Secondary axes in Matplotlib - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a secondary axis in matplotlib?

A secondary axis is an additional axis on the same plot that allows you to show a different scale or units for the same data or related data. It helps compare two different measurements on one graph.

beginner

How do you create a secondary y-axis in matplotlib?

You can create a secondary y-axis by calling ax.secondary_yaxis() on an existing axis object. You provide a function to convert between the primary and secondary axis scales.

intermediate

What is the purpose of the functions passed to secondary_xaxis or secondary_yaxis?

These functions convert values from the primary axis scale to the secondary axis scale and back. They ensure the secondary axis shows correct corresponding values.

intermediate

Can you add a secondary x-axis and y-axis on the same plot in matplotlib?

Yes, matplotlib allows adding both a secondary x-axis and a secondary y-axis on the same plot to show different scales or units for both horizontal and vertical directions.

beginner

What is a practical example of using a secondary axis?

A practical example is plotting temperature in Celsius on the primary y-axis and Fahrenheit on the secondary y-axis, so viewers can see both units on the same graph.

Which matplotlib method adds a secondary y-axis to an existing axis?

A new_yaxis()

B add_secondary_axis()

C create_secondary_axis()

D secondary_yaxis()

The correct method is secondary_yaxis() which adds a secondary y-axis to an existing axis.

What do the functions passed to secondary_xaxis or secondary_yaxis do?

A Set the axis label font size

B Change the color of the axis

C Convert values between primary and secondary axis scales

D Add grid lines to the plot

These functions convert values between the primary and secondary axis scales to keep the axes aligned correctly.

Can you have both a secondary x-axis and y-axis on the same matplotlib plot?

A Yes

B No

C Only if using subplots

D Only with special plugins

Matplotlib supports adding both secondary x-axis and y-axis on the same plot.

Why would you use a secondary axis in a plot?

A To add a legend

B To show different units or scales for the same data

C To change the plot background color

D To zoom into a section of the plot

Secondary axes help show different units or scales for the same or related data on one plot.

Which of these is a good example of using a secondary axis?

A Plotting temperature in Celsius and Fahrenheit on the same graph

B Changing the line style of a plot

C Adding a title to the plot

D Plotting two unrelated datasets on separate plots

Showing temperature in Celsius and Fahrenheit on the same graph is a classic use of a secondary axis.

Explain how to add a secondary y-axis in matplotlib and why you might want to use it.

Think about showing two measurements like Celsius and Fahrenheit on one graph.

Describe the role of the conversion functions used with secondary axes in matplotlib.

These functions translate values from one axis scale to the other.

Practice

1. What is the main purpose of using secondary_xaxis or secondary_yaxis in matplotlib?

easy

A. To add a new axis with a different scale on the same plot

B. To create a separate figure window

C. To change the color of the existing axis

D. To remove the original axis from the plot

Solution

1. Step 1: Understand the concept of secondary axes

   Secondary axes allow adding a new axis that shares the same plot but has a different scale or units.

2. Step 2: Identify the purpose of secondary_xaxis or secondary_yaxis

   These functions add a secondary axis to the existing plot to compare data with different units clearly.

3. Final Answer:

   To add a new axis with a different scale on the same plot -> Option A

4. Quick Check:

   Secondary axes = different scale on same plot [OK]

Hint: Secondary axes add a new scale on the same plot [OK]

Common Mistakes:

• Thinking it creates a new figure
• Confusing axis color change with adding axes
• Assuming it removes original axes

2. Which of the following is the correct way to add a secondary y-axis in matplotlib?

easy

A. ax.add_secondary_yaxis('right', functions=(forward, inverse))

B. ax.add_secondary_axis('right', functions=(forward, inverse))

C. ax.secondary_yaxis('right', functions=(forward, inverse))

D. ax.secondary_axis('right', functions=(forward, inverse))

Solution

1. Step 1: Recall the matplotlib method for secondary y-axis

   The correct method is secondary_yaxis called on the axes object.

2. Step 2: Match the exact syntax

   The method is ax.secondary_yaxis('right', functions=(forward, inverse)) where 'right' is the position and functions are conversion functions.

