Package 'pubDashboard' reference manual

Title:	Creating Publication Data Visualization Dashboards
Description:	Package to facilitate the creation of data visualization dashboards through the flexdashboard and openalexR packages.
Authors:	Rémi Thériault [aut, cre]
Maintainer:	Rémi Thériault <[email protected]>
License:	GPL (>= 3)
Version:	0.0.1
Built:	2024-11-18 02:53:35 UTC
Source:	https://github.com/rempsyc/pubDashboard

Add regions to pubDashboard dataframe

Description

Add regions to pubDashboard dataframe

Usage

add_region(data, progress_bar = FALSE)
add_region(data, progress_bar = FALSE)

Arguments

`data`	The dataframe on which to add region.
`progress_bar`	Logical, whether to print a progress bar.

Examples

## Not run: 
x <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1, per_page = 1)
x <- add_region(x)
names(x)

## End(Not run)
## Not run: 
x <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1, per_page = 1)
x <- add_region(x)
names(x)

## End(Not run)

Clean dataframe, for names of journals and continents

Description

Clean dataframe, for names of journals and continents

Usage

clean_journals_continents(data, progress_bar = FALSE)
clean_journals_continents(data, progress_bar = FALSE)

Arguments

`data`	The processed dataframe of data
`progress_bar`	Logical, whether to print a progress bar.

Examples

## Not run: 
x <- fetch_openalex_pubs(journal_name = "Collabra",
  pages = 1, per_page = 1, publication_year = 2024)
x <- clean_journals_continents(x)
names(x)

## End(Not run)
## Not run: 
x <- fetch_openalex_pubs(journal_name = "Collabra",
  pages = 1, per_page = 1, publication_year = 2024)
x <- clean_journals_continents(x)
names(x)

## End(Not run)

List of countries taken from the package `countrycode`

Description

List of countries taken from the package countrycode

Usage

countries
countries

Format

A vector of class character containing country names.

Detect missing journals

Description

Detect missing journals

Usage

detect_missing_journals(data)
detect_missing_journals(data)

Arguments

data

The processed dataframe of data

Generate a dygraph of journal paper percentages, by country and year

Description

Generate a dygraph of journal paper percentages, by country and year

Usage

dygraph_year(data, level = "continent")
dygraph_year(data, level = "continent")

Arguments

`data`	The processed dataframe of data
`level`	Level of analysis, either country or continent

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
dygraph_year(data)
dygraph_year(data, "country")

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
dygraph_year(data)
dygraph_year(data, "country")

## End(Not run)

Downloads relevant publication data using `openalexR`

Description

Downloads relevant publication data using openalexR

Usage

fetch_openalex_pubs(
  journal_name = NULL,
  journal_id = NULL,
  clean_journals_continents = FALSE,
  progress_bar = FALSE,
  verbose = TRUE,
  ...
)
fetch_openalex_pubs(
  journal_name = NULL,
  journal_id = NULL,
  clean_journals_continents = FALSE,
  progress_bar = FALSE,
  verbose = TRUE,
  ...
)

Arguments

`journal_name`	The list of desired journals (by journal name).
`journal_id`	The list of desired journals (by OpenAlex ID).
`clean_journals_continents`	Logical, whether to also process the dataframe with the clean_journals_continents function. It is set to FALSE by default because on large datasets it can be very time consuming.
`progress_bar`	Logical, whether to print a progress bar.
`verbose`	Passed to `openalexR::oa_fetch()` and defaults to `TRUE.`
`...`	Arguments passed to `openalexR::oa_fetch()`

Details

As recommended by the authors of the openalexR package,

Before we go any further, we highly recommend you set openalexR.mailto option so that your requests go to the polite pool for faster response times. If you have OpenAlex Premium, you can add your API key to the openalexR.apikey option as well. These lines best go into .Rprofile with file.edit("~/.Rprofile").

options(openalexR.mailto = "[email protected]")
options(openalexR.apikey = "EXAMPLE_APIKEY")"

Examples

## Not run: 
x <- fetch_openalex_pubs(journal_name = "Collabra",
  pages = 1, per_page = 1, publication_year = 2024)
names(x)
# Same as:
x <- fetch_openalex_pubs(journal_id = "S4210175756",
  pages = 1, per_page = 1, publication_year = 2024)
names(x)

