Why axis formatting matters in Matplotlib - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to set the x-axis label in a matplotlib plot.

Matplotlib

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

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

A'X Axis'

Bxlabel

CX Axis

Dplt.xlabel

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to put the label text inside quotes.

Passing a variable name without defining it.

The xlabel function requires a string argument to label the x-axis. So, the label must be in quotes.

2fill in blank

medium

Complete the code to set the y-axis limits from 0 to 10.

Matplotlib

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

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

A(0, 10)

B[0, 10]

C0, 10

D{0:10}

Attempts:

3 left

💡 Hint

Common Mistakes

Using a list instead of a tuple.

Passing two separate arguments instead of a tuple.

The ylim function expects a tuple with two values for the limits.

3fill in blank

hard

Fix the error in the code to correctly format the x-axis ticks as percentages.

Matplotlib

import matplotlib.pyplot as plt
import matplotlib.ticker as mtick

fig, ax = plt.subplots()
ax.plot([0.1, 0.2, 0.3], [1, 2, 3])
ax.xaxis.set_major_formatter([1](xmax=1))
plt.show()

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

Amtick.FuncFormatter

Bmtick.FormatStrFormatter

Cmtick.PercentFormatter

Dmtick.PercentFormatter()

Attempts:

3 left

💡 Hint

Common Mistakes

Calling PercentFormatter with parentheses before passing it.

Using the wrong formatter class.

PercentFormatter is a class and should be instantiated with xmax=1 to correctly format values between 0 and 1 as percentages.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if the length is greater than 3.

Matplotlib

words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: [1] for word in words if [2]
plt.plot(list(lengths.values()))
plt.show()

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself instead of its length.

Checking if the word is greater than 3 instead of its length.

The dictionary comprehension maps each word to its length (len(word)) only if the length is greater than 3 (len(word) > 3).

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths only if the length is less than 6.

Matplotlib

words = ['apple', 'bat', 'carrot', 'dog']
result = { [1]: [2] for w in words if [3] }
plt.bar(result.keys(), result.values())
plt.show()

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

Aw.upper()

Blen(w)

Clen(w) < 6

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() instead of w.upper().

Checking length greater than 6 instead of less than 6.

The comprehension maps uppercase words (w.upper()) to their lengths (len(w)) only if the length is less than 6 (len(w) < 6).

Practice

1. Why is axis formatting important when creating charts with matplotlib?

easy

A. It adds animation effects to the chart.

B. It changes the color of the chart background.

C. It automatically saves the chart to a file.

D. It helps make the chart easier to understand by labeling and scaling axes properly.

Solution

1. Step 1: Understand the role of axis formatting

   Axis formatting controls labels, ticks, and limits on the axes, which helps viewers read the chart easily.

2. Step 2: Identify the effect on chart clarity

   Proper axis formatting makes the data story clear by showing correct scales and labels.

3. Final Answer:

   It helps make the chart easier to understand by labeling and scaling axes properly. -> Option D

4. Quick Check:

   Axis formatting = clarity [OK]

Hint: Axis formatting improves chart clarity and understanding [OK]

Common Mistakes:

• Confusing axis formatting with chart colors
• Thinking axis formatting adds animations
• Assuming axis formatting saves files automatically

2. Which of the following matplotlib commands correctly sets the x-axis label to 'Time (s)'?

easy

A. plt.xaxis.label('Time (s)')

B. plt.set_xlabel('Time (s)')

C. plt.xlabel('Time (s)')

D. plt.label_x('Time (s)')

Solution

1. Step 1: Recall the correct function for x-axis label

   The function to set the x-axis label in matplotlib is plt.xlabel().

2. Step 2: Check the options for syntax correctness

   Only plt.xlabel('Time (s)') matches the correct syntax.

3. Final Answer:

   plt.xlabel('Time (s)') -> Option C

4. Quick Check:

   Use plt.xlabel() to label x-axis [OK]

Hint: Use plt.xlabel() to set x-axis label [OK]

Common Mistakes:

• Using incorrect function names like plt.set_xlabel
• Trying to access label as an attribute
• Mixing up axis label functions

3. What will be the effect of this code on the x-axis ticks?

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.xticks([1, 2, 3], ['One', 'Two', 'Three'])
plt.show()

medium

A. The x-axis ticks will be replaced by labels 'One', 'Two', 'Three'.

B. The x-axis ticks will show numbers 1, 2, 3 as labels.

C. The x-axis ticks will be hidden.

D. The code will cause an error because of wrong syntax.

Solution

1. Step 1: Understand plt.xticks() usage

   The function plt.xticks() sets the positions and labels of x-axis ticks.

2. Step 2: Analyze the given arguments

   Positions are [1, 2, 3] and labels are ['One', 'Two', 'Three'], so ticks at 1, 2, 3 will show these labels.

3. Final Answer:

   The x-axis ticks will be replaced by labels 'One', 'Two', 'Three'. -> Option A

4. Quick Check:

   plt.xticks(pos, labels) changes tick labels [OK]

Hint: plt.xticks(pos, labels) sets custom tick labels [OK]

Common Mistakes:

• Thinking ticks remain numeric after plt.xticks with labels
• Assuming ticks get hidden without plt.xticks([])
• Believing code causes syntax error

4. Identify the error in this code that tries to set y-axis limits:

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.ylim = (0, 10)
plt.show()

medium

A. The plot data is invalid and causes an error.

B. The code uses assignment instead of calling plt.ylim() function.

C. plt.show() is missing and causes no output.

D. There is no error; the code runs correctly.

Solution

1. Step 1: Check how y-axis limits are set

   In matplotlib, plt.ylim() is a function to set y-axis limits, not an attribute to assign.

2. Step 2: Identify the mistake in code

   The code uses plt.ylim = (0, 10) which assigns a tuple instead of calling the function plt.ylim(0, 10).

3. Final Answer:

   The code uses assignment instead of calling plt.ylim() function. -> Option B

4. Quick Check:

   Use plt.ylim() function, not assignment [OK]

Hint: Use plt.ylim() as a function, not assignment [OK]

Common Mistakes:

• Assigning tuple to plt.ylim instead of calling it
• Forgetting plt.show() to display plot
• Confusing data errors with axis formatting errors

5. You want to create a plot where the x-axis shows dates but only every Monday is labeled to avoid clutter. Which approach best formats the axis in matplotlib?

hard

A. Use matplotlib.dates.WeekdayLocator to set ticks on Mondays and format labels with DateFormatter.

B. Rotate all date labels by 90 degrees without changing ticks.

C. Manually set x-axis limits to only show Mondays.

D. Use plt.xticks() with all dates as labels.

Solution

1. Step 1: Understand the problem of cluttered date labels

   Showing all dates can clutter the axis; selecting specific days like Mondays reduces clutter.

2. Step 2: Identify matplotlib tools for date axis formatting

   WeekdayLocator can set ticks on specific weekdays, and DateFormatter formats the tick labels nicely.

3. Step 3: Evaluate options

   The approach using matplotlib.dates.WeekdayLocator to set ticks on Mondays and format labels with DateFormatter correctly reduces clutter; others either show all dates, only rotate labels without reducing ticks, or limit the axis range.

4. Final Answer:

   Use matplotlib.dates.WeekdayLocator to set ticks on Mondays and format labels with DateFormatter. -> Option A

5. Quick Check:

   Use WeekdayLocator + DateFormatter for clean date axes [OK]

Hint: Use WeekdayLocator and DateFormatter for selective date ticks [OK]

Common Mistakes:

• Labeling all dates causing clutter
• Only rotating labels without reducing ticks
• Trying to limit axis range instead of ticks