## 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")Learning Plotly
Preface
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.
Content and Goals of this Book
NEEDS TO BE FILLED
Text passages
Quotes and personal comments
NEEDS TO BE FILLED
Glossary
I am using the {glossary} package to create links to glossary entries.]
R Code 1 : Load glossary
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.
R Code and Datasets
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:
- {base}: The R Base Package
- {datsets}: The R Datasets Package
- {graphics}: The R Graphics Package
- {grDevices}: The R Graphics Devices and Support for Colours and Fonts
- {methods}: Formal Methods and Classes
- {stats}: The R Stats Package
- {utils}: The R Utils Package
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.
Resources
Resource 1 : Resources used for this Quarto book
- Online: Interactive web-based data visualization with R, plotly, and shiny
- Printed version: Sievert, C. (2019). Interactive web-based data visualization with R, plotly, and shiny. https://plotly-r.com/ (Sievert 2019)
- Plotly JavaScript Open Source Graphing Library
- Plotly R Open Source Graphing Library
- Plotly ggplot2 Open Source Graphing Library
Glossary
| 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
Session Info
Code
sessioninfo::session_info()#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.4.2 (2024-10-31)
#> os macOS Sequoia 15.1
#> system x86_64, darwin20
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Vienna
#> date 2024-11-19
#> pandoc 3.5 @ /usr/local/bin/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> cli 3.6.3 2024-06-21 [2] CRAN (R 4.4.1)
#> colorspace 2.1-1 2024-07-26 [2] CRAN (R 4.4.0)
#> commonmark 1.9.2 2024-10-04 [2] CRAN (R 4.4.1)
#> curl 6.0.0 2024-11-05 [2] CRAN (R 4.4.1)
#> digest 0.6.37 2024-08-19 [2] CRAN (R 4.4.1)
#> evaluate 1.0.1 2024-10-10 [2] CRAN (R 4.4.1)
#> fastmap 1.2.0 2024-05-15 [2] CRAN (R 4.4.0)
#> glossary * 1.0.0.9003 2024-08-05 [2] Github (debruine/glossary@05e4a61)
#> glue 1.8.0 2024-09-30 [2] CRAN (R 4.4.1)
#> htmltools 0.5.8.1 2024-04-04 [2] CRAN (R 4.4.0)
#> htmlwidgets 1.6.4 2023-12-06 [2] CRAN (R 4.4.0)
#> jsonlite 1.8.9 2024-09-20 [2] CRAN (R 4.4.1)
#> kableExtra 1.4.0 2024-01-24 [2] CRAN (R 4.4.0)
#> knitr 1.49 2024-11-08 [2] CRAN (R 4.4.1)
#> lifecycle 1.0.4 2023-11-07 [2] CRAN (R 4.4.0)
#> magrittr 2.0.3 2022-03-30 [2] CRAN (R 4.4.0)
#> markdown 1.13 2024-06-04 [2] CRAN (R 4.4.0)
#> munsell 0.5.1 2024-04-01 [2] CRAN (R 4.4.0)
#> R6 2.5.1 2021-08-19 [2] CRAN (R 4.4.0)
#> rlang 1.1.4 2024-06-04 [2] CRAN (R 4.4.0)
#> rmarkdown 2.29 2024-11-04 [2] CRAN (R 4.4.1)
#> rstudioapi 0.17.1 2024-10-22 [2] CRAN (R 4.4.1)
#> rversions 2.1.2 2022-08-31 [2] CRAN (R 4.4.0)
#> scales 1.3.0 2023-11-28 [2] CRAN (R 4.4.0)
#> sessioninfo 1.2.2 2021-12-06 [2] CRAN (R 4.4.0)
#> stringi 1.8.4 2024-05-06 [2] CRAN (R 4.4.0)
#> stringr 1.5.1 2023-11-14 [2] CRAN (R 4.4.0)
#> svglite 2.1.3 2023-12-08 [2] CRAN (R 4.4.0)
#> systemfonts 1.1.0 2024-05-15 [2] CRAN (R 4.4.0)
#> vctrs 0.6.5 2023-12-01 [2] CRAN (R 4.4.0)
#> viridisLite 0.4.2 2023-05-02 [2] CRAN (R 4.4.0)
#> xfun 0.49 2024-10-31 [2] CRAN (R 4.4.1)
#> xml2 1.3.6 2023-12-04 [2] CRAN (R 4.4.0)
#> yaml 2.3.10 2024-07-26 [2] CRAN (R 4.4.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/4.4-x86_64/library
#> [2] /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library
#>
#> ──────────────────────────────────────────────────────────────────────────────References
Sievert, Carson. 2019. Interactive Web-Based Data Visualization with r, Plotly, and Shiny. https://plotly-r.com/.