## End(Not run)
## Not run: 
x <- fetch_openalex_pubs(journal_name = "Collabra",
  pages = 1, per_page = 1, publication_year = 2024)
names(x)
# Same as:
x <- fetch_openalex_pubs(journal_id = "S4210175756",
  pages = 1, per_page = 1, publication_year = 2024)
names(x)

## End(Not run)

Extract `openalexR` journal ID from journal names

Description

Extract openalexR journal ID from journal names

Usage

get_journal_id(journal_name, verbose = TRUE)
get_journal_id(journal_name, verbose = TRUE)

Arguments

`journal_name`	The list of desired journals (by journal name).
`verbose`	Passed to `openalexR::oa_fetch()` and defaults to `TRUE.`

Details

As recommended by the authors of the openalexR package,

options(openalexR.mailto = "[email protected]")
options(openalexR.apikey = "EXAMPLE_APIKEY")"

Examples

## Not run: 
x <- get_journal_id(journal_name = "Collabra")
x
x <- get_journal_id(journal_name = c(
  "Social Psychological and Personality Science", "Nature Human Behaviour"))
x$id

## End(Not run)
## Not run: 
x <- get_journal_id(journal_name = "Collabra")
x
x <- get_journal_id(journal_name = c(
  "Social Psychological and Personality Science", "Nature Human Behaviour"))
x$id

## End(Not run)

List of academic journals and corresponding fields

Description

List of academic journals and corresponding fields

Usage

journal_field
journal_field

Format

A data frame with 60 rows and 5 variables:

journal: academic journal
journal_abbr: abbreviation of the journal name
openalex_id: the OpenAlex ID
field: the field of research
original_journal: Whether it is part of one of the six original journals

...

Loop `fetch_openalex_pubs` over journals or years

Description

Loop fetch_openalex_pubs over journals or years

Usage

lapply_fetch_openalex_pubs(
  years = 1987:2023,
  journal_id,
  over = "year",
  from_publication_date = "1987-01-01",
  save = TRUE,
  file_suffix = "",
  verbose = TRUE,
  ...
)
lapply_fetch_openalex_pubs(
  years = 1987:2023,
  journal_id,
  over = "year",
  from_publication_date = "1987-01-01",
  save = TRUE,
  file_suffix = "",
  verbose = TRUE,
  ...
)

Arguments

`years`	Desired list to loop over (for option `over = "year"`).
`journal_id`	The list of desired journals (by OpenAlex ID).
`over`	Looping over what. Options are `"year"` or `"journal"`.
`from_publication_date`	Start date (for option `over = "journal"`).
`save`	Whether to save the data to disk.
`file_suffix`	What suffix to add to the file (e.g., "_new").
`verbose`	Passed to `openalexR::oa_fetch()` and defaults to `TRUE.`
`...`	Arguments passed to `openalexR::oa_fetch()`

Details

As recommended by the authors of the openalexR package,

options(openalexR.mailto = "[email protected]")
options(openalexR.apikey = "EXAMPLE_APIKEY")"

Examples

## Not run: 
lapply_fetch_openalex_pubs(
  over = "journal",
  journal_id = c("https://openalex.org/S90392387",
                 "https://openalex.org/S33443600"),
 from_publication_date = "2024-01-01",
 to_publication_date = "2024-10-15",
 save = FALSE)

## End(Not run)
## Not run: 
lapply_fetch_openalex_pubs(
  over = "journal",
  journal_id = c("https://openalex.org/S90392387",
                 "https://openalex.org/S33443600"),
 from_publication_date = "2024-01-01",
 to_publication_date = "2024-10-15",
 save = FALSE)

## End(Not run)

Read local pubDashboard data files and bind them in a single dataframe

Description

Read local pubDashboard data files and bind them in a single dataframe

Usage

read_bind_all_data(data_folder = "data", check_duplicate = FALSE)
read_bind_all_data(data_folder = "data", check_duplicate = FALSE)

Arguments

`data_folder`	The folder in which the data lives
`check_duplicate`	whether to check article ids with rempsyc::best_duplicate

