Personal Finance with Python (eBook)
XVI, 117 Seiten
Apress (Verlag)
978-1-4842-3802-8 (ISBN)
- 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
Max Humber is a Data Engineer interested in improving finance with technology. He works for Wealthsimple, and previously served as the first data scientist for the online lending platform Borrowell. He has spoken at Pycon, ODSC, PyData, useR, and BigDataX in Colombia, London, Berlin, Brussels, and Toronto.
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.What You'll LearnWork with data in pandasCalculate Net Present Value and Internal Rate ReturnQuery a third-party API with RequestsManage secretsBuild efficient loopsParse English sentences with RecurrentWork with the YAML file formatFetch stock quotes and use Prophet to forecast the futureWho This Book Is ForAnyone interested in Python, personal finance, and/or both! This book is geared towards those who want to manage their money more effectively and to those who just want to learn or improve their Python.
Max Humber is a Data Engineer interested in improving finance with technology. He works for Wealthsimple, and previously served as the first data scientist for the online lending platform Borrowell. He has spoken at Pycon, ODSC, PyData, useR, and BigDataX in Colombia, London, Berlin, Brussels, and Toronto.
Table of Contents 4
About the Author 8
About the Technical Reviewer 9
Introduction 10
Chapter 1: Setup 16
Anaconda 16
nteract 20
pip install 23
Data 23
Chapter 2: Profit 24
Mining 25
ROI 26
IRR 27
=IRR() 27
pandas 30
read_excel 30
xnpv 32
xirr 35
Again! 37
Conclusion 39
Chapter 3: Convert 40
openexchangerates.org 41
Secrets 42
Documentation 43
Encapsulate 46
show_alternative 48
.apply 49
Conclusion 53
Chapter 4: Amortize 54
Banks 55
Amortization 56
Payment 56
Loop A 57
Loop B 61
Functionize 63
Evaluate 64
Conclusion 67
Chapter 5: Budget 68
Dates 68
datetime 70
Timestamp 70
.normalize 71
Horizon 72
Flows 73
Totals 76
Visualization 77
Updating 78
Vacation I 80
English 82
get_dates 84
Fun 86
YAML 89
Functionize 91
Vacation II 92
Loading YAML 94
Conclusion 95
Chapter 6: Invest 96
Trade-Offs 97
Instantiate 97
Prices 102
Orders 103
Deposit 105
Simulate 106
Quotes 107
get_price 110
get_historical 113
Portfolio 115
Rebalance 116
Conclusion 117
Chapter 7: Spend 118
Prophet 118
Purchases 119
Forecast 120
Visualize 122
Conclusion 124
Appendix: Next 125
Index 128
Erscheint lt. Verlag | 20.7.2018 |
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Zusatzinfo | XVI, 117 p. 36 illus. |
Verlagsort | Berkeley |
Sprache | englisch |
Themenwelt | Informatik ► Programmiersprachen / -werkzeuge ► Python |
Recht / Steuern ► Wirtschaftsrecht | |
Wirtschaft ► Betriebswirtschaft / Management ► Finanzierung | |
Schlagworte | Code • Finance • Forecasts • Household finance • Pandas • Personal • price • Python • recurrent • Software • source • Stock |
ISBN-10 | 1-4842-3802-8 / 1484238028 |
ISBN-13 | 978-1-4842-3802-8 / 9781484238028 |
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