Applied Math with Python - Blake Rayfield

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Auteur(s) : Blake Rayfield

Editeur : Wiley

Langue : Anglais

Parution : 01/06/2026

Format : Moyen, de 350g à 1kg

Nombre de pages : 288.0

ISBN : 139437075X

Biographie:

BLAKE RAYFIELD, PhD, is an Assistant Professor of Finance at the University of North Florida. He's a Fulbright Specialist with expertise in applying mathematical solutions to common, difficult business problems. His research has appeared in the Journal of Financial Research, the Quarterly Review of Economics and Finance, and the Review of Behavioral Finance.

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Sommaire:

Introduction xix

Part 1: Getting Started

Chapter 1: Introduction to Python for Business Applications 3

Introducing Python for Business 3

Why Python, Not a Spreadsheet? 4

Setting Up Your Tools 5

Install Python with the Anaconda Distribution (Running Python on Your Machine) 5

Launch Jupyter Notebook 6

Cloud-friendly Alternatives 6

The Python Ecosystem 7

What Is a (Jupyter) Notebook? 8

Installing Libraries Locally or in a Notebook 8

Writing Your First Python Script 9

Summary 10

Continue Your Learning 10

Chapter 2: Basic Mathematical Operations in Python 11

Numbers, Variables, and Functions: The Foundations of Business Logic 11

Understanding Variables 12

Arithmetic in Python 13

Working with the math Module 14

Data Types in Python 14

Core Data Types 14

Why Data Types Matter 16

Converting Between Types 17

Business Data Structures: Arrays and Matrices 18

One-dimensional Arrays 18

Matrices: Two-dimensional Arrays 19

Data Manipulation Basics with Pandas 23

Constructing a DataFrame 23

First Looks: head(), info(), describe() 24

Working with Columns and Rows 24

Filtering with Booleans 25

Creating New Columns 25

Grouping and Aggregation 26

Joins and Merges 27

Reshaping: Pivot, Melt, Stack 28

Summary 28

Continue Your Learning 28

Chapter 3: Visualization for Business Decision-making 29

The Landscape of Visualization Tools in Python 29

Visualization Applications: Dashboarding Frameworks 30

Choosing the Right Visualization Tool for Your Work 31

Graphing Basics with Matplotlib 32

Understanding the Structure of a Plot 32

Creating and Working with Plots 33

Customizing Visualizations to Enhance Understanding 35

Plotting Options 36

Creating Effective Visuals to Communicate Business Data 37

Time-series Data and Line Charts 38

Cross-sectional Data and Bar or Pie Charts 38

Relational Data and Scatterplots 39

Other Charts You Can Create 41

Visualizing Trends and Patterns for Business Insights 42

Highlighting Seasonality and Long-term Growth 42

Comparing Categories and Segments 44

Visualizing Cumulative Effects 46

Smoothing Trends with Rolling Averages 47

Line Charts with Confidence Intervals Using Seaborn 49

Analyzing Relationships and Distributions with jointplot 52

Summary 55

Continue Your Learning 55

Part 2: Applying the Math

Chapter 4: Linear Algebra for Business and Finance 59

Working with Vectors and Matrices 59

Understanding Vectors 60

Understanding Matrix 61

Operations with Vectors and Matrices 62

Scalar Multiplication 63

The Dot Product 63

Norms (Vector Lengths) 64

Combining Matrices 64

Slicing Matrices 65

Matrix Multiplication 66

Transpose 67

Creating and Manipulating Vectors (and Matrices) with NumPy 67

Step 1: Compute Asset Returns from Prices 69

Step 2: Portfolio with Constant Weights 70

Step 3: Portfolio with Time-varying Weights 72

Comparing Strategies (Same Math, Different Inputs) 75

Eigenvalues and Eigenvectors: Business Applications 76

What Eigenvalues and Eigenvectors Represent 76

Why Eigenvalues Matter for Long-term Stability 77

Summary 80

Continue Your Learning 80

Chapter 5: Calculus for Business Problem Solving 83

Numerical Differentiation and Integration in Business Analytics 84

The Derivativ...