Render complete pubDashboard dashboard

Description

Render complete pubDashboard dashboard

Usage

render_dashboard(
  file_name = "dashboard",
  title = "title",
  author = "author",
  journal_name = NULL,
  journal_id = NULL,
  data_folder = "data",
  tab_continent = TRUE,
  tab_continent_year = TRUE,
  tab_continent_journal = TRUE,
  tab_country = TRUE,
  tab_country_journal = TRUE,
  tab_psychology = FALSE,
  tab_economics = FALSE,
  tab_general = FALSE,
  tab_figure1 = FALSE,
  tab_missing = TRUE,
  ...
)
render_dashboard(
  file_name = "dashboard",
  title = "title",
  author = "author",
  journal_name = NULL,
  journal_id = NULL,
  data_folder = "data",
  tab_continent = TRUE,
  tab_continent_year = TRUE,
  tab_continent_journal = TRUE,
  tab_country = TRUE,
  tab_country_journal = TRUE,
  tab_psychology = FALSE,
  tab_economics = FALSE,
  tab_general = FALSE,
  tab_figure1 = FALSE,
  tab_missing = TRUE,
  ...
)

Arguments

`file_name`	Desired file name.
`title`	Desired dashboard title.
`author`	Desired displayed dashboard author.
`journal_name`	The list of desired journals (by journal name).
`journal_id`	The list of desired journals (by OpenAlex ID).
`data_folder`	Folder where to save the data.
`tab_continent`	Whether to render the "Continent" tab.
`tab_continent_year`	Whether to render the "Continent by year" tab.
`tab_continent_journal`	Whether to render the "Continent by journal" tab.
`tab_country`	Whether to render the "Country" tab.
`tab_country_journal`	Whether to render the "Country by journal" tab.
`tab_psychology`	Whether to render the "Psychology" tab.
`tab_economics`	Whether to render the "Economics" tab.
`tab_general`	Whether to render the "General" tab.
`tab_figure1`	Whether to render the "Figure 1" tab.
`tab_missing`	Whether to render the "Missing" tab.
`...`	Arguments passed to `openalexR::oa_fetch()`

Examples


## Not run: 
render_dashboard(
  file_name = "my_dashboard",
  title = "Wonderful Dashboard",
  author = "Rémi Thériault",
  journal_name = c("Journal of Personality and Social Psychology", "Health Psychology"),
  from_publication_date = "2024-01-01",
  tab_figure1 = TRUE
)

## End(Not run)

## Not run: 
render_dashboard(
  file_name = "my_dashboard",
  title = "Wonderful Dashboard",
  author = "Rémi Thériault",
  journal_name = c("Journal of Personality and Social Psychology", "Health Psychology"),
  from_publication_date = "2024-01-01",
  tab_figure1 = TRUE
)

## End(Not run)

Generate table of journal paper percentages, by continent and year

Description

Generate table of journal paper percentages, by continent and year

Usage

scatter_continent_year(
  data,
  method = "lm",
  ymin = 0,
  ymax = 100,
  yby = 20,
  plotly = TRUE,
  citation = NULL,
  citation_size = 15,
  text_size = NULL,
  height = NULL,
  data_formatted = NULL,
  ...
)
scatter_continent_year(
  data,
  method = "lm",
  ymin = 0,
  ymax = 100,
  yby = 20,
  plotly = TRUE,
  citation = NULL,
  citation_size = 15,
  text_size = NULL,
  height = NULL,
  data_formatted = NULL,
  ...
)

Arguments

`data`	The processed dataframe of data
`method`	Which method to use for the regression line, either "lm" (default) or "loess"
`ymin`	Minimum value for y-axis
`ymax`	Maximum value for y-axis
`yby`	Tick increments for y-axis
`plotly`	Logical, whether to use plotly for dynamic data visualization
`citation`	Optionally, a citation to add as a footer
`citation_size`	Font size of the citation
`text_size`	Size of the element_text ggplot2 element
`height`	Height argument of plotly::ggplotly
`data_formatted`	To save time, it is possible to reuse the dataframe used for this function that is generated by `table_continent_year()`.
`...`	Further arguments passed to rempsyc::nice_scatter

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra Psychology", pages = 1)
data <- clean_journals_continents(data)
scatter_continent_year(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra Psychology", pages = 1)
data <- clean_journals_continents(data)
scatter_continent_year(data)

