📊 Day 7: Column Chart in Python

 

📊 Day 7: Column Chart in Python

🔹 What is a Column Chart?

A Column Chart is a type of bar chart where vertical bars represent values for different categories.
The height of each column shows the magnitude of the data.

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🔹 When Should You Use It?

Use a column chart when:

• Comparing values across categories

• Tracking changes over time

• Showing performance, growth, or trends

• You want a simple and intuitive comparison

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🔹 Example Scenario

Suppose you are tracking monthly sales of a product.
A column chart quickly shows:

• Which month performed best

• Sales growth or decline over time

• Easy month-to-month comparison

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🔹 Key Idea Behind It

👉 Categories on the X-axis
👉 Values on the Y-axis
👉 Taller column = higher value

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🔹 Python Code (Column Chart)

import matplotlib.pyplot as plt

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

plt.bar(months, sales) 

plt.xlabel('Months')
plt.ylabel('Sales')
plt.title('Monthly Sales Column Chart')

plt.show()

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🔹 Output Explanation

• Each column represents one month

• Column height shows sales value

• Easy to spot:

  • Highest sales → June

  • Growth trend from Jan to Jun

• Clear and readable visualization

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🔹 Column Chart vs Bar Chart

Feature	Column Chart	Bar Chart
Orientation	Vertical	Horizontal
Best for	Time-based data	Category comparison
Readability	Trend-focused	Label-friendly

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🔹 Key Takeaways

• Column charts are simple and powerful

• Best for time-series comparison

• Easy to interpret for beginners

• Widely used in business & analytics

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