windows by default.

2. Step 2: Analyze the code behavior

   The code calls plt.show(), which triggers the plot window to open externally.

3. Final Answer:

   The plot will open in a separate window. -> Option C

4. Quick Check:

   No inline command = external window [OK]

Hint: No %matplotlib inline means external window [OK]

Common Mistakes:

• Assuming plot shows inside notebook by default
• Expecting syntax errors
• Thinking no plot appears

4. You run %matplotlib inline in a Jupyter notebook but your plots still do not show inside the notebook. What is the most likely cause?

medium

A. You forgot to import matplotlib.pyplot as plt.

B. Your notebook does not support inline plotting.

C. You used plt.show() which disables inline plots.

D. You ran the magic command after plotting the graphs.

Solution

1. Step 1: Understand when to run %matplotlib inline

   The magic command must be run before any plotting commands to enable inline display.

2. Step 2: Analyze the options

   You ran the magic command after plotting the graphs. correctly identifies that running the magic after plotting will not show plots inline. Other options are less likely or incorrect.

3. Final Answer:

   You ran the magic command after plotting the graphs. -> Option D

4. Quick Check:

   Run magic before plotting [OK]

Hint: Run %matplotlib inline before plotting [OK]

Common Mistakes:

• Running magic after plotting
• Thinking plt.show() disables inline
• Assuming import affects inline display

5. You want to create multiple plots in a Jupyter notebook cell and have them all display inline one after another. Which approach will work best?

hard

A. Run %matplotlib inline and call plt.show() after each plot.

B. Run %matplotlib inline before plotting, then create all plots without calling plt.show().

C. Run %matplotlib inline and call plt.show() only after the last plot.

D. Run %matplotlib inline once, then call plt.show() after each plot.

Solution

1. Step 1: Understand inline plotting with multiple plots

   With %matplotlib inline, plots are automatically rendered and displayed inline at the end of the cell without needing plt.show().

2. Step 2: Evaluate options for correct usage

   Run %matplotlib inline before plotting, then create all plots without calling plt.show(). is the standard best practice as plt.show() is unnecessary in inline mode.

3. Final Answer:

   Run %matplotlib inline before plotting, then create all plots without calling plt.show(). -> Option B

4. Quick Check:

   No plt.show() needed in inline mode [OK]

Hint: No plt.show() needed with %matplotlib inline [OK]

Common Mistakes:

• Calling plt.show() after each plot (unnecessary)
• Calling plt.show() only after the last plot
• Thinking plt.show() is required for inline