🐍 NumPy Notes - Yuvraj

"That was my first step... now I know far beyond this, as that notes was starting."

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About this Repository

These notes are a guide to NumPy, the fundamental library for numerical computing in Python.
It covers everything from basic array operations to advanced features like vectorization, masking, and saving/loading arrays.

These notes were created as part of my journey to learn Python for data analysis and scientific computing.

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Author

Yuvraj
Skills: Python | NumPy | Data Analysis | Vectorization | Scientific Computing

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What This Note Covers

1. Performance: Lists vs NumPy

• Element-wise operations
• Timing comparisons: Python lists vs NumPy arrays

2. Array Creation

• Zeros, ones, full, random arrays
• arange, identity matrices
• Vectors, matrices, 3D tensors

3. Array Properties

• Shape, dimensions, data type, size, item size, total bytes

4. Transformations

• Reshape, flatten, ravel, transpose

5. Slicing and Indexing

• 1D and 2D indexing
• Row, column, and element selection

6. Sorting and Uniqueness

• Sorting arrays
• Unique elements
• Row-wise and column-wise sorting

7. Filtering and Masking

• Boolean indexing
• Fancy indexing
• np.where for conditional selection

8. Combining & Deleting

• Concatenation
• Deleting elements

9. Arithmetic Operations

• Element-wise addition and multiplication
• Dot product
• Matrix multiplication using @

10. Vectorization of Python Functions

• Using np.vectorize to apply functions element-wise

11. Save & Load Arrays

• Save arrays with np.save and load them with np.load

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Files Generated

• my_array.npy (saved array example)

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"That was my first step... now I know far beyond this, as that notes was ending."

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