Numpy in Cheat sheet
NumPy (Numerical Python) is a library in Python for scientific computing and data analysis. It provides support for arrays (n-dimensional arrays), which are an efficient data structure for numerical computations. NumPy also includes functions for performing mathematical operations on arrays, such as linear algebra, statistical analysis, and Fourier transformations. Additionally, it is integrated with other scientific computing libraries, such as Pandas and Matplotlib, making it a popular choice for data analysis and scientific computing tasks in Python.
NumPy is an essential library for anyone who works with numerical data in Python. Its array data structure and optimized mathematical functions make it a fast and efficient tool for numerical computations, data analysis, and scientific computing. Additionally, its integration with other libraries, such as Pandas and Matplotlib, make it a popular choice for data scientists, engineers, and researchers working with large amounts of numerical data. Whether you’re a beginner or an experienced data analyst, learning NumPy is a valuable investment in your Python programming skills.