25% of the book read (chapter 1 to 4)
As I am mainly interested in interactive maps I will pause for the moment with publishing further personal learning material to {plotly}.
WATCH OUT: This is my personal learning material and is therefore neither an accurate replication nor an authoritative textbook.
I am writing this book as a text for others to read because that forces me to become explicit and explain all my learning outcomes more carefully. Please keep in mind that this text is not written by an expert but by a learner.
Text passages with content I am already familiar I have skipped. Section of the original text where I needed more in-depth knowledge I have elaborated and added my own comments resulted from my personal research.
Be warned! In spite of replicating most of the content this Quarto book may contain many mistakes. All the misapprehensions and errors are of course my own responsibility.
I want to use interactivity for internet graphics. My main interest is that users are able to select certain features of the figures (e.g., a specific country or a specific year). I am special interested in interactive maps to compare different countries or regions.
I am using the {glossary} package to create links to glossary entries.]
R Code 1 : Load glossary
## 1. Install the glossary package:
## https://debruine.github.io/glossary/
library(glossary)
## If you want to use my glossary.yml file:
## 1. fork my repo
## https://github.com/petzi53/glossary-pb
## 2. Download the `glossary.yml` file from
## https://github.com/petzi53/glossary-pb/blob/master/glossary.yml)
## 3. Store the file on your hard disk
## and change the following path accordingly
glossary::glossary_path("../glossary-pb/glossary.yml")If you hover with your mouse over the double underlined links it opens an window with the appropriate glossary text. Try this example: Anderson-Darling. AT the end of every chapter there is a list of all glossary entries used in the file.
WATCH OUT! Glossary entries are my personal additions and may be incomplete or even wrong!
I have added many of the glossary entries when I was working through other books either taking the text passage of these books I was reading or via an internet recherche from other resources. I have added the source of glossary entry, but sometimes only with an abbreviation. I still need still to provide a key what these abbreviation mean.
Another issue is that I could not manage to provide active links. So you have to copy and paste the URL to find the reference of the glossary entry.
If you fork this repository then the glossary will not work out of the box. Load down the glossary.yml file from my glossary-pb GitHub repo, store it on your hard disk and change the path in the code chunk Listing / Output 1.
In any case I am the only responsible person for this text, especially if I have used code from the resources wrongly or misunderstood a quoted text passage.
I am using the Tidyverse Style Guide with a slight modification: I am using Google’s recommendation to qualify the used namespace. This is important for my learning endeavor: Besides preventing conflicts with functions of identical names from different packages it helps me to learn (or remember) which function belongs to which package. I think this justifies the small overhead and helps to make R code chunks self-sufficient. (No previous package loading, or library calls in the setup chunk.) To foster learning the relation between function and package I embrace the package name with curly brakes and format it in italics.
I am using the package name also for the default installation of base R. This wouldn’t be necessary but it helps me to understand where the base R functions come from. What follows is a list of base R packages of the system library included into every installation and attached (opened) by default:
With the exception of the base R packages I have added a short profile of every package used in this project. Most of the time these profiles are copied text from the package DESCRIPTION file or an accompanying web page. Sometimes I have also added in a separate section my notes about my personal experiences with package usage.
Resource 1 : Resources used for this Quarto book
| term | definition |
|---|---|
| Anderson-Darling | The Anderson-Darling Goodness of Fit Test (AD-Test) is a measure of how well your data fits a specified distribution. It’s commonly used as a test for normality. (<a href="https://www.statisticshowto.com/anderson-darling-test/">Statistics How-To</a>) |
Session Info
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#> ──────────────────────────────────────────────────────────────────────────────