Learn Challenge: Earnings Trend Visualizer | Analyzing and Visualizing Freelance Data

In this challenge, you will create a Python script that visualizes your freelance earnings for each month using matplotlib. This exercise will help you gain practical experience in turning raw data into a clear, informative line plot—a valuable skill for freelancers who want to quickly interpret their income trends over time.

Begin by defining your earnings data. Use a Python list to represent the earnings for each month. Assign each month's name to a separate list to use as labels on the x-axis. Next, use matplotlib.pyplot to plot this data as a line graph. You will add markers to each data point for clarity, label both axes, set a descriptive title, and enable gridlines to make the plot easier to read.


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import matplotlib.pyplot as plt

# Hardcoded monthly earnings data (in USD)
months = [
    "Jan", "Feb", "Mar", "Apr", "May", "Jun",
    "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"
]
earnings = [1200, 1350, 1600, 1550, 1700, 1800, 1750, 1900, 2100, 2200, 2000, 2300]

plt.figure(figsize=(10, 6))
plt.plot(months, earnings, marker="o", color="blue", linestyle="-", linewidth=2, markersize=8)

plt.title("Freelance Earnings Trend (2024)")
plt.xlabel("Month")
plt.ylabel("Earnings (USD)")
plt.grid(True, linestyle="--", alpha=0.6)
plt.tight_layout()
plt.show()

This script will generate a line plot showing how your freelance earnings changed month by month. The markers highlight each month's earning, and the gridlines help you compare values more easily. The labeled axes and title provide clear context, making the plot straightforward to interpret and present to clients or for your own records.

Task

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Write a Python script to visualize your monthly freelance earnings as a line plot using matplotlib.

Define two lists: one for month names and one for earnings data.
Plot the earnings data as a line plot with markers for each point.
Add labels for the x-axis (months) and y-axis (earnings).
Set a title for the plot.
Enable gridlines for clarity.

Your code will be tested for:

Correct use of matplotlib to plot the data.
Proper labeling of axes and title.
Use of markers and gridlines on the plot.

Solution

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Section 2. Chapter 3

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What should I do if my earnings data is in a CSV file instead of a list?

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import matplotlib.pyplot as plt

# Hardcoded monthly earnings data (in USD)
months = [
    "Jan", "Feb", "Mar", "Apr", "May", "Jun",
    "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"
]
earnings = [1200, 1350, 1600, 1550, 1700, 1800, 1750, 1900, 2100, 2200, 2000, 2300]

plt.figure(figsize=(10, 6))
plt.plot(months, earnings, marker="o", color="blue", linestyle="-", linewidth=2, markersize=8)

plt.title("Freelance Earnings Trend (2024)")
plt.xlabel("Month")
plt.ylabel("Earnings (USD)")
plt.grid(True, linestyle="--", alpha=0.6)
plt.tight_layout()
plt.show()