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Extending Excel with Python and R

You're reading from  Extending Excel with Python and R

Product type Book
Published in Apr 2024
Publisher Packt
ISBN-13 9781804610695
Pages 344 pages
Edition 1st Edition
Languages
Authors (2):
Steven Sanderson Steven Sanderson
Profile icon Steven Sanderson
David Kun David Kun
Profile icon David Kun
View More author details

Table of Contents (20) Chapters

Preface 1. Part 1:The Basics – Reading and Writing Excel Files from R and Python
2. Chapter 1: Reading Excel Spreadsheets 3. Chapter 2: Writing Excel Spreadsheets 4. Chapter 3: Executing VBA Code from R and Python 5. Chapter 4: Automating Further – Task Scheduling and Email 6. Part 2: Making It Pretty – Formatting, Graphs, and More
7. Chapter 5: Formatting Your Excel Sheet 8. Chapter 6: Inserting ggplot2/matplotlib Graphs 9. Chapter 7: Pivot Tables and Summary Tables 10. Part 3: EDA, Statistical Analysis, and Time Series Analysis
11. Chapter 8: Exploratory Data Analysis with R and Python 12. Chapter 9: Statistical Analysis: Linear and Logistic Regression 13. Chapter 10: Time Series Analysis: Statistics, Plots, and Forecasting 14. Part 4: The Other Way Around – Calling R and Python from Excel
15. Chapter 11: Calling R/Python Locally from Excel Directly or via an API 16. Part 5: Data Analysis and Visualization with R and Python for Excel Data – A Case Study
17. Chapter 12: Data Analysis and Visualization with R and Python in Excel – A Case Study 18. Index 19. Other Books You May Enjoy

Creating a Brownian motion with healthyR.ts

The final time series plot that we are going to showcase is the Brownian motion. Brownian motion, also known as the Wiener process, is a fundamental concept in finance and mathematics that describes the random movement of particles in a fluid. In the context of finance, it is often used to model the price movement of financial instruments such as stocks, commodities, and currencies.

Here are some of the key characteristics of Brownian motion:

  • Randomness: Brownian motion is inherently random. The future direction and magnitude of movement at any point in time cannot be predicted with certainty.
  • Continuous path: The path of a Brownian motion is continuous, meaning that the asset’s price can move smoothly without sudden jumps or gaps.
  • Independent increments: The changes in the asset’s price over non-overlapping time intervals are independent of each other. In other words, the price movement in one interval does...
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