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Matplotlibdata~5 mins

Fig, ax = plt.subplots pattern in Matplotlib

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Introduction

This pattern helps you create a figure and one or more plots (axes) in a clear and organized way.

When you want to draw one or more charts in a single window.
When you need to control the size or layout of your plots.
When you want to customize each plot separately.
When you want to save or show the whole figure with all plots.
When you want to add titles, labels, or legends to your plots.
Syntax
Matplotlib
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(width, height))

fig is the whole figure or window that holds your plots.

ax is the plot area where you draw your data.

Examples
Create one plot with default size.
Matplotlib
fig, ax = plt.subplots()
Create one plot with width 8 inches and height 6 inches.
Matplotlib
fig, ax = plt.subplots(figsize=(8, 6))
Create a 2 by 2 grid of plots. axs is a 2D array of axes.
Matplotlib
fig, axs = plt.subplots(2, 2)
Create 3 plots stacked vertically with a tall figure size.
Matplotlib
fig, ax = plt.subplots(nrows=3, ncols=1, figsize=(5, 10))
Sample Program

This code creates a figure with one plot. It draws a line connecting points (1,4), (2,5), and (3,6). Then it adds a title and labels for the axes. Finally, it shows the plot window.

Matplotlib
import matplotlib.pyplot as plt

# Create a figure and one plot
fig, ax = plt.subplots(figsize=(6, 4))

# Draw a simple line
ax.plot([1, 2, 3], [4, 5, 6])

# Add title and labels
ax.set_title('Simple Line Plot')
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')

# Show the plot
plt.show()
OutputSuccess
Important Notes

If you create multiple plots, ax becomes an array or matrix of axes objects.

You can use fig to adjust the whole figure, like saving it or changing layout.

Always call plt.show() to display your plots when running scripts.

Summary

The fig, ax = plt.subplots() pattern creates a figure and plot(s) together.

fig is the container; ax is where you draw your data.

This pattern helps organize and customize your charts easily.

Practice

(1/5)
1. What does the variable fig represent when you write fig, ax = plt.subplots() in matplotlib?
easy
A. The specific plot area where data is drawn
B. The whole figure container that holds all plot elements
C. A list of all plots in the figure
D. The title of the plot

Solution

  1. Step 1: Understand the role of fig in plt.subplots()

    The fig variable holds the entire figure container, which can include multiple plots, titles, legends, and other elements.
  2. Step 2: Differentiate fig from ax

    The ax variable is the specific plot area inside the figure where data is drawn, not the whole container.
  3. Final Answer:

    The whole figure container that holds all plot elements -> Option B
  4. Quick Check:

    fig = whole figure container [OK]
Hint: Remember: fig = full figure, ax = plot area [OK]
Common Mistakes:
  • Confusing fig with ax as the plot area
  • Thinking fig is just the plot title
  • Assuming fig is a list of plots
2. Which of the following is the correct syntax to create a figure and axes using matplotlib's plt.subplots()?
easy
A. plt.subplots = fig, ax
B. fig = plt.subplots(ax)
C. ax, fig = plt.subplots()
D. fig, ax = plt.subplots()

Solution

  1. Step 1: Recall the correct unpacking syntax

    The function plt.subplots() returns two objects: the figure and the axes. The correct way to capture them is fig, ax = plt.subplots().
  2. Step 2: Check each option for syntax correctness

    fig = plt.subplots(ax) tries to pass ax as an argument incorrectly. ax, fig = plt.subplots() reverses the order, which is wrong. plt.subplots = fig, ax tries to assign incorrectly.
  3. Final Answer:

    fig, ax = plt.subplots() -> Option D
  4. Quick Check:

    Correct unpacking = fig, ax = plt.subplots() [OK]
Hint: Remember: fig first, then ax from plt.subplots() [OK]
Common Mistakes:
  • Swapping fig and ax order
  • Passing ax as argument to plt.subplots()
  • Incorrect assignment syntax
3. What will be the output type of ax after running this code?
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
medium
A.
B.
C.
D.

Solution

  1. Step 1: Understand what plt.subplots() returns

    The function returns a figure object and an axes object. The axes object is usually an instance of AxesSubplot class.
  2. Step 2: Identify the type of ax

    After unpacking, ax is the axes object, which is of type matplotlib.axes._subplots.AxesSubplot.
  3. Final Answer:

    <class 'matplotlib.axes._subplots.AxesSubplot'> -> Option A
  4. Quick Check:

    ax type = AxesSubplot [OK]
Hint: ax is the plot area object, not the figure [OK]
Common Mistakes:
  • Confusing ax type with fig type
  • Thinking ax is a list or tuple
  • Assuming ax is a string or number
4. Identify the error in this code snippet:
import matplotlib.pyplot as plt
fig, ax = plt.subplots
ax.plot([1, 2, 3], [4, 5, 6])
plt.show()
medium
A. fig and ax are reversed in assignment
B. ax.plot() arguments are incorrect
C. Missing parentheses after plt.subplots
D. plt.show() is called before plotting

Solution

  1. Step 1: Check the call to plt.subplots

    The code uses plt.subplots without parentheses, so it assigns the function itself, not its result.
  2. Step 2: Understand the impact on ax.plot

    Since fig, ax are assigned incorrectly, ax is a function, not an axes object, so ax.plot() will cause an error.
  3. Final Answer:

    Missing parentheses after plt.subplots -> Option C
  4. Quick Check:

    Call plt.subplots() with () [OK]
Hint: Always add () to call plt.subplots function [OK]
Common Mistakes:
  • Forgetting parentheses on plt.subplots
  • Mixing up fig and ax variables
  • Calling plt.show() too early
5. You want to create a figure with 2 rows and 1 column of plots using plt.subplots(). Which code correctly creates the figure and axes, and plots a line on the second subplot?
hard
A. fig, ax = plt.subplots(2, 1) ax[1].plot([1, 2, 3], [3, 2, 1])
B. fig, ax = plt.subplots(1, 2) ax[2].plot([1, 2, 3], [3, 2, 1])
C. fig, ax = plt.subplots(2, 1) ax.plot([1, 2, 3], [3, 2, 1])
D. fig, ax = plt.subplots(2) ax[0].plot([1, 2, 3], [3, 2, 1])

Solution

  1. Step 1: Create figure with 2 rows and 1 column

    Use plt.subplots(2, 1) to create 2 vertical subplots. This returns ax as an array of axes.
  2. Step 2: Plot on the second subplot

    Access the second subplot with ax[1] (indexing starts at 0) and call plot() on it.
  3. Final Answer:

    fig, ax = plt.subplots(2, 1) ax[1].plot([1, 2, 3], [3, 2, 1]) -> Option A
  4. Quick Check:

    2 rows, 1 col = plt.subplots(2,1), plot on ax[1] [OK]
Hint: Use ax[index] for multiple subplots, index starts at 0 [OK]
Common Mistakes:
  • Using wrong subplot shape (1,2) instead of (2,1)
  • Trying to plot on ax without indexing when multiple axes exist
  • Using invalid index like ax[2] when only 2 subplots exist
Recommended

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10 questions~5 mineasy hard