Tuesday, 27 January 2026

📈 Day 1: Line Chart in Python

Samaksh Dubey January 27, 2026 data, Data Science No comments

📈 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.

🔍 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

✅ 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

❌ 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

📊 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

🧠 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()