Subplots for multiple charts in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of using subplots in data visualization?

Subplots allow you to display multiple charts in one figure. This helps compare different data views side by side easily.

beginner

How do you create a 2x2 grid of subplots using matplotlib?

Use plt.subplots(2, 2) to create a figure with 4 subplots arranged in 2 rows and 2 columns.

beginner

What does the 'axes' object represent when you create subplots?

The 'axes' object is the area where each individual chart is drawn. It lets you control each subplot separately.

intermediate

How can you adjust the space between subplots?

Use plt.tight_layout() or fig.subplots_adjust() to add space between subplots so labels and titles don’t overlap.

beginner

Why might you use subplots instead of separate figures?

Subplots keep related charts together in one view. This makes it easier to compare data and saves screen space.

Which function creates multiple subplots in matplotlib?

A plt.plot()

B plt.subplots()

C plt.figure()

D plt.show()

plt.subplots() creates a figure and a grid of subplots.

What does plt.subplots(3, 1) create?

A A single plot

B 1 row and 3 columns of subplots

C 3 rows and 1 column of subplots

D 3 separate figures

It creates 3 subplots stacked vertically in one column.

How do you access the second subplot in a 1D axes array from plt.subplots(2)?

A axes[1]

B axes[0]

C axes(1)

D axes[2]

Indexing starts at 0, so the second subplot is axes[1].

Which method helps prevent overlapping labels in subplots?

A plt.plot()

B plt.show()

C plt.grid()

D plt.tight_layout()

plt.tight_layout() automatically adjusts spacing to avoid overlaps.

If you want 4 subplots in a 2x2 grid, which call is correct?

A plt.subplots(2, 2)

B plt.subplots(4, 1)

C plt.subplots(1, 4)

D plt.subplots(3, 3)

plt.subplots(2, 2) creates 4 subplots arranged in 2 rows and 2 columns.

Explain how to create and customize multiple charts using subplots in matplotlib.

Think about how to organize charts in a grid and control each one.

Describe why subplots are useful when analyzing data with multiple related charts.

Consider the benefits of seeing charts together instead of separately.

Practice

1. What is the main purpose of using plt.subplots() in data visualization?

easy

A. To create multiple charts in one figure for easy comparison

B. To save a plot as an image file

C. To change the color of a single plot

D. To add a title to a chart

Solution

1. Step 1: Understand the function of plt.subplots()

   This function creates a figure and a grid of subplots (axes) to hold multiple charts.

2. Step 2: Recognize the benefit of multiple charts in one figure

   Having multiple charts in one figure helps compare data visually side-by-side.

3. Final Answer:

   To create multiple charts in one figure for easy comparison -> Option A

4. Quick Check:

   Subplots = multiple charts in one figure [OK]

Hint: Subplots = multiple charts in one figure [OK]

Common Mistakes:

• Thinking it saves images
• Confusing with styling functions
• Assuming it adds titles

2. Which of the following is the correct way to create a 2x2 grid of subplots using Matplotlib?

easy

A. fig, axs = plt.subplots(2)

B. fig, axs = plt.subplots(4)

C. fig, axs = plt.subplots(1, 4)

D. fig, axs = plt.subplots(2, 2)

Solution

1. Step 1: Recall the syntax of plt.subplots()

   The function takes rows and columns as arguments to create a grid.

2. Step 2: Identify the 2x2 grid syntax

   Using plt.subplots(2, 2) creates 2 rows and 2 columns, making 4 subplots.

3. Final Answer:

   fig, axs = plt.subplots(2, 2) -> Option D

4. Quick Check:

   Rows and columns = plt.subplots(2, 2) [OK]

Hint: Rows and columns go as two numbers in plt.subplots() [OK]

Common Mistakes:

• Passing only one number for grid
• Confusing total plots with grid shape
• Using wrong argument order

3. What will be the output shape of axs when you run fig, axs = plt.subplots(3, 1)?

medium

A. A list of 3 Axes objects

B. A single Axes object

C. A 3x1 numpy array of Axes objects

D. A 1x3 numpy array of Axes objects

Solution

1. Step 1: Understand plt.subplots(3, 1) creates 3 rows and 1 column

   This means 3 subplots stacked vertically.

2. Step 2: Check the type of axs for single column

   When columns = 1, axs is a 2D numpy array of shape (3,1) of Axes objects, not a list.

3. Final Answer:

   A 3x1 numpy array of Axes objects -> Option C

4. Quick Check:

   Single column = 2D numpy array of shape (3,1) [OK]

Hint: Single column subplots return 2D numpy array of shape (n,1) [OK]

Common Mistakes:

• Assuming always 1D list
• Confusing rows and columns order
• Expecting single Axes object

4. Identify the error in this code snippet for plotting on subplots:

fig, axs = plt.subplots(2, 2)
axs[2, 0].plot([1, 2, 3])

medium

A. TypeError because axs is not subscriptable

B. IndexError because axs[2, 0] is out of range

C. No error, code runs fine

D. SyntaxError due to wrong indexing

Solution

1. Step 1: Check the shape of axs from plt.subplots(2, 2)

   It creates a 2x2 grid, so valid indices are 0 or 1 for rows and columns.

2. Step 2: Analyze the index axs[2, 0]

   Index 2 for rows is out of range (only 0 and 1 allowed), causing IndexError.

3. Final Answer:

   IndexError because axs[2, 0] is out of range -> Option B

4. Quick Check:

   Index out of range = IndexError [OK]

Hint: Check subplot indices start at 0 and max is rows-1 [OK]

Common Mistakes:

• Using indices beyond grid size
• Confusing syntax error with index error
• Assuming axs is a flat list

5. You want to plot 5 different line charts in a single figure using subplots arranged in 2 rows and 3 columns. Which code correctly handles the extra subplot that will remain empty?

hard

A. fig, axs = plt.subplots(2, 3)
for i in range(5):
axs.flat[i].plot([i, i+1, i+2])
axs.flat[5].axis('off')

B. fig, axs = plt.subplots(2, 3)
for i in range(6):
axs[i].plot([i, i+1, i+2])

C. fig, axs = plt.subplots(5, 1)
for i in range(5):
axs[i].plot([i, i+1, i+2])

D. fig, axs = plt.subplots(1, 5)
for i in range(5):
axs[i].plot([i, i+1, i+2])

Solution

1. Step 1: Understand subplot grid and number of plots

   A 2x3 grid has 6 subplots but only 5 are needed, so one remains empty.

2. Step 2: Use axs.flat to iterate all subplots in 1D

   This allows easy indexing over the 2D array of axes.

3. Step 3: Turn off the extra subplot axis

   Calling axs.flat[5].axis('off') hides the unused subplot.

4. Final Answer:

   fig, axs = plt.subplots(2, 3) for i in range(5): axs.flat[i].plot([i, i+1, i+2]) axs.flat[5].axis('off') -> Option A

5. Quick Check:

   Use axs.flat and turn off extra subplot [OK]

Hint: Use axs.flat to index subplots and turn off unused ones [OK]

Common Mistakes:

• Ignoring extra subplot and leaving it blank
• Indexing axs as 1D when it's 2D without flat
• Creating wrong grid shape for number of plots