NumPy – Basics & Examples

Sandeep Mewara

This is to get started with NumPy and try few concrete examples. NumPy (Numerical Python) are packages for numerical computation designed for efficient work on large data sets.

Entire Jupiter notebook can be downloaded or forked from my GitHub to play around: https://github.com/sandeep-mewara/python-examples

numpy-icon

Reference: https://numpy.org/learn/

NumPy basics includes:

  • Initialize Matrix via
    • List
    • NULL Matrix
    • IDENTITY Matrix
    • ONES Matrix
  • Matrix Transpose
  • Matrix Indexing
  • Simulation
  • Basic CSV file operations
  • Matrix Broadcasting
  • Basic Image Processing

# matrix in python is list of a list

# arrays are compatible for broadcasting when the trailing dimensions match or either of them is of length 1

# image when read as numbers, the values are between 0 & 1

Key learning’s …

Examples notebook includes:

  • Random walk simulation
  • Triangle simulation
  • Random Number
  • Correlation co-efficient
  • Mean/Variance of crude oil

# masking helps get all the values back that satisfy the mask

# cumsum() is a handy function for cumulative sum

# there are handy methods for random number generation

Key learning’s …

For learning more about NumPy, look here: https://numpy.org/doc/stable/

Keep learning!

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