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.