## End(Not run)

Generate table of journal paper percentages, by continent and year

Description

Generate table of journal paper percentages, by continent and year

Usage

scatter_country_year(
  data,
  method = "lm",
  ymin = 0,
  ymax = 100,
  yby = 20,
  plotly = TRUE,
  citation = NULL,
  citation_size = 15,
  text_size = NULL,
  height = NULL,
  data_formatted = NULL,
  ...
)
scatter_country_year(
  data,
  method = "lm",
  ymin = 0,
  ymax = 100,
  yby = 20,
  plotly = TRUE,
  citation = NULL,
  citation_size = 15,
  text_size = NULL,
  height = NULL,
  data_formatted = NULL,
  ...
)

Arguments

`data`	The processed dataframe of data
`method`	Which method to use for the regression line, either "lm" (default) or "loess".
`ymin`	Minimum value for y-axis
`ymax`	Maximum value for y-axis
`yby`	Tick increments for y-axis
`plotly`	Logical, whether to use plotly for dynamic data visualization.
`citation`	Optionally, a citation to add as a footer.
`citation_size`	Font size of the citation.
`text_size`	Size of the element_text ggplot2 element
`height`	Height argument of plotly::ggplotly
`data_formatted`	To save time, it is possible to reuse the dataframe used for this function that is generated by `table_country_year()`.
`...`	Further arguments passed to rempsyc::nice_scatter

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
suppressWarnings(scatter_country_year(data))

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
suppressWarnings(scatter_country_year(data))

## End(Not run)

Generate table of journal paper percentages, by continent and year

Description

Generate table of journal paper percentages, by continent and year

Usage

scatter_figure1(data, method = "lm", original = TRUE, plotly = TRUE, ...)
scatter_figure1(data, method = "lm", original = TRUE, plotly = TRUE, ...)

Arguments

`data`	The processed dataframe of data
`method`	Which method to use for the regression line, either "lm" (default) or "loess".
`original`	Logical; if `TRUE`, attempts to mimic Arnett's (2008) Figure 1 in style.
`plotly`	Logical, whether to use plotly for dynamic data visualization.
`...`	Further arguments passed to rempsyc::nice_scatter

Examples

## Not run: 
journals <- c("Developmental Psychology",
             "Journal of Personality and Social Psychology",
             "Journal of Abnormal Psychology",
             "Journal of Family Psychology",
             "Health Psychology",
             "Journal of Educational Psychology"
)

data <- fetch_openalex_pubs(journal_name = journals, pages = 10)
data <- clean_journals_continents(data)
scatter_figure1(data)

## End(Not run)
## Not run: 
journals <- c("Developmental Psychology",
             "Journal of Personality and Social Psychology",
             "Journal of Abnormal Psychology",
             "Journal of Family Psychology",
             "Health Psychology",
             "Journal of Educational Psychology"
)

data <- fetch_openalex_pubs(journal_name = journals, pages = 10)
data <- clean_journals_continents(data)
scatter_figure1(data)

## End(Not run)

Generate table of journal paper percentages, by continent and year

Description

Generate table of journal paper percentages, by continent and year

Usage

scatter_journal_year(
  data,
  method = "lm",
  ymin = 0,
  ymax = 100,
  yby = 20,
  plotly = TRUE,
  citation = NULL,
  citation_size = 15,
  ncol = 4,
  ...
)
scatter_journal_year(
  data,
  method = "lm",
  ymin = 0,
  ymax = 100,
  yby = 20,
  plotly = TRUE,
  citation = NULL,
  citation_size = 15,
  ncol = 4,
  ...
)

Arguments

`data`	The processed dataframe of data
`method`	Which method to use for the regression line, either "lm" (default) or "loess"
`ymin`	Minimum value for y-axis
`ymax`	Maximum value for y-axis
`yby`	Tick increments for y-axis
`plotly`	Logical, whether to use plotly for dynamic data visualization
`citation`	Optionally, a citation to add as a footer
`citation_size`	Font size of the citation
`ncol`	How many columns for ggplot2::facet_wrap
`...`	Further arguments passed to rempsyc::nice_scatter

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
scatter_journal_year(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
scatter_journal_year(data)

## End(Not run)

Generate table of journal paper percentages, by continent

Description

Generate table of journal paper percentages, by continent

Usage

table_continent(data, datatable = TRUE)
table_continent(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_continent(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_continent(data)

