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Record Nr. |
UNINA9910300364303321 |
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Autore |
Humber Max |
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Titolo |
Personal Finance with Python [[electronic resource] ] : Using pandas, Requests, and Recurrent / / by Max Humber |
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Pubbl/distr/stampa |
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Berkeley, CA : , : Apress : , : Imprint : Apress, , 2018 |
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ISBN |
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Edizione |
[1st ed. 2018.] |
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Descrizione fisica |
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1 online resource (XVI, 117 p. 36 illus.) |
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Disciplina |
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Soggetti |
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Python (Computer program language) |
Personal finance |
Pension plans |
Programming languages (Electronic computers) |
Python |
Personal Finance/Wealth Management/Pension Planning |
Programming Languages, Compilers, Interpreters |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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1. Setup -- 2. Profit -- 3. Convert -- 4. Amortize -- 5. Budget -- 6. Invest -- 7. Spend -- Next. |
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Sommario/riassunto |
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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 |
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• 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. |
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