NumPy

The core Python library for data manipulation

NumPy is a popular Python library used for numerical computing, scientific computing, and data analysis. It provides support for large, multi-dimensional arrays and matrices, along with a large library of mathematical functions to operate on these arrays.

Efficient array operations: NumPy arrays are much more efficient than regular Python arrays because they are implemented in C, which makes them faster and more memory-efficient. This makes NumPy a great tool for working with large datasets.

Broadcasting: NumPy's broadcasting feature allows for element-wise operations between arrays of different shapes and sizes, which can simplify code and reduce memory usage.

Linear algebra: NumPy includes a range of functions for linear algebra operations such as matrix multiplication, determinants, and eigenvalues, making it a valuable tool for scientific computing.

Integration with other libraries: NumPy integrates well with other Python libraries such as SciPy (for scientific computing), Pandas (for data analysis), and Matplotlib (for data visualization), making it a key component in many data science and scientific computing workflows.