Dual y-axis for different scales in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a plot with two y-axes using matplotlib.

Matplotlib

import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5]
y1 = [10, 20, 30, 40, 50]
y2 = [100, 200, 300, 400, 500]
fig, ax1 = plt.subplots()
ax2 = ax1.[1]()
ax1.plot(x, y1, 'g-')
ax2.plot(x, y2, 'b-')
plt.show()

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

Asubplots

Btwiny

Csubplot

Dtwinx

Attempts:

3 left

💡 Hint

Common Mistakes

Using twiny() creates a twin x-axis, not y-axis.

Using subplot() or subplots() creates new plots, not twin axes.

The method twinx() creates a second y-axis sharing the same x-axis.

2fill in blank

medium

Complete the code to set the y-axis label for the second y-axis.

Matplotlib

ax2.[1]('Second Y Axis')

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

Aset_ylabel

Bset_xlabel

Clabel

Dset_title

Attempts:

3 left

💡 Hint

Common Mistakes

Using set_xlabel() sets the x-axis label instead.

Using label or set_title() does not set axis labels.

set_ylabel() sets the label for the y-axis of the given axis object.

3fill in blank

hard

Fix the error in the code to correctly set the color of the second y-axis tick labels.

Matplotlib

ax2.tick_params(axis='y', [1]='b')

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

Alabelcolour

Bcolor

Clabelcolor

Dtickcolor

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'color' or 'tickcolor' causes no effect or errors.

Misspelling 'labelcolor' as 'labelcolour'.

The tick_params method uses 'labelcolor' to set the color of tick labels.

4fill in blank

hard

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

Matplotlib

words = ['data', 'science', 'is', 'fun']
lengths = {word: [1] for word in words if [2]

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

Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word > 3' compares strings to numbers, causing errors.

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

The dictionary comprehension maps each word to its length if the length is greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths if length is greater than 3.

Matplotlib

words = ['data', 'science', 'is', 'fun']
result = [1]: [2] for [3] in words if len([3]) > 3}}

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

Aword.upper()

Blen(word)

Cword

Dlen

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'len' as loop variable causes errors.

Not using upper() for keys.

Mismatching variable names in comprehension.

The comprehension maps uppercase words to their lengths, iterating over each word and filtering by length.

Practice

1. What is the main purpose of using a dual y-axis in a matplotlib plot?

easy

A. To compare two datasets with different scales on the same plot

B. To create two separate plots side by side

C. To add a legend to the plot

D. To change the color of the plot lines

Solution

1. Step 1: Understand the purpose of dual y-axis

   A dual y-axis allows plotting two datasets with different value ranges on the same graph for easy comparison.

2. Step 2: Identify the correct use case

   Comparing datasets with different scales requires two y-axes; other options do not describe this purpose.

3. Final Answer:

   To compare two datasets with different scales on the same plot -> Option A

4. Quick Check:

   Dual y-axis = compare different scales [OK]

Hint: Dual y-axis means two y-scales on one graph [OK]

Common Mistakes:

• Thinking dual y-axis creates two separate plots
• Confusing dual y-axis with adding legends
• Assuming it changes line colors only

2. Which matplotlib function is used to create a second y-axis sharing the same x-axis?

easy

A. plt.subplots()

B. ax.twiny()

C. ax.twinx()

D. plt.plot()

Solution

1. Step 1: Recall matplotlib methods for axes

   The method twinx() creates a second y-axis sharing the x-axis.

2. Step 2: Differentiate from similar methods

   twiny() creates a second x-axis, not y-axis; subplots() creates figure and axes; plot() draws lines.

3. Final Answer:

   ax.twinx() -> Option C

4. Quick Check:

   Second y-axis = twinx() [OK]

Hint: Use ax.twinx() for second y-axis, twiny() is for x-axis [OK]

Common Mistakes:

• Using plt.subplots() to create second y-axis
• Confusing twinx() with twiny()
• Trying to use plt.plot() to add axes

3. What will the following code output?

import matplotlib.pyplot as plt
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
ax1.plot([1, 2, 3], [10, 20, 30], 'g-')
ax2.plot([1, 2, 3], [100, 200, 300], 'b-')
print(len(fig.axes))

medium

A. 2

B. 1

C. 3

D. 4

Solution

1. Step 1: Understand axes creation

   plt.subplots() creates one axes (ax1), then ax1.twinx() adds a second y-axis (ax2), so total axes are 2.

2. Step 2: Check figure axes count

   fig.axes is a list of all axes in the figure; after adding ax2, length is 2.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Two axes after twinx() = 2 [OK]

Hint: twinx() adds one more axes, so total axes count increases by 1 [OK]

Common Mistakes:

• Assuming twinx() replaces the original axes
• Thinking twinx() adds multiple axes
• Confusing axes count with number of plots

4. Identify the error in this code snippet for creating dual y-axis:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax2 = plt.twinx()
ax.plot([1,2,3], [10,20,30])
ax2.plot([1,2,3], [100,200,300])
plt.show()

medium

A. plt.show() is missing

B. plt.subplots() should be plt.figure()

C. ax2.plot() should be ax.plot()

D. plt.twinx() should be ax.twinx()

Solution

1. Step 1: Check method usage for second y-axis

   twinx() is a method of an axes object, not plt module. So plt.twinx() is invalid.

2. Step 2: Correct method call

   Use ax.twinx() to create the second y-axis sharing the x-axis.

3. Final Answer:

   plt.twinx() should be ax.twinx() -> Option D

4. Quick Check:

   twinx() is an axes method, not plt function [OK]

Hint: twinx() must be called on axes object, not plt [OK]

Common Mistakes:

• Calling twinx() on plt instead of axes
• Confusing figure and axes creation methods
• Missing plt.show() (though present here)

5. You want to plot temperature (°C) and rainfall (mm) over months on the same plot with dual y-axes. Which of these code snippets correctly sets different y-axis labels and colors for clarity?

hard

A. ax1.set_xlabel('Temperature (°C)', color='red')\nax2.set_xlabel('Rainfall (mm)', color='blue')

B. ax1.set_ylabel('Temperature (°C)', color='red')\nax2.set_ylabel('Rainfall (mm)', color='blue')

C. ax1.set_ylabel('Rainfall (mm)', color='blue')\nax2.set_ylabel('Temperature (°C)', color='red')

D. ax1.set_title('Temperature and Rainfall')\nax2.set_title('Temperature and Rainfall')

Solution

1. Step 1: Assign correct y-axis labels

   Temperature and rainfall are y-axis data, so use set_ylabel() on each axis with matching labels.

2. Step 2: Use colors to distinguish axes

   Setting label colors helps visually separate the two y-axes for clarity.

3. Final Answer:

   ax1.set_ylabel('Temperature (°C)', color='red')\nax2.set_ylabel('Rainfall (mm)', color='blue') -> Option B

4. Quick Check:

   Correct y-labels and colors = ax1.set_ylabel('Temperature (°C)', color='red')\nax2.set_ylabel('Rainfall (mm)', color='blue') [OK]

Hint: Label y-axes with units and colors for clear dual-axis plots [OK]

Common Mistakes:

• Setting x-axis labels instead of y-axis
• Swapping labels between axes
• Using titles instead of axis labels