Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Mastering Pandas for Finance
Mastering Pandas for Finance

Mastering Pandas for Finance: Master pandas, an open source Python Data Analysis Library, for financial data analysis

Arrow left icon
Profile Icon Michael Heydt
Arrow right icon
S$66.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7 (6 Ratings)
Paperback May 2015 298 pages 1st Edition
eBook
S$36.99 S$52.99
Paperback
S$66.99
Subscription
Free Trial
Arrow left icon
Profile Icon Michael Heydt
Arrow right icon
S$66.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7 (6 Ratings)
Paperback May 2015 298 pages 1st Edition
eBook
S$36.99 S$52.99
Paperback
S$66.99
Subscription
Free Trial
eBook
S$36.99 S$52.99
Paperback
S$66.99
Subscription
Free Trial

What do you get with Print?

Product feature icon Instant access to your digital copy whilst your Print order is Shipped
Product feature icon Paperback book shipped to your preferred address
Product feature icon Redeem a companion digital copy on all Print orders
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
OR
Modal Close icon
Payment Processing...
tick Completed

Shipping Address

Billing Address

Shipping Methods
Table of content icon View table of contents Preview book icon Preview Book

Mastering Pandas for Finance

Chapter 2. Introducing the Series and DataFrame

pandas provides a comprehensive set of data structures for working with and manipulating data and performing various statistical and financial analyses. The two primary data structures in pandas are Series and DataFrame. In this chapter, we will examine the Series object and how it extends a NumPy ndarray to provide operations such as indexed data retrieval, axis labeling, and automatic alignment. Then, we will move on to examine how DataFrame extends the capabilities of Series to use columnar/tabular data, which can be of more than one data type.

The intention of this chapter is to be not only a refresher for those with basic familiarity with pandas, but also a means by which someone who is not initiated with pandas can gain enough familiarity with the two data structures and have a good foundation as we move into more finance-related subjects in later chapters. We will not cover all the details of using Series and DataFrame but...

Notebook setup

To utilize the examples in this chapter, we will need to include the following imports and settings in either your IPython or IPython Notebook environment:

In [1]:
   import pandas as pd
   import numpy as np

   pd.set_option('display.notebook_repr_html', False)
   pd.set_option('display.max_columns', 8)
   pd.set_option('display.max_rows', 8)

The main pandas data structures – Series and DataFrame

Several classes for manipulating data are provided by pandas. Of those, we are interested in Series and more interested in DataFrame.

The Series

The Series is the primary building block of pandas and represents a one-dimensional labeled array based on the NumPy ndarray. The Series extends the functionality of the NumPy ndarray by adding an associated set of labels that are used to index the elements of the array. A Series can hold zero or more instances of any single data type.

This labeled index adds significant power to access the elements of the Series over a NumPy array. Instead of simply accessing elements by position, a Series allows access to items through the associated index labels. The index also assists in a feature of pandas referred to as alignment, where operations between two Series are applied to values with identical labels.

The DataFrame

The Series is the basis for data representation and manipulation in pandas,...

The basics of the Series and DataFrame objects

Now let's examine using the Series and DataFrame objects, building up an understanding of their capabilities that will assist us in working with financial data.

Creating a Series and accessing elements

A Series can be created by passing a scalar value, a NumPy array, or a Python dictionary/list to the constructor of the Series object. The following command creates a Series from 100 normally distributed random numbers:

In [2]:
   np.random.seed(1)
   s = pd.Series(np.random.randn(100))
   s

Out[2]:
   0     1.624345
   1    -0.611756
   2    -0.528172
   3    -1.072969
           ...   
   96   -0.343854
   97    0.043597
   98   -0.620001
   99    0.698032
   Length: 100, dtype: float64

Individual elements of a Series can be retrieved using the [] operator of the Series object. The item with the index label 2 can be retrieved using the following code:

In [3]:
   s[2]

Out[3]:
   -0.528171752263

Multiple values can be retrieved using an array...

Reindexing the Series and DataFrame objects

Reindexing in pandas is a process that makes the data present in a Series or DataFrame match with a given set of labels along a particular axis. This is core to the functionalities of pandas as it enables label alignment across multiple objects.

The process of performing a reindex does the following:

  • Reorders existing data to match a set of labels
  • Inserts NaN markers where no data exists for a label
  • Fills missing data for a label using a type of logic (defaulting to adding NaNs)

The following is a simple example of reindexing a Series. The following Series has an index with numerical values, and the index is modified to be alphabetic by simply assigning a list of characters to the .index property, making the values able to be accessed via the character labels in the new index:

In [60]:
   np.random.seed(1)
   s = pd.Series(np.random.randn(5))
   s

Out[60]:
   0    1.624345
   1   -0.611756
   2   -0.528172
   3   -1.072969
   4    0.865408
   dtype...

Summary

In this chapter, we briefly overviewed the pandas Series and DataFrame objects, how they are used to represent data, and how to select data in both via queries, columns, and indices. The concept of reindexing both classes of objects is also introduced, and as we get into the later chapters, it will be common to perform reindexing of time-series data.

In the next chapter, we will examine indexing in more depth with an eye towards how performing various aggregations of data can derive results from the information represented in pandas. As we progress into more specific financial analysis, this combination of reindexing and aggregation will form the basis of much of the analysis performed later in the book.

Left arrow icon Right arrow icon
Download code icon Download Code

Description

If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.

Who is this book for?

If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.

