Axis scales (linear, log) in Matplotlib - Mini Project: Build & Apply

Axis scales (linear, log) with matplotlib

📖 Scenario: You are analyzing sales data that grows exponentially. You want to see how the sales look on a normal scale and on a logarithmic scale to better understand the growth pattern.

🎯 Goal: Create a simple line plot of sales data using matplotlib. First, plot the data with a linear scale on the y-axis. Then, change the y-axis scale to logarithmic to compare the views.

📋 What You'll Learn

Create a list called sales with the values: 10, 100, 1000, 10000, 100000

Create a list called months with the values: 1, 2, 3, 4, 5

Create a variable called y_scale and set it to the string 'linear'

Use matplotlib to plot months vs sales with the y-axis scale set to y_scale

Change the value of y_scale to 'log' and plot the same data again

Print the plots so the output shows both linear and logarithmic scale plots

💡 Why This Matters

🌍 Real World

Scientists and business analysts often use logarithmic scales to better understand data that grows exponentially or covers a wide range.

💼 Career

Knowing how to change axis scales in plots is important for data visualization roles and helps communicate insights clearly.

1

Create the sales and months data lists

Create a list called sales with the values 10, 100, 1000, 10000, and 100000. Also create a list called months with the values 1, 2, 3, 4, and 5.

Matplotlib

# Create the sales and months lists
# Your code here

Need a hint?

Use square brackets [] to create lists with the exact numbers given.

2

Set the initial y-axis scale to linear

Create a variable called y_scale and set it to the string 'linear'.

Matplotlib

sales = [10, 100, 1000, 10000, 100000]
months = [1, 2, 3, 4, 5]

# Set y_scale to 'linear'
# Your code here

Need a hint?

Assign the string 'linear' to the variable y_scale.

3

Plot the sales data with the y-axis scale set to y_scale

Import matplotlib.pyplot as plt. Use plt.plot() to plot months on the x-axis and sales on the y-axis. Then set the y-axis scale using plt.yscale(y_scale). Finally, add a title 'Sales Data with Linear Scale' and call plt.show() to display the plot.

Matplotlib

sales = [10, 100, 1000, 10000, 100000]
months = [1, 2, 3, 4, 5]
y_scale = 'linear'

# Import matplotlib.pyplot as plt
# Plot months vs sales
# Set y-axis scale to y_scale
# Add title 'Sales Data with Linear Scale'
# Show the plot
# Your code here

Need a hint?

Remember to import matplotlib.pyplot as plt. Use plt.plot() and plt.yscale() to set the scale.

4

Change y_scale to 'log' and plot again

Change the value of y_scale to the string 'log'. Then plot months vs sales again using plt.plot(), set the y-axis scale with plt.yscale(y_scale), add the title 'Sales Data with Logarithmic Scale', and call plt.show() to display the plot.

Matplotlib

import matplotlib.pyplot as plt

sales = [10, 100, 1000, 10000, 100000]
months = [1, 2, 3, 4, 5]
y_scale = 'linear'

plt.plot(months, sales)
plt.yscale(y_scale)
plt.title('Sales Data with Linear Scale')
plt.show()

# Change y_scale to 'log'
# Plot months vs sales again
# Set y-axis scale to y_scale
# Add title 'Sales Data with Logarithmic Scale'
# Show the plot
# Your code here

Need a hint?

Assign 'log' to y_scale and repeat the plotting steps with the new scale.