Python for Data Science

Master Python for data analysis, visualization, and machine learning

Python in Data Science

Learn why Python is the preferred language for data science

Key Concept: Python is the leading language for data science with rich libraries for analysis, visualization, and machine learning.

Essential Libraries

  • NumPy: Numerical computing and array operations
  • Pandas: Data manipulation and analysis
  • Matplotlib: Data visualization
  • Scikit-learn: Machine learning algorithms
  • TensorFlow/PyTorch: Deep learning frameworks

NumPy Basics

Work with numerical arrays

NumPy Arrays
import numpy as np

# Create arrays
arr = np.array([1, 2, 3, 4, 5])
matrix = np.array([[1, 2], [3, 4]])

# Operations
print(arr.mean())
print(arr.sum())
print(matrix.shape)

Key Takeaways

  • Python is the leading data science language
  • NumPy provides efficient numerical computing
  • Pandas simplifies data manipulation
  • Scikit-learn offers machine learning algorithms