## End(Not run)

Generate table of journal paper percentages, by continent and journals

Description

Generate table of journal paper percentages, by continent and journals

Usage

table_continent_journal(data, datatable = TRUE)
table_continent_journal(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_continent_journal(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_continent_journal(data)

## End(Not run)

Generate table of journal paper percentages, by continent and year

Description

Generate table of journal paper percentages, by continent and year

Usage

table_continent_year(data, datatable = TRUE)
table_continent_year(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_continent_year(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_continent_year(data)

## End(Not run)

Generate table of journal paper percentages, by country

Description

Generate table of journal paper percentages, by country

Usage

table_country(data, datatable = TRUE)
table_country(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_country(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_country(data)

## End(Not run)

Generate table of journal paper percentages, by continent and year

Description

Generate table of journal paper percentages, by continent and year

Usage

table_country_journal(data, datatable = TRUE)
table_country_journal(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_country_journal(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_country_journal(data)

## End(Not run)

Generate table of journal paper percentages, by country and year

Description

Generate table of journal paper percentages, by country and year

Usage

table_country_year(data, datatable = TRUE)
table_country_year(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_country_year(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_country_year(data)

## End(Not run)

Count number of papers per journal, with year range

Description

Count number of papers per journal, with year range

Usage

table_journal_count(data, datatable = TRUE)
table_journal_count(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_journal_count(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_journal_count(data)

## End(Not run)

Generate table of journal paper percentages, by journal, continent and year

Description

Generate table of journal paper percentages, by journal, continent and year

Usage

table_journal_year(data, datatable = TRUE)
table_journal_year(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_journal_year(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
table_journal_year(data)

## End(Not run)

Generate table of journal paper percentages, by country

Description

Generate table of journal paper percentages, by country

Usage

table_missing_country(data, datatable = TRUE)
table_missing_country(data, datatable = TRUE)

Arguments

`data`	The processed dataframe of data
`datatable`	Whether to output a DT::datatable HTML table widget instead of a regular dataframe (defaults to TRUE).

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
data[1, c(4, 6)] <- NA
table_missing_country(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
data[1, c(4, 6)] <- NA
table_missing_country(data)

## End(Not run)

A data frame of university and corresponding country

Description

Obtained from GitHub, and then modified with minor improvements and more universities.

Usage

universities
universities

Format

A data frame with 9420 rows and 2 variables:

country_code: the country code
university: the university

...

Source

https://raw.githubusercontent.com/endSly/world-universities-csv/master/world-universities.csv

List of US states taken from the package `countrycode`

Description

List of US states taken from the package countrycode

Usage

us_states
us_states

Format

A data frame with 50 rows and 3 variables:

state.name: the name of the state
state.abb: the name of the abbreviation
state.regex: the regex for that state

...

Generate a waffle chart of journal paper percentages, by continent (each square = 1% of data)

Description

Generate a waffle chart of journal paper percentages, by continent (each square = 1% of data)

Usage

waffle_continent(
  data,
  citation = NULL,
  citation_size = NULL,
  data_formatted = NULL
)
waffle_continent(
  data,
  citation = NULL,
  citation_size = NULL,
  data_formatted = NULL
)

Arguments

`data`	The processed dataframe of data
`citation`	Optionally, a citation to add as a footer.
`citation_size`	Font size of the citation.
`data_formatted`	To save time, it is possible to reuse the dataframe used for this function that is generated by `table_continent()`.

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Journal of Economic Psychology", pages = 1)
data <- clean_journals_continents(data)
waffle_continent(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Journal of Economic Psychology", pages = 1)
data <- clean_journals_continents(data)
waffle_continent(data)

## End(Not run)

Generate a waffle chart of journal paper percentages, by continent (each square = 1% of data)

Description

Generate a waffle chart of journal paper percentages, by continent (each square = 1% of data)

Usage

waffle_continent_journal(
  data,
  citation = NULL,
  citation_size = NULL,
  journal_abbreviation = TRUE,
  data_formatted = NULL
)
waffle_continent_journal(
  data,
  citation = NULL,
  citation_size = NULL,
  journal_abbreviation = TRUE,
  data_formatted = NULL
)

Arguments

`data`	The processed dataframe of data
`citation`	Optionally, a citation to add as a footer.
`citation_size`	Font size of the citation.
`journal_abbreviation`	Logical, whether to use the journal abbreviation to fit the entire plot, otherwise some journal names can be quite long and accordingly be cropped.
`data_formatted`	To save time, it is possible to reuse the dataframe used for this function that is generated by `table_continent_journal()`.

