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Mastering Pandas for Finance

You're reading from Mastering Pandas for Finance Master pandas, an open source Python Data Analysis Library, for financial data analysis

Product type Paperback

Published in May 2015

Publisher Packt

ISBN-13 9781783985104

Length 298 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Author (1):

Michael Heydt

View More author details

Table of Contents (11) Chapters

Preface

1. Getting Started with pandas Using Wakari.io FREE CHAPTER

2. Introducing the Series and DataFrame

3. Reshaping, Reorganizing, and Aggregating

4. Time-series

5. Time-series Stock Data

6. Trading Using Google Trends

7. Algorithmic Trading

8. Working with Options

9. Portfolios and Risk

Index

Index

A

aggregating
- about / Grouping and aggregating, Aggregating
algorithmic trading
- about / The process of algorithmic trading
- process / The process of algorithmic trading
- momentum strategies / Momentum strategies
- mean-reversion strategies / Mean-reversion strategies
- with Zipline / Algo trading with Zipline
American option
- about / The pricing of options
arithmetic operations, on DataFrame
- performing / Arithmetic on a DataFrame

B

Black-Scholes
- used, for pricing of options / The pricing of options with Black-Scholes
- deriving / Deriving the model
- value of cash, determining / The value of the cash to buy
- value of received stock, determining / The value of the stock received
- formulas / The formulas
- implementing, Mibian used / Black-Scholes using Mibian
Boolean selection
- rows, selecting with / Selecting rows using the Boolean selection
box-and-whisker plots
- about / Box-and-whisker plots
buyer
- about / Introducing...

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Authors (1)

Michael Heydt

Michael Heydt

Michael Heydt is an independent consultant, programmer, educator, and trainer. He has a passion for learning and sharing his knowledge of new technologies. Michael has worked in multiple industry verticals, including media, finance, energy, and healthcare. Over the last decade, he worked extensively with web, cloud, and mobile technologies and managed user experiences, interface design, and data visualization for major consulting firms and their clients. Michael's current company, Seamless Thingies , focuses on IoT development and connecting everything with everything. Michael is the author of numerous articles, papers, and books, such as D3.js By Example, Instant Lucene. NET, Learning Pandas, and Mastering Pandas for Finance, all by Packt. Michael is also a frequent speaker at .NET user groups and various mobile, cloud, and IoT conferences and delivers webinars on advanced technologies.

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