This article is originally published at https://ikashnitsky.github.io/atom.html

SCImago Journal & Country Rank provides valuable estimates of academic journals’ prestige. The data is freely available at the project website and is distributed for deeper analysis in forms of .csv and .xlsx files. I downloaded all the files and pooled them together, ready to be used in R.

Basically, all the package gives you three easily accessible data frames: sjr_journals (Journal Rank), sjr_countries (Country Rank, year-by-year), and sjr_countries_1996_2017 (Country Rank, all years together).

The whole process of data acquisition can be found in the github repo (dev directory) or this gist.

# install
devtools::install_github("ikashnitsky/sjrdata")

# load
library(sjrdata)

# use
View(sjr_countries)

library(tidyverse)
library(sjrdata)

sjr_journals %>%
    filter(title %in% c("Nature", "Science")) %>%
    ggplot(aes(cites_doc_2years, sjr, color = title))+
    geom_path(size = 1, alpha = .5)+
    geom_label(aes(label = year %>% str_sub(3, 4)),
              size = 3, label.padding = unit(.15, "line"))

sjr_journals %>%
    filter(title %in% c(
        "Demography",
        "Population and Development Review",
        "European Journal of Population",
        "Population Studies",
        "Demographic Research",
        "Genus"
    )) %>%
    ggplot(aes(cites_doc_2years, sjr, color = title))+
    geom_point()+
    stat_ellipse()+
    scale_color_brewer(palette = "Dark2")+
    coord_cartesian(expand = F)

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This article is originally published at https://ikashnitsky.github.io/atom.html
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