MATplotlib

1. Matplotlib (Class 12 Python)
– Matplotlib is a Python library used for data
visualization.
– Used to create plots, charts and graphs.

2. Why Use Matplotlib?
– Easy to create high quality graphs.
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– Supports many plot types.
– Widely used in Data Science.

3. Basic Syntax
– import matplotlib.pyplot as plt
– plt.plot(x, y)
– plt.show()

4. Types of Plots
– Line Plot
– Bar Chart
– Histogram
– Scatter Plot
– Pie Chart

5. Line Plot
– Used to show trends over time.
– Syntax: plt.plot(x, y)

6. Example: Line Plot
– import matplotlib.pyplot as plt
– x=[1,2,3,4]
– y=[10,20,15,30]
– plt.plot(x,y)
– plt.show()

7. Bar Chart
– Used to compare values across categories.
– Syntax: plt.bar(x, height)

8. Example: Bar Chart
– x=['A','B','C']
– y=[10,25,15]
– plt.bar(x,y)

9. Scatter Plot
– Shows relationship between two variables.
– Syntax: plt.scatter(x, y)

10. Histogram
– Represents distribution of data.
– Syntax: plt.hist(data)

11. Pie Chart
– Used to show proportion of categories.
– Syntax: plt.pie(values, labels=labels)

12. Adding Labels
– plt.xlabel('X-axis')
– plt.ylabel('Y-axis')
– plt.title('Graph Title')

13. Figure Size
– plt.figure(figsize=(6,4))
– Used to change graph dimensions.

14. Multiple Plots
– plt.subplot(rows, columns, plot_number)

15. Saving Graph
– plt.savefig('graph.png')

16. Styling
– color, linestyle, linewidth options available

17. Common Functions
– plt.grid()
– plt.legend()
– plt.xlim() / plt.ylim()

18. Real-Life Uses
– Data analysis
– Machine learning
– Business reporting

19. Summary
– Matplotlib is essential for visualization.
– Supports many chart types.
– Simple and powerful.

20. End
– Thank You!