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Survey of R users on package discovery 📦
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packagesurvey: Navigating the R package universe

Author: Julia Silge
License: MIT

Build Status

There are now more than 11,000 packages on CRAN, and R users must approach this abundance of packages with effective strategies to find what they need and choose which packages to invest time in learning how to use. At useR!2017, I contributed to an organized session focused on discovering, learning about, and evaluating R packages. In preparation for that session, I ran a brief online survey in the spring of 2017 to ask R users how they currently discover and learn about R packages. This package contains the results of that survey.


This package can be install from GitHub using devtools.



The survey results are available in this package in the package_survey data object.


There were 1039 respondents to the survey. You can easily explore how many respondents chose each answer.


package_survey %>%
    mutate(total = n_distinct(respondent)) %>%
    count(answer, total) %>%
    arrange(desc(n)) %>%
    mutate(proportion = scales::percent(n / total)) %>% 
    select(-total, -n) %>%
    kable(col.names = c("How do you currently discover and learn about R packages",
                        "% of respondents who chose each answer"))
How do you currently discover and learn about R packages % of respondents who chose each answer
Social media such as blogs, R-bloggers, Twitter, Slack, or GitHub contacts 79.8%
General search websites such as Google and Yahoo 57.0%
Your personal network, such as colleagues and professors 41.6%
Books, textbooks, or journal articles (JSS, JOSS, R-Journal) 31.9%
Conferences, meet-ups, or seminars 24.1%
CRAN Task Views 21.8%
Email lists such as r-help, r-packages, or r-pkg-devel 15.3%
R-specific search websites such as METACRAN ( or Rdocumentation ( 11.1%
Other (send ideas to @juliasilge on Twitter!) 4.2%
R packages built for search such as the sos package 2.2%

You might also be interested in when R users responded to the survey.

package_survey %>%
    distinct(respondent, .keep_all = TRUE) %>%
    ggplot(aes(response_time)) +
    geom_histogram() +
    labs(x = NULL,
         y = "Number of R users",
         title = "Responses to survey on package discovery over time")

plot of chunk unnamed-chunk-4

This project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

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