Introduction to Python - Data Science, Quantitative Finance (2.0)

It is a book for both beginners and experienced professionals who either have a relevant educational background or are interested in learning Python under the data science or quantitative finance background.

No prior experience in Python is required. It is a practical book complete with working code that guides the reader through the basics of Python. Topics are introduced gradually, each building on the last. The examples are either run in a command line or an editor. Jupyter notebook examples are presented in later part of the book where mathematical models and data analysis of time series are introduced.

BY THE END OF THIS BOOK, YOU WILL BE ABLE TO :
•gain a general understanding of Python
•write basic Python code
•write Python function to perform efficient data analysis and simple financial model analysis for those who have prior knowledge of programming ( you could skip the first chapter)

WHO IS THIS BOOK FOR
This book is directed at both industry practitioners and students interested in learning python for financial modelling or/and data science purpose. It helps to advance your career either within the finance modelling arena or the Data science field! You will also find this book useful if you want to extend the your existing programming language knowledge in another application field.

TABLE OF CONTENT
1Introduction
1.1Basic of programming language
1.2What is Python?
1.3Python Development Environment
1.4Basic data types in Python
1.5Looping and Condition
1.6Python functions
1.7 Further examples
2Python Packages
2.1Mathematics - NumPy
2.2Data Analysis - Pandas
2.3Visual Plot – Matplotlib
3 Advanced Python Examples
3.1Mathematical modelling
3.2Visual graphic examples
3.3Model Parameter Analysis
3.4Object Oriented Programming (OOP)