📈 Day 1: Line Chart in Python

 

📈 Day 1: Line Chart in Python – Visualize Trends Like a Pro

When working with data, one of the most common questions we ask is:
“How does this value change over time?”

That’s exactly where a Line Chart comes in.

Welcome to Day 1 of the “50 Days of Python Data Visualization” series, where we explore one essential chart every day using Python.

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🔍 What is a Line Chart?

A line chart is a data visualization technique used to show trends and changes over time.

It connects individual data points with straight lines, making it easy to:

• Identify upward or downward trends

• Spot sudden spikes or drops

• Compare growth patterns

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✅ When Should You Use a Line Chart?

Use a line chart when:

• Data is time-based (days, months, years)

• You want to track progress or trends

• Order of values matters

Real-world examples:

• Website traffic over months

• Stock prices over days

• Temperature changes during a week

• App downloads over time

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❌ When NOT to Use a Line Chart

Avoid line charts when:

• Data is categorical → use a bar chart

• You want to show relationships → use a scatter plot

• Order of data does not matter

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📊 Example Dataset

Let’s say we want to visualize website visitors over 6 months.

Month	Visitors
Jan	120
Feb	150
Mar	180
Apr	160
May	200
Jun	240

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🧠 Python Code: Line Chart Using Matplotlib

import matplotlib.pyplot as plt

# Data
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
visitors = [120, 150, 180, 160, 200, 240]

# Create line chart
plt.plot(months, visitors, marker='o') 

# Labels and title
plt.xlabel('Month')
plt.ylabel('Visitors') 
plt.title('Website Visitors Over Time')

# Display chart
plt.show()

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🧩 Code Explanation (Simple Words)

• plt.plot() → creates the line chart

• marker='o' → shows dots on each data point

• xlabel() and ylabel() → label the axes

• title() → adds chart title

• show() → displays the chart

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📌 Key Takeaways

✔ Line charts show trends over time
✔ Order of x-axis values is very important
✔ Simple, powerful, and widely used in data science