Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition Paperback – 30 Dec. 2022

Really well structured, well written, and the code is thoughtfully put together. This is a complex topic and the direct writing style and real world insights make this a book well worth the asking price. Solid.

Review: Python for Finance Cookbook – Second EditionThis book offers a solid blend of financial concepts and Python programming, making it a valuable resource for anyone looking to apply coding skills to real-world finance problems. The financial objectives are well-chosen, and the Python examples are clear, practical, and well-explained. The only downside is that some of the data sources referenced have changed or become outdated. However, with minor adjustments or alternative APIs, the code can still be adapted effectively. Overall, it remains an excellent learning tool for finance-focused Python developers.

Very good reference book. it covers a lot of essential materials for analysing financial data.

I was sent an early review copy of this to review and have to say, for someone who has worked with Python, it gives a very comprehensive walkthrough of how to connect to and work with Finance data in many ways.The examples are worked through methodically and then each step is explained in detail so the reader gets to understand the 'how' and 'why' of what they are doing.It's a very useful book for a Data Scientist or a Data Analyst looking to advance their skillset.Just a slight warning, this book doesn't aim to give beginners the basic understanding of how to use Python, install modules, the different UIs available, etc so if you're new to Python, I'd suggest starting with a basics book first

Immediately what drew me in was the table of contents, describing topic, how to do it, how it works and additional info. Clearly the author has spent time to think what are people really looking for from a book like this and this level of clarity is right on the money for me.After working through some of the typical data sources and how they work we move on processing and preprocessing the data. You’ll covers time series basics as well as setting your configurations for how the data is handled, handling poor/missing data and making conversions where necessary to get a good data set that can be used to visualise upon using approaches such as candlestick charts.The next phase of the book goes deeper into analysis and dashboarding using popular libraries like Streamlit here you get enough knowledge to build simple web apps and can easily pickup the official docs to expand your knowledge if you’re looking to add further complexities or component types. You then move in to ML based approaches to forecasting with time series datasets and MonteCarlo simulations.Asset allocation is not a key strength for me so I enjoyed exploiting this section and would like to read it again and further texts to bolster my understanding.The latter sections again deal with more advanced topics that I got to expand on the knowledge I had. Again this compounded my enjoyment to the What it is, how it works, what else do you need to know approach to the topics.Overall this book covers a wealth of knowledge from beginner concepts to really quite advanced, I would more say it is aimed at those who already have some knowledge and skills with finance and python already. The motivated beginner could work through it but if you are experienced the structure of the book will probably resonate with you better. Overall I found it a fascinating read and would expect to read it again for areas that I am stuck unsure of or where I get a little rusty. A title that can certainly justify claiming some space on your bookshelf. 4.5 stars.

Having just started as a Junior Data Scientist this book was really helpful for time series analysis and forecasting. It's not for beginners you need to have some basic understanding of Python and data analysis to get the most out of this book. I don't work in the Finance industry but it was nice to learn more about financial data.

Eryk Lewinson has just made time-series analysis much more simplified, it's impossible to make such a complicated topic so interesting!Though the book requires some kind of expertise in Python and Statistics it's worth the price!It's an Effective recipe for easy finance!