Introduction

This is a collection of sympy examples and notes. The purpose of this is to provide a cheat sheet summary of the techniques used in solving sympy problems.

The purpose of this is to provide a cheat sheet summary of the techniques used in solving sympy problems from

1. Mathematics
2. Probability
3. Statistics
4. Dynamics(Kinematics and Kinetics)

2023/08/26 Document creation and intro

IPython

• Described in Ipython usage

IPython (Interactive Python) is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language. It offers introspection, rich media, shell syntax, tab completion, and history. IPython provides the following features:

• Interactive shells (terminal and Qt-based)
• A web-based notebook interface with support for code, text, mathematical expressions, inline plots and other media
• Support for interactive data visualization and use of GUI toolkits
• Flexible, embeddable interpreters to load into one's own projects
• Tools for parallel computing

IPython is a powerful tool for data scientists, machine learning engineers, and other professionals who need to work with Python interactively. It is also a popular choice for teaching Python, as it makes it easy to experiment with code and see the results immediately.

IPython and Jupyter

Jupyter is a web-based interactive computing environment that supports many programming languages, including Python. It is a spin-off of the IPython project, and IPython is still a core component of Jupyter.

Jupyter notebooks, which are the most popular way to use Jupyter, are interactive documents that contain code, text, mathematical expressions, inline plots, and other media. Jupyter notebooks are created using the IPython kernel, which is a Python interpreter that runs inside of Jupyter.

IPython also provides a number of other features, such as:

• A terminal-based interactive shell
• A Qt-based interactive shell
• A number of tools for parallel computing
• Support for embedding IPython in other applications

Jupyter is a popular choice for data science, machine learning, and other computational tasks. It is also widely used in education and research.

Here is a summary of the relationship between Jupyter and IPython:

• Jupyter is a web-based interactive computing environment that supports many programming languages.
• IPython is a Python interpreter and command shell for interactive computing.
• IPython is the core component of Jupyter notebooks.
• IPython also provides a number of other features, such as a terminal-based interactive shell, a Qt-based interactive shell, and a number of tools for parallel computing.

Sympy

1. SymPy Documentation
2. SymPy Modules Reference
3. tutorialspoint Sympy Tutorial
4. Sympy Live
5. Scipy Lecture Notes
6. Sympy Tutorial Main Site
7. Sympy Tutorial - Russia
8. Sympy examples 1
9. SymPy: symbolic computing in Python looks cool
10. Good sympy tutorial and sympy plotting by Vladimir Dobrushkin

Vectors, Tensors and Fields

Added a doc by Peacock on Vectors, Tensors and Fields. It is very readable. The book may be found in thedocs section

Statistics

Provide a simple guide for using sympy.stats in a note book