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. WHO IS THIS BOOK FORThis 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 CONTENT1 Introduction1.1Basic of programming language1.2 What is Python?1.3 Python Development Environment1.4 Basic data types in Python1.5 Looping and Condition1.6 Python functions2Python Packages2.1 Mathematics - NumPy2.2 Data Analysis - Pandas2.3 Visual Plot - Matplotlib3 Advanced Python Examples3.1 Mathematical modelling3.2 Visual graphic examples3.3 Model Parameter Analysis3.4 Object Oriented Programming (OOP)