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra Psychology", pages = 1)
data <- clean_journals_continents(data)
waffle_continent_journal(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra Psychology", pages = 1)
data <- clean_journals_continents(data)
waffle_continent_journal(data)

## End(Not run)

Generate a waffle plot made of country flags

Description

Generate a waffle plot made of country flags

Usage

waffle_country(
  data,
  citation = NULL,
  citation_size = NULL,
  data_formatted = NULL
)
waffle_country(
  data,
  citation = NULL,
  citation_size = NULL,
  data_formatted = NULL
)

Arguments

`data`	The processed dataframe of data
`citation`	Optionally, a citation to add as a footer.
`citation_size`	Font size of the citation.
`data_formatted`	To save time, it is possible to reuse the dataframe used for this function that is generated by `table_country()`.

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
waffle_country(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
waffle_country(data)

## End(Not run)

Generate a waffle chart of journal paper percentages, by continent (each square = 1% of data)

Description

Generate a waffle chart of journal paper percentages, by continent (each square = 1% of data)

Usage

waffle_country_journal(
  data,
  citation = NULL,
  citation_size = NULL,
  journal_abbreviation = TRUE,
  data_formatted = NULL
)
waffle_country_journal(
  data,
  citation = NULL,
  citation_size = NULL,
  journal_abbreviation = TRUE,
  data_formatted = NULL
)

Arguments

`data`	The processed dataframe of data
`citation`	Optionally, a citation to add as a footer.
`citation_size`	Font size of the citation.
`journal_abbreviation`	Logical, whether to use the journal abbreviation to fit the entire plot, otherwise some journal names can be quite long and accordingly be cropped.
`data_formatted`	To save time, it is possible to reuse the dataframe used for this function that is generated by `table_country_journal()`.

Examples

## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
waffle_country_journal(data)

## End(Not run)
## Not run: 
data <- fetch_openalex_pubs(journal_name = "Collabra", pages = 1)
data <- clean_journals_continents(data)
waffle_country_journal(data)

## End(Not run)

List of world capitals taken from the package `maps`

Description

List of world capitals taken from the package maps

Usage

world_capitals
world_capitals

Format

A data frame with 259 rows and 6 variables:

name: the name of the capital
country.etc: the country of the capital
pop: population of the capital
lat: latitude of the capital
long: longitude of the capital
capital: whether it is a capital

...

Package 'pubDashboard'

Help Index

Add regions to pubDashboard dataframe

Description

Usage

Arguments

Examples

Clean dataframe, for names of journals and continents

Description

Usage

Arguments

Examples

List of countries taken from the package countrycode

Description

Usage

Format

Detect missing journals

Description

Usage

Arguments

Generate a dygraph of journal paper percentages, by country and year

Description

Usage

Arguments

Examples

Downloads relevant publication data using openalexR

Description

Usage

Arguments

Details

Examples

Extract openalexR journal ID from journal names

Description

Usage

Arguments

Details

Examples

List of academic journals and corresponding fields

Description

Usage

Format

Loop fetch_openalex_pubs over journals or years

Description

Usage

Arguments

Details

Examples

Read local pubDashboard data files and bind them in a single dataframe

Description

Usage

Arguments

Render complete pubDashboard dashboard

Description

Usage

Arguments

Examples

Generate table of journal paper percentages, by continent and year

Description

Usage

Arguments

Examples

Generate table of journal paper percentages, by continent and year

Description

Usage

Arguments

Examples

Generate table of journal paper percentages, by continent and year

Description

Usage

Arguments

Examples

Generate table of journal paper percentages, by continent and year

Description

Usage

Arguments

Examples

Generate table of journal paper percentages, by continent

Description

Usage

Arguments

List of countries taken from the package `countrycode`

Downloads relevant publication data using `openalexR`

Extract `openalexR` journal ID from journal names

Loop `fetch_openalex_pubs` over journals or years

List of US states taken from the package `countrycode`