Python_Matplotlib_13_Slides_With_Diagrams.pptx

Python_Matplotlib_13_Slides_With_Diagrams.pptx

• 1.
  Data Visualization UsingPython Matplotlib • An Overview of Python’s Powerful Plotting Library • Presented by: [Your Name]
• 2.
  Introduction to DataVisualization • • Importance of visualizing data • • Common chart types • • Helps identify trends and outliers
• 3.
  What is Matplotlib? •• A plotting library for Python • • Part of the SciPy stack • • Created by John D. Hunter
• 4.
  Installing and ImportingMatplotlib • • Install: pip install matplotlib • • Import: import matplotlib.pyplot as plt
• 5.
  Matplotlib Architecture • •Figure, Axes, and Axis • • Object-oriented vs. Pyplot interface
• 6.
  Creating Basic Plots •• Line plot syntax: plt.plot(x, y) • • Used to show trends over time
• 7.
  Bar and HistogramCharts • • Bar: plt.bar() • • Histogram: plt.hist() • • Useful for categorical and frequency data
• 8.
  Scatter Plots andCustomization • • Syntax: plt.scatter(x, y) • • Customize markers, size, and color
• 9.
  Pie Charts • •Syntax: plt.pie() • • Show parts of a whole
• 10.
  Subplots and Layouts •• Multiple plots using plt.subplot() or plt.subplots() • • Useful for comparing data
• 11.
  Styling and CustomizingPlots • • Titles: plt.title() • • Labels: plt.xlabel(), plt.ylabel() • • Legends and grid
• 12.
  Saving and ExportingFigures • • Syntax: plt.savefig('filename.png') • • Formats: PNG, PDF, SVG
• 13.
  Conclusion and Applications •• Easy to use and highly customizable • • Used in Data Science, Machine Learning, etc.