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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

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Product type Paperback
Published in May 2015
Publisher Packt
ISBN-13 9781783985104
Length 298 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Toc

Table of Contents (11) Chapters Close

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

Conventions

In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.

Code words in text are shown as follows: "This information can be easily imported into DataFrame using the pd.read_csv() function as follows."

A block of code entered in a Python interpreter is set as follows:

import pandas as pd
df = pd.DataFrame.from_items([('column1', [1, 2, 3])])
print (df)

Any command-line/IPython input or output is written as follows:

In [2]:
   # create a DataFrame with 5 rows and 3 columns
   df = pd.DataFrame(np.arange(0, 15).reshape(5, 3), 
                  index=['a', 'b', 'c', 'd', 'e'], 
                  columns=['c1', 'c2', 'c3'])
   df

Out[2]:
      c1  c2  c3
   a   0   1   2
   b   3   4   5
   c   6   7   8
   d   9  10  11
   e  12  13  14

New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this: "Once dropped, click on the Upload Files button and you will see the following files in your Wakari directory."

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

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