NumPy Tutorial

This notebook explores fundamental concepts and operations in the NumPy library for numerical computing in Python.

Array Creation and Properties

• Creating arrays from Python lists.
• Checking array type and dimensions (ndim).
• Creating arrays with a specified number of dimensions (ndmin).
• Creating arrays filled with zeros (zeros).
• Creating arrays filled with ones (ones).
• Creating empty arrays (empty).
• Creating arrays with a range of values (arange).
• Creating identity matrices (eye).
• Creating evenly spaced values within an interval (linspace).
• Creating arrays with random numbers (random.rand, random.randn, random.ranf, random.randint).

Data Types

• Understanding different data types in NumPy arrays (dtype).
• Converting data types of arrays.

Arithmetic Operations

• Performing element-wise arithmetic operations between arrays and scalars.
• Performing element-wise arithmetic operations between two arrays.
• Using NumPy's arithmetic functions (add, subtract, multiply, divide, mod, power, reciprocal).
• Performing arithmetic operations on 2D arrays.

Arithmetic Functions

• Using common arithmetic functions like max, min, argmin, argmax, sqrt, sin, cos, cumsum.
• Applying arithmetic functions to 2D arrays along specific axes.

Shape and Reshaping

• Checking the shape of an array (shape).
• Reshaping arrays into different dimensions (reshape).
• Reshaping to a 1D array (reshape(-1)).

Broadcasting

• Understanding broadcasting rules and errors.

Indexing and Slicing

• Accessing elements in 1D, 2D, and 3D arrays using indexing.
• Slicing arrays to extract subsets of elements.

Iteration

• Iterating through array elements using standard Python loops.
• Iterating through arrays using np.nditer.
• Iterating through arrays with index using np.ndenumerate.

Copy vs View

• Differentiating between copying and viewing arrays and how changes affect the original and new arrays.

Join and Split

• Joining arrays using concatenate, stack, hstack, vstack, and dstack.
• Splitting arrays using array_split.

Search, Sort, and Filter

• Searching for elements in an array using where.
• Searching for insertion points in a sorted array using searchsorted.
• Sorting arrays using sort.
• Filtering arrays based on a boolean mask.

Other Functions

• Shuffling array elements randomly using shuffle.
• Finding unique elements in an array using unique.
• Resizing arrays using resize.
• Flattening arrays to 1D using flatten and ravel.

Insert and Delete

• Inserting elements into an array using insert.
• Appending elements to an array using append.
• Deleting elements from an array using delete.

Matrix Operations

• Creating NumPy matrices.
• Performing arithmetic operations on matrices (including dot product).
• Using matrix functions like transpose, swapaxes, linalg.inv (inverse), linalg.matrix_power, and linalg.det (determinant).