Figure and axes creation in Data Analysis Python - Mini Project: Build & Apply

Figure and axes creation

📖 Scenario: You are working as a data analyst. You want to create a simple plot to visualize some data. Before plotting, you need to create a figure and axes using a popular plotting library.

🎯 Goal: Create a figure and axes using matplotlib.pyplot so you can later add plots to the axes.

📋 What You'll Learn

Import matplotlib.pyplot as plt

Create a figure and axes using plt.subplots()

Store the figure in a variable called fig

Store the axes in a variable called ax

💡 Why This Matters

🌍 Real World

Creating figures and axes is the first step in visualizing data in many data science projects.

💼 Career

Data analysts and scientists often create plots to explore and communicate data insights clearly.

1

Import matplotlib.pyplot

Write the import statement to import matplotlib.pyplot as plt.

Data Analysis Python

# Your code here

Hint

Use the syntax import matplotlib.pyplot as plt to import the plotting library.

2

Create figure and axes

Create a figure and axes using plt.subplots(). Assign the figure to a variable called fig and the axes to a variable called ax.

Data Analysis Python

import matplotlib.pyplot as plt
# Create figure and axes using plt.subplots()
# Your code here

Hint

Use fig, ax = plt.subplots() to create the figure and axes.

3

Check figure and axes types

Write code to print the types of fig and ax using the type() function.

Data Analysis Python

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
# Print the types of fig and ax
# Your code here

Hint

Use print(type(fig)) and print(type(ax)) to see their types.

4

Display the empty figure

Use the plt.show() function to display the empty figure you created.

Data Analysis Python

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
print(type(fig))
print(type(ax))
# Display the figure
# Your code here

Hint

Call plt.show() to open a window with the empty plot.

Practice

1. What does the plt.subplots() function return in matplotlib?

easy

A. A figure and one or more axes objects

B. Only a figure object

C. Only an axes object

D. A list of data points

Solution

1. Step 1: Understand plt.subplots() purpose

   The function is designed to create a figure and axes together for plotting.

2. Step 2: Check the return values

   It returns a tuple: the first is the figure, the second is the axes (single or array).

3. Final Answer:

   A figure and one or more axes objects -> Option A

4. Quick Check:

   plt.subplots() = (figure, axes) [OK]

Hint: Remember plt.subplots() returns figure and axes together [OK]

Common Mistakes:

• Thinking it returns only figure or only axes
• Confusing axes with data points
• Assuming it returns a plot directly

2. Which of the following is the correct syntax to create a figure with 2 rows and 3 columns of axes using matplotlib?

easy

A. fig, axes = plt.subplots(rows=3, cols=2)

B. fig, axes = plt.subplots(2, 3)

C. fig, axes = plt.subplots(3, 2)

D. fig, axes = plt.subplots(2*3)

Solution

1. Step 1: Recall plt.subplots() parameters

   The first argument is number of rows, the second is number of columns.

2. Step 2: Match the correct order

   To create 2 rows and 3 columns, use plt.subplots(2, 3).

3. Final Answer:

   fig, axes = plt.subplots(2, 3) -> Option B

4. Quick Check:

   Rows first, columns second in plt.subplots() [OK]

Hint: Remember rows first, columns second in plt.subplots() [OK]

Common Mistakes:

• Swapping rows and columns order
• Using keyword arguments incorrectly
• Passing a single number instead of two

3. What will be the shape of axes when running fig, axes = plt.subplots(2, 2)?

medium

A. A 2x2 numpy array of AxesSubplot objects

B. A list of 4 AxesSubplot objects

C. A single AxesSubplot object

D. A dictionary of axes objects

Solution

1. Step 1: Understand axes structure for multiple subplots

   When more than one subplot is created, axes is a 2D array matching the grid shape.

2. Step 2: Check the shape for 2 rows and 2 columns

   Axes will be a 2x2 numpy array of AxesSubplot objects.

3. Final Answer:

   A 2x2 numpy array of AxesSubplot objects -> Option A

4. Quick Check:

   Multiple subplots = axes array matching grid [OK]

Hint: Multiple subplots return axes array matching rows and columns [OK]

Common Mistakes:

• Expecting a flat list instead of 2D array
• Thinking axes is a single object always
• Confusing axes with figure

4. Identify the error in this code snippet:

fig, ax = plt.subplots(2, 2)
ax.plot([1, 2, 3], [4, 5, 6])

medium

A. fig and ax are swapped in assignment

B. plt.subplots() cannot create 2x2 axes

C. ax is an array, so ax.plot() causes an error

D. The plot data lists have different lengths

Solution

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

   ax is a 2x2 array of axes, not a single axes object.

2. Step 2: Understand why ax.plot() fails

   Calling plot() on an array causes an AttributeError because arrays don't have plot method.

3. Final Answer:

   ax is an array, so ax.plot() causes an error -> Option C

4. Quick Check:

   Array of axes needs indexing before plot() [OK]

Hint: Index axes array before plotting when multiple subplots exist [OK]

Common Mistakes:

• Trying to plot on axes array directly
• Assuming plt.subplots(2,2) returns single axes
• Ignoring need to index axes for plotting

5. You want to create a figure with 3 subplots stacked vertically and set the figure size to 8 inches wide and 12 inches tall. Which code correctly does this?

hard

A. fig, axes = plt.subplots(1, 3, figsize=(12, 8))

B. fig, axes = plt.subplots(3, figsize=(8, 12))

C. fig, axes = plt.subplots(3, 1, size=(8, 12))

D. fig, axes = plt.subplots(3, 1, figsize=(8, 12))

Solution

1. Step 1: Determine subplot layout for vertical stacking

   3 subplots stacked vertically means 3 rows and 1 column.

2. Step 2: Set figure size correctly

   Use figsize=(width, height) with width=8 and height=12 inches.

3. Final Answer:

   fig, axes = plt.subplots(3, 1, figsize=(8, 12)) -> Option D

4. Quick Check:

   Rows=3, cols=1, figsize=(8,12) [OK]

Hint: Use figsize=(width, height) and rows, columns order [OK]

Common Mistakes:

• Swapping rows and columns
• Using wrong keyword 'size' instead of 'figsize'
• Confusing width and height order