What you will learn

  • Modeling and manipulating financial data using the pandas DataFrame
  • Indexing, grouping, and calculating statistical results on financial information
  • Timeseries modeling, frequency conversion, and deriving results on fixed and moving windows
  • Calculating cumulative returns and performing correlations with index and social data
  • Algorithmic trading and backtesting using momentum and mean reversion strategies
  • Option pricing and calculation of Value at Risk
  • Modeling and optimization of financial portfolios
Estimated delivery fee Deliver to Singapore

Standard delivery 10 - 13 business days

S$11.95

Premium delivery 5 - 8 business days

S$54.95
(Includes tracking information)

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : May 25, 2015
Length: 298 pages
Edition : 1st
Language : English
ISBN-13 : 9781783985104
Category :
Languages :
Concepts :
Tools :

What do you get with Print?

Product feature icon Instant access to your digital copy whilst your Print order is Shipped
Product feature icon Paperback book shipped to your preferred address
Product feature icon Redeem a companion digital copy on all Print orders
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
OR
Modal Close icon
Payment Processing...
tick Completed

Shipping Address

Billing Address

Shipping Methods
Estimated delivery fee Deliver to Singapore

Standard delivery 10 - 13 business days

S$11.95

Premium delivery 5 - 8 business days

S$54.95
(Includes tracking information)

Product Details

Publication date : May 25, 2015
Length: 298 pages
Edition : 1st
Language : English
ISBN-13 : 9781783985104
Category :
Languages :
Concepts :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
$19.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
$199.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just S$6 each
Feature tick icon Exclusive print discounts
$279.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just S$6 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total S$ 208.97
Mastering Pandas for Finance
S$66.99
Python for Finance
S$66.99
Mastering Python for Finance
S$74.99
Total S$ 208.97 Stars icon

Table of Contents

10 Chapters
1. Getting Started with pandas Using Wakari.io Chevron down icon Chevron up icon
2. Introducing the Series and DataFrame Chevron down icon Chevron up icon
3. Reshaping, Reorganizing, and Aggregating Chevron down icon Chevron up icon
4. Time-series Chevron down icon Chevron up icon
5. Time-series Stock Data Chevron down icon Chevron up icon
6. Trading Using Google Trends Chevron down icon Chevron up icon
7. Algorithmic Trading Chevron down icon Chevron up icon
8. Working with Options Chevron down icon Chevron up icon
9. Portfolios and Risk Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7
(6 Ratings)
5 star 0%
4 star 66.7%
3 star 33.3%
2 star 0%
1 star 0%
Filter icon Filter
Top Reviews

Filter reviews by




Amazon Customer Jul 01, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
This book brings together several important concepts in finance and explains how to implement them using a core of Python and pandas. Some of the key topics included in the books are:Wakari.io - a collaborative data analytics platform that allows to explore data and create analytic scripts in collaboration with IPython Notebooks.Introduction to the Series and DataFrame objectsA chapter on Reshaping, Reorganizing, and Aggregating DataCorrelations of Google trends with stock movements, creating algorithmic trading systemsCalculating options payoffs, prices, and behaviorsConstructing an efficient portfolioAn overview of modern portfolio theory and Computing Value at Risk (VaR)I liked that the provided code is in the form of ipython notebook.Disclaimer: I received this eBook as a complementary copy.
Amazon Verified review Amazon
yatgonewest Aug 30, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I would recommend this book as a good basic intro to the fundamentals of Pandas even if you're not particularly interested in applying it to finance. I have read portions of a few others and this authors style is very concise and to the point on Series and DataFrames, and in particular on indexing of both.
Amazon Verified review Amazon
Al Krinker Oct 07, 2016
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I wish I could give it 5 stars, but since this book was poorly edited by tech reviewer that missed many errors, I can't go above 3... The content is great and it def will get you going, but some formulas for example Value at Risk at the very end is incorrect and even in example it is wrong (they forgot the mean!)
Amazon Verified review Amazon
ajk251 Jul 11, 2015
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I found this book to be a useful one - it nicely covers all the pandas/finance basics. If your're a bit of a novice in either one, this book provides a nice introduction. It doesn't waste time with a Python introduction or other book-filling topics. It shows how to do all of the most useful operations in pandas as they relate to finance. Then it goes into options, portfolio theory, and applying pandas to a Google Trends project. I particularly liked the section on Zipline, a back-testing library. It was a little clearer than the documentation. The part where Quandl is used is also nice.That said, if you dug around the internet, you could probably cobble these examples together. Also, it doesn't really go into either pandas or finance too deeply. I don't hold those against the book - it can't be all things to all people. The book makes for a nice overview of the relevant topics - but expect an overview.Note: I was asked to give a review of the book by the publisher in exchange for a free ebook (I purchased the book from the publisher).
Amazon Verified review Amazon
Ho Yan Chan May 02, 2018
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
ok
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is the digital copy I get with my Print order? Chevron down icon Chevron up icon

When you buy any Print edition of our Books, you can redeem (for free) the eBook edition of the Print Book you’ve purchased. This gives you instant access to your book when you make an order via PDF, EPUB or our online Reader experience.

What is the delivery time and cost of print book? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela
What is custom duty/charge? Chevron down icon Chevron up icon

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order? Chevron down icon Chevron up icon

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges? Chevron down icon Chevron up icon

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

  • If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
  • Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.
How can I cancel my order? Chevron down icon Chevron up icon

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy? Chevron down icon Chevron up icon

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

  1. If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
  2. Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
  3. You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
  4. Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
  5. If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
  6. Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged? Chevron down icon Chevron up icon

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use? Chevron down icon Chevron up icon

You can pay with the following card types:

  1. Visa Debit
  2. Visa Credit
  3. MasterCard
  4. PayPal
What is the delivery time and cost of print books? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela