Resources for developers using Python for scientific computing and quantitative analysis
Python’s pandas library is one of the things that makes Python a great programming language for data analysis. Pandas makes importing, analyzing, and visualizing data much easier. It builds on packages like NumPy and matplotlib to give you a single, convenient, place to do most of your data analysis and visualization work.
Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more.
