I have finished approximately 5%. This is just a rough guess, derived from my Project plan.
Currently I am working on plotting the map for the RWB datasets 2022-2025.
I am writing this book to learn how to develop a Shiny Dashboard. It is a practical project to support my understanding of Mastering Shiny (Wickham 2021). It was helpful that I have written down during reading Mastering Shiny personal notes in Learning Shiny. But this was mostly only a replication exercise. With this project I am trying to develop my practical skills in building Shiny apps.
WATCH OUT: I am a learner not an expert
I am writing this book as a text for others to read because that forces me to become explicit and explain all my considerations and my code lines more carefully. Please keep in mind that this text is not written by an expert but by a learner.
I have some experience with data wrangling using the {tidyverse}. But it is important to stress that I have almost no experience with Shiny apps and much less with building an interactive Dashboard. At the moment (August 2025) I haven’t read neither Engineering Production-Grade Shiny Apps (Fay et al. 2021) nor Outstanding User Interfaces with Shiny (Granjon 2022). So my theoretical and practical knowledge is very limited. Therefore this Quarto book my contain many mistakes. If you find misapprehensions, errors or just better ways to solve my intentions feel free to drop me a note in the GitHub repo of this book.
I decided to develop a dashboard for the dataset on the World Press Freedom Index (WPFI) for this practical learning project. The WPFI was developed by Reporters Without Borders (RWB) (French: Reporters sans frontières) (RSF).
The World Press Freedom Index (WPFI) is an annual ranking of countries compiled and published by Reporters Without Borders (RSF) since 2002 based upon the non-governmental organization’s own assessment of the countries’ press freedom records in the previous year. It intends to reflect the degree of freedom that journalists, news organizations, and netizens have in each country, and the efforts made by authorities to respect this freedom. Reporters Without Borders notes that the WPFI only deals with press freedom and does not measure the quality of journalism in the countries it assesses, nor does it look at human rights violations in general. (Wikipedia)
It is important to note that the questionnaire as well the method to construct the index has changed several times.
These three score methods are not comparable. One way to compare the different years from 2002-2025 is the rank, with the caveat that in the earlier year there are many ties. Another one could be elicited by the five categories using map colors. Starting with 2005 there are colored maps with five colors. But a detailed inspection reveals that the scores and map colors does not match.
Although the score ranges between 2013 and 2025 change with 2021 onwards the content of the categories remain constant. We could therefore compare these countries not only with their global score but also in five sub-categories:
It is symptomatic that the borders for the different categories have been relaxed from 2022 onwards. We will have a look on these differences later to judge if the general distribution of scores has changed (worsened), so that the adaption was made to get similar numbers of countries in each category. But it could also the case that the different sub-criteria after 2021 required this slight adaption. Another reason could be to set the four upper categories to the same range (all have 15 points), whereas they differ between 2013-2021 (20, 10, 10, 15 points).
Although the index construction from 2013 to today has changed in 2022 we can compare not only the ranks but also the amount of points as all these years have the same scale of 0-100 points.
I take as a model for my practical project the Word Happiness Report (WHR) dashboard. I cannot plan the details but my dashboar should contain the following main visualizations:
The start of the dashboard should be a map from the last year where data are available. This is currently 2025. It should be a map quite similar as it is in the original website at https://rsf.org/en/index. As in the original it should also reveal country information whenever the mouse is hovering over a specific country.
The differences to the start view are:
To compare with my WHR model see the WHR Map.
(Looking for a better name, as the ranking graphics are also charts.)
The charts should show the development by year for the
Additionally you can
I am thinking of Connected Scatterplots as graphical device to show the development over the years.
To compare with my WHR model see the WHR Chart.
The charts should show the ranking development of countries / regions by year for the
I am thinking of Lollipop Plots and/or Bump Charts as a graphical devices to show the development of ranks.
Similar to the charts you should also be able to
My WHR model has only a list of ranked countries without any visualization.
Choosing one country or regions displays a summary of all available data for this item. This could be:
I will apply the intermediate results of my code development parallel the Shiny package RSF (Reporters sans frontières). After some research I learned that the {bslib} package is the most modern package fpr dashboard development. I looked into
{bslib} is now the recommendation for Shiny dashboards. See Towards easy, delightful, and customizable dashboards in Shiny for R with {bslib} and {bslib} Dashboardes. The “Mastering Shiny” book does not use {bslib} for its example code. Although I had experimented a little bit with {bslib} I still have to learn to apply the {bslib} package.
An interesting intermediate solution could also trying to apply {flexdashboard} to get a first flavor of my results. I don’t know if this is a viable option because I have never used {flexdashboard} so far.
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: RWB.
