Reader small image

You're reading from  Python for Finance

Product typeBook
Published inApr 2014
Reading LevelBeginner
Publisher
ISBN-139781783284375
Edition1st Edition
Languages
Tools
Right arrow
Author (1)
Yuxing Yan
Yuxing Yan
author image
Yuxing Yan

Yuxing Yan graduated from McGill University with a PhD in finance. Over the years, he has been teaching various finance courses at eight universities: McGill University and Wilfrid Laurier University (in Canada), Nanyang Technological University (in Singapore), Loyola University of Maryland, UMUC, Hofstra University, University at Buffalo, and Canisius College (in the US). His research and teaching areas include: market microstructure, open-source finance and financial data analytics. He has 22 publications including papers published in the Journal of Accounting and Finance, Journal of Banking and Finance, Journal of Empirical Finance, Real Estate Review, Pacific Basin Finance Journal, Applied Financial Economics, and Annals of Operations Research. He is good at several computer languages, such as SAS, R, Python, Matlab, and C. His four books are related to applying two pieces of open-source software to finance: Python for Finance (2014), Python for Finance (2nd ed., expected 2017), Python for Finance (Chinese version, expected 2017), and Financial Modeling Using R (2016). In addition, he is an expert on data, especially on financial databases. From 2003 to 2010, he worked at Wharton School as a consultant, helping researchers with their programs and data issues. In 2007, he published a book titled Financial Databases (with S.W. Zhu). This book is written in Chinese. Currently, he is writing a new book called Financial Modeling Using Excel — in an R-Assisted Learning Environment. The phrase "R-Assisted" distinguishes it from other similar books related to Excel and financial modeling. New features include using a huge amount of public data related to economics, finance, and accounting; an efficient way to retrieve data: 3 seconds for each time series; a free financial calculator, showing 50 financial formulas instantly, 300 websites, 100 YouTube videos, 80 references, paperless for homework, midterms, and final exams; easy to extend for instructors; and especially, no need to learn R.
Read more about Yuxing Yan

Right arrow

Understanding the data types


In the following table, most of the types of data are given:

Data type

Description

Bool

Boolean (True or False) stored as a byte

int

Platform integer (normally either int32 or int64)

int8

Byte (-128 to 127)

int16

Integer (-32768 to 32767)

int32

Integer (-2147483648 to 2147483647)

int64

Integer (9223372036854775808 to 9223372036854775807)

unit8

Unsigned integer (0 to 255)

unit16

Unsigned integer (0 to 65535)

unit32

Unsigned integer (0 to 4294967295)

unit64

Unsigned integer (0 to 18446744073709551615)

float

Short and for float64

float32

Single precision float: sign bit23 bits mantissa; 8 bits exponent

float64

52 bits mantissa

complex

Shorthand for complex128

complex64

Complex number; represented by two 32-bit floats (real and imaginary components)

complex128

Complex number; represented by two 64-bit floats (real and imaginary components)

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Python for Finance
Published in: Apr 2014Publisher: ISBN-13: 9781783284375

Author (1)

author image
Yuxing Yan

Yuxing Yan graduated from McGill University with a PhD in finance. Over the years, he has been teaching various finance courses at eight universities: McGill University and Wilfrid Laurier University (in Canada), Nanyang Technological University (in Singapore), Loyola University of Maryland, UMUC, Hofstra University, University at Buffalo, and Canisius College (in the US). His research and teaching areas include: market microstructure, open-source finance and financial data analytics. He has 22 publications including papers published in the Journal of Accounting and Finance, Journal of Banking and Finance, Journal of Empirical Finance, Real Estate Review, Pacific Basin Finance Journal, Applied Financial Economics, and Annals of Operations Research. He is good at several computer languages, such as SAS, R, Python, Matlab, and C. His four books are related to applying two pieces of open-source software to finance: Python for Finance (2014), Python for Finance (2nd ed., expected 2017), Python for Finance (Chinese version, expected 2017), and Financial Modeling Using R (2016). In addition, he is an expert on data, especially on financial databases. From 2003 to 2010, he worked at Wharton School as a consultant, helping researchers with their programs and data issues. In 2007, he published a book titled Financial Databases (with S.W. Zhu). This book is written in Chinese. Currently, he is writing a new book called Financial Modeling Using Excel — in an R-Assisted Learning Environment. The phrase "R-Assisted" distinguishes it from other similar books related to Excel and financial modeling. New features include using a huge amount of public data related to economics, finance, and accounting; an efficient way to retrieve data: 3 seconds for each time series; a free financial calculator, showing 50 financial formulas instantly, 300 websites, 100 YouTube videos, 80 references, paperless for homework, midterms, and final exams; easy to extend for instructors; and especially, no need to learn R.
Read more about Yuxing Yan