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https://github.com/rempsyc/pubmeddashboard

Creating PubMed Data Visualization Dashboards
https://github.com/rempsyc/pubmeddashboard

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Creating PubMed Data Visualization Dashboards

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README

        

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```

# pubmedDashboard: Creating PubMed Data Visualization Dashboards

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**This package is now deprecated in favour of the [`pubDashboard`](https://rempsyc.github.io/pubDashboard/) package.**

The goal of `pubmedDashboard` is to facilitate the creation of pretty data visualization dashboards using the `flexdashboard` and `easyPubMed` packages.

## Installation

You can install the development version of `pubmedDashboard` like so:

``` r
# If `remotes` isn't installed, use `install.packages("remotes")`
remotes::install_github("rempsyc/pubmedDashboard")
```

## Basic Examples

`pubmedDashboard` helps parse the address to identify department and university of affiliation, as well as country.

```{r, warning=FALSE}
library(pubmedDashboard)

address <- c(
"Department of Psychology, Cornell University, Ithaca, New York 14853-7601.",
"Dipartimento di Psicologia Generale, Università di Padova, Italy.",
"Universität Mannheim, Federal Republic of Germany.",
"Département de psychologie, Université du Québec à Montréal, Canada."
)

get_affiliation(address, "department")

get_affiliation(address, "university")

get_country(address)
```

## Mega Function

One simple function allows to download the paper data from PubMed, convert the XLM data to a dataframe, extract affiliations, match universities to countries, identify countries and continents, and save the file to disk for later reuse.

```{r example, warning=FALSE}
save_process_pubmed_batch(
pubmed_query_string = "passion [Title/Abstract]",
journal = c("Journal of Personality and Social Psychology", "Health Psychology"),
year_low = 2023,
year_high = 2030
)
```

## Table formatting functions

Various functions allow to prepare DT tables to display specific information, such as journal paper percentages by continent or country.

```{r read_bind_all, message=FALSE}
data <- read_bind_all_data()
```

```{r table_continent, eval = FALSE}
table_continent(data)
```

![](man/figures/table_journal_continent.png)

## Figure formatting functions

```{r waffle_country, warning=FALSE, message=FALSE}
waffle_country(data)
```

## Example Dashboards

The full source-code for these dashboards are available on the corresponding button at the top-right of each dashboard.

### Neglected 95% Dashboard

[![](man/figures/n95.png)](https://remi-theriault.com/dashboards/neglected_95)

### Passion Dashboard

[![](man/figures/passion.png)](https://remi-theriault.com/dashboards/passion)