3. Final Answer:

   ax.secondary_yaxis('right', functions=(forward, inverse)) -> Option C

4. Quick Check:

   Correct method name = secondary_yaxis [OK]

Hint: Use ax.secondary_yaxis with conversion functions [OK]

Common Mistakes:

• Using incorrect method names like add_secondary_axis
• Missing the functions parameter
• Using secondary_axis instead of secondary_yaxis

3. What will be the output of this code snippet?

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([0, 1, 2], [0, 10, 20])

forward = lambda x: x / 10
inverse = lambda x: x * 10
secax = ax.secondary_yaxis('right', functions=(forward, inverse))
print(secax.get_ylim())

medium

A. [0.0, 2.0]

B. [0, 20]

C. [0.0, 200.0]

D. [0, 10]

Solution

1. Step 1: Understand the original y-axis limits

   The original y-axis data ranges from 0 to 20, so default limits are approximately (0, 20).

2. Step 2: Apply the forward function to original limits for secondary axis

   The forward function divides by 10, so 0 becomes 0.0 and 20 becomes 2.0 on the secondary axis.

3. Final Answer:

   [0.0, 2.0] -> Option A

4. Quick Check:

   Secondary axis limits = original limits / 10 [OK]

Hint: Secondary axis limits = apply forward function to original limits [OK]

Common Mistakes:

• Confusing forward and inverse functions
• Expecting original limits instead of transformed
• Assuming inverse function applies to limits

4. Identify the error in this code that tries to add a secondary x-axis:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([0, 1, 2], [0, 1, 4])

forward = lambda x: x * 2
inverse = lambda x: x / 2
secax = ax.secondary_xaxis('top', functions=(inverse, forward))

medium

A. The lambda functions should not be used

B. The order of functions in the tuple is reversed

C. The position 'top' is invalid for secondary_xaxis

D. The method name should be secondary_yaxis instead

Solution

1. Step 1: Check the order of conversion functions

   The first function should convert from primary to secondary axis (forward), the second from secondary to primary (inverse).

2. Step 2: Identify the mistake in the code

   The code uses (inverse, forward) instead of (forward, inverse), so the order is reversed causing incorrect scaling.

3. Final Answer:

   The order of functions in the tuple is reversed -> Option B

4. Quick Check:

   Functions order = (forward, inverse) [OK]

Hint: First function forward, second inverse in tuple [OK]

Common Mistakes:

• Swapping forward and inverse functions
• Using invalid axis position
• Confusing secondary_xaxis with secondary_yaxis

5. You have temperature data in Celsius and want to add a secondary y-axis in Fahrenheit on the right side. Which of these code snippets correctly creates the secondary axis with proper conversion?

hard

A. forward = lambda f: (f - 32) * 5/9
inverse = lambda c: (c * 9/5) + 32
ax.secondary_yaxis('right', functions=(inverse, forward))

B. forward = lambda c: (c * 5/9) + 32
inverse = lambda f: (f - 32) * 9/5
ax.secondary_yaxis('right', functions=(forward, inverse))

C. forward = lambda c: (c - 32) * 5/9
inverse = lambda f: (f * 9/5) + 32
ax.secondary_yaxis('left', functions=(forward, inverse))

D. forward = lambda c: (c * 9/5) + 32
inverse = lambda f: (f - 32) * 5/9
ax.secondary_yaxis('right', functions=(forward, inverse))

Solution

1. Step 1: Recall Celsius to Fahrenheit conversion formulas

   Celsius to Fahrenheit: F = (C * 9/5) + 32; Fahrenheit to Celsius: C = (F - 32) * 5/9.

2. Step 2: Match the forward and inverse functions correctly

   Forward converts primary (C) to secondary (F), inverse converts secondary (F) back to primary (C). Position 'right' is correct for secondary y-axis.

3. Final Answer:

   forward = lambda c: (c * 9/5) + 32 inverse = lambda f: (f - 32) * 5/9 ax.secondary_yaxis('right', functions=(forward, inverse)) -> Option D

4. Quick Check:

   Correct conversion and axis position = forward = lambda c: (c * 9/5) + 32 inverse = lambda f: (f - 32) * 5/9 ax.secondary_yaxis('right', functions=(forward, inverse)) [OK]

Hint: Forward: C to F; Inverse: F to C; position 'right' for y-axis [OK]

Common Mistakes:

• Swapping forward and inverse functions
• Using wrong conversion formulas
• Placing secondary axis on 'left' instead of 'right'