WATCH OUT! Glossary is my private learning vehicle
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. Sometimes I have added the source of the glossary entry as an abbreviation or as an URL. Many definitions were provided by the KI provided within the search of my Brave browser.
If you fork the repo of this book 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 accordingly.
In any case I am the only responsible person for the glossary text, especially if I have used text from other resources wrongly. Again: The main purpose of the glossary is to support my personal learning venture.
During coding I am following the Tidyverse Style Guide. But for learning purposes I am trying to prefix all functions with the package name in the format dplyr::filter()) This is an overhead but supports me to understand which packages is responsible for which action.
Sometimes adding just the package name does not work. This is mostly the case when a generic function name like plot is used by another package in a more specialized manner. In this case I will try to use the function of the package. If this doesn’t work too then I have to come back to the standard usage of base::library(<package-name>).
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:
I am not using always the exact code snippets for my replications because I am not only replicating the code to see how it works but also to change the values of parameters to observe their influences.
When it is clear then I will follow the advice from Hadley Wickham:
When you call a function, you typically omit the names of data arguments, because they are used so commonly. If you override the default value of an argument, use the full name (tidyverse style guide).
I am not using code annotation because it disables code linking and does not show up correctly in the pop-up window generated with listing cross references.
In some of my book notes I provide files in the annex. They contain experiments not directly in line with the book but inspired by my reading of the book.
Often you will also find an annex file with a standardized short description of all my used packages, sometimes added with notes about my personal experiences with this package. An example of the standardized format gives you the following Glossary package.
Package Profile: glossary
Add glossaries to markdown and quarto documents by tagging individual words. Definitions can be provided inline or in a separate file.
There is a lot of necessary jargon to learn reading new books. The goal of {glossary} is to provide a lightweight solution for making glossaries in educational materials written in quarto or R Markdown. This package provides functions to link terms in text to their definitions in an external glossary file, as well as create a glossary table of all linked terms at the end of a section.
In the meantime {glossary} is for me a very important learning vehicle. Whenever an expression appears with a doubled underlined link I know that I will get more information by hovering the mouse over the underlined text.
There is a little inconvenience with abrreviation that could also be part of another glossary entry text string (e.g., API and Capital Income). My workaround is to end the short abbreviation with an additional ‘x’ and then to call the glossary with the x-version follwed by the text that should be appear in the document (e.g., r glossary(“APIx”, “API”)). This double format is a standard feature of the {glossary} package so that you can adapt the appearing text to the glossary entry (e.g., singular/plural or other grammar changes).
Resource 1 : Resources used for this Quarto book
XXX: [ADD HERE USED ADDITIONAL SOURCES]
XXX: [DESCRIBE PRIVATE FUNCTION USED IN THIS BOOK]
| term | definition |
|---|---|
| APIx | An API, or application programming interface, is a set of defined rules that enable different applications to communicate with each other. It acts as an intermediary layer that processes data transfers between systems, letting companies open their application data and functionality to external third-party developers, business partners, and internal departments within their companies. (<a href="https://www.ibm.com/topics/api">IBM</a>) |
| Capital Income | Capital income is defined as the sum of property income, including dividends, interest gains, reinvested earnings on foreign direct investment, investment income disbursements and land rents ([Distributional National Accounts (DINA) for Austria, 2004-2016](https://wid.world/document/distributional-national-accounts-dina-for-austria-2004-2016-world-inequality-lab-wp-2020-23/)). |
| RWB | Reporters Without Borders (RWB), known by its French name Reporters sans frontières and acronym RSF, is an international non-profit and non-governmental organization headquartered in Paris, France, founded in 1985 in Montpellier by journalists Robert Ménard, Rémy Loury, Jacques Molénat, and Émilien Jubineau. It is dedicated to safeguarding the right to freedom of information and defends journalists and media personnel who are imprisoned, persecuted, or at risk for their work. The organization has consultative status at the United Nations, UNESCO, the Council of Europe, and the International Organisation of the Francophonie. |
| WHR | The World Happiness Reports are a partnership of Gallup, the Oxford Wellbeing Research Centre, the UN Sustainable Development Solutions Network, and the WHR’s Editorial Board. The report is produced under the editorial control of the WHR Editorial Board. The Reports reflects a worldwide demand for more attention to happiness and well-being as criteria for government policy. It reviews the state of happiness in the world today and shows how the science of happiness explains personal and national variations in happiness. (https://worldhappiness.report/about/) |
| WPFI | The World Press Freedom Index (WPFI) is an annual ranking of countries compiled and published by Reporters Without Borders (RSF), an international non-governmental organization based in France, since 2002. It aims to reflect the degree of freedom that journalists, news organizations, and netizens have in each country, as well as the efforts made by authorities to respect this freedom. The index ranks 180 countries and territories based on RSF's assessment of their press freedom records in the preceding year. |
Session Info
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