Personal Finance with Python : Using pandas, Requests, and Recurrent Paperback - 2018
by Max Humber
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- Paperback
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Details
- Title Personal Finance with Python : Using pandas, Requests, and Recurrent
- Author Max Humber
- Binding Paperback
- Condition New
- Pages 117
- Volumes 1
- Language ENG
- Publisher Apress
- Publication date 2018-07-21
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # ria9781484238011_inp
- ISBN 9781484238011 / 148423801X
- Weight 0.44 lbs (0.20 kg)
- Dimensions 9.21 x 6.14 x 0.29 in (23.39 x 15.60 x 0.74 cm)
- Category Computers - Languages / Programming
- Dewey Decimal Code 005.13
- Quantity available 64
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From the publisher
From the rear cover
Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively mix the two together.
In Personal Finance with Python you will learn Python and finance at the same time by creating a profit calculator, a currency converter, an amortization schedule, a budget, a portfolio rebalancer, and a purchase forecaster. Many of the examples use pandas, the main data manipulation tool in Python. Each chapter is hands-on, self-contained, and motivated by fun and interesting examples.
Although this book assumes a minimal familiarity with programming and the Python language, if you don't have any, don't worry. Everything is built up piece-by-piece and the first chapters are conducted at a relaxed pace. You'll need Python 3.6 (or above) and all of the setup details are included.
You will:
- Work with data in pandas- Calculate Net Present Value and Internal Rate Return- Query a third-party API with Requests- Manage secrets- Build efficient loops- Parse English sentences with Recurrent- Work with the YAML file format- Fetch stock quotes and use Prophet to forecast the future
In Personal Finance with Python you will learn Python and finance at the same time by creating a profit calculator, a currency converter, an amortization schedule, a budget, a portfolio rebalancer, and a purchase forecaster. Many of the examples use pandas, the main data manipulation tool in Python. Each chapter is hands-on, self-contained, and motivated by fun and interesting examples.
Although this book assumes a minimal familiarity with programming and the Python language, if you don't have any, don't worry. Everything is built up piece-by-piece and the first chapters are conducted at a relaxed pace. You'll need Python 3.6 (or above) and all of the setup details are included.
You will:
- Work with data in pandas- Calculate Net Present Value and Internal Rate Return- Query a third-party API with Requests- Manage secrets- Build efficient loops- Parse English sentences with Recurrent- Work with the YAML file format- Fetch stock quotes and use Prophet to forecast the future
