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Matplotlibdata~30 mins

Transparent backgrounds in Matplotlib - Mini Project: Build & Apply

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Transparent backgrounds
📖 Scenario: You are creating a simple line plot to visualize sales data over a week. You want to save the plot image with a transparent background so it can be used on different colored web pages without a white box around it.
🎯 Goal: Build a line plot using matplotlib and save the image with a transparent background.
📋 What You'll Learn
Create a list of sales numbers for 7 days
Create a list of day names for the x-axis
Plot the sales data as a line chart
Save the plot image with a transparent background
💡 Why This Matters
🌍 Real World
Transparent backgrounds in plots are useful when you want to overlay charts on different colored backgrounds in presentations or websites without a white box around the image.
💼 Career
Data scientists and analysts often need to create clean, professional visuals that integrate seamlessly into reports and dashboards. Knowing how to save images with transparent backgrounds helps in producing polished deliverables.
Progress0 / 4 steps
1
Create sales data and days list
Create a list called sales with these exact values: [150, 200, 170, 220, 180, 210, 190]. Also create a list called days with these exact values: ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"].
Matplotlib
Need a hint?

Use square brackets to create lists. Separate values with commas.

2
Import matplotlib and set up plot
Import matplotlib.pyplot as plt. Then create a line plot using plt.plot(days, sales).
Matplotlib
Need a hint?

Use import matplotlib.pyplot as plt to import. Then call plt.plot(days, sales) to create the line chart.

3
Save the plot with transparent background
Save the plot image as sales_plot.png using plt.savefig with the argument transparent=True to make the background transparent.
Matplotlib
Need a hint?

Use plt.savefig("sales_plot.png", transparent=True) to save with a transparent background.

4
Display the plot
Use plt.show() to display the plot on the screen.
Matplotlib
Need a hint?

Call plt.show() to see the plot window.