Formation
90 min read
Data Visualization
📦 Visualization with Matplotlib
Learning objectives
🎯 Objectives:\n
1Create line plots\n2. Create bar charts\n3. Create histograms\n4. Customize plots
Introduction
📖 Matplotlib is the most widely used visualization library in Python.
Theoretical content
Matplotlib:\n
PYTHON
\nimport matplotlib.pyplot as plt\nplt.plot([1,2,3], [4,5,6])\nplt.show()\nPractical examples
💻 Example: Sales chart\n
PYTHON
\nimport matplotlib.pyplot as plt\nplt.plot(["Jan", "Feb"], [1000, 1200])\nplt.show()\nBest practices
1Always import plt\n✅ 2. Use figure() for size\n✅ 3. Add titles and labels\n✅ 4. Use grid() for readability\n✅ 5. tight_layout() to avoid overlap
Common pitfalls
Forgetting plt.show()\n
Always call plt.show()
Summary
plot(): line plot\n✅ bar(): bar chart\n✅ hist(): histogram\n✅ title(), xlabel(), ylabel(): labels\n✅ legend(): legend\n✅ grid(): grid\n✅ show(): display
Additional resources
📚 matplotlib.org/stable/tutorials/index.html