How to modify or create RStudio code snippets

RStudio snippets are very handy when it comes to dealing with repetitive tasks. Here is how to modify RStudio snippets or create a new one.

In my case, there was a problem with the format that I get by using the ts snippet.

Modify RStudio snippets

To change or create new snippet go to Tools -> Global Options -> Code -> Edit Snippets.

After that, I located the ts snippet.

To get my desired date-time format, I replaced the date function with this and saved snippets.

format(Sys.time(), format = "%Y-%m-%d %H:%M:%S")

You can enhance productivity in RStudio by making RProfile modifications. Take a look at this post on how to do that and why.

2 comments on “How to modify or create RStudio code snippets

  1. […] Thank you for reading this and check out this other post on how to modify or create RStudio code snippets. […]

  2. Kevin Martins

    I love the post. most of my snippets are working fine, however, I cannot get a certain nippet to populate when I type the name.

    Do you know if Rstudio snippets have size limitations?
    Is my snippet formatted incorrectly?

    Here is the code. (sorry it’s kind of big.)

    snippet supersense
    sentiment_analysis %
    select(${2:columns}, text)
    sentiment_analysis %
    unnest_tokens(word, text)
    custom_stop <- c("get", "can")
    sentiment_analysis %
    anti_join(get_stopwords()) %>%
    filter(!word %in% custom_stop)
    sentiment_analysis %
    full_join(get_sentiments(“nrc”)) %>%
    group_by(${2:columns}, sentiment) %>%
    summarize(count = n()) %>%
    na.omit() %>%
    pivot_wider(names_from = sentiment, values_from = count) %>%
    mutate(across(everything(), ~ replace_na(.x, 0))) %>%
    ungroup() %>%
    full_join(sentiment_analysis)
    sentiment_analysis %
    full_join(get_sentiments(“afinn”)) %>%
    group_by(${2:columns}) %>%
    summarize(positivity_weights = mean(value, na.rm = TRUE)) %>%
    ungroup() %>%
    full_join(sentiment_analysis)
    sentiment_analysis %
    full_join(get_sentiments(“bing”)) %>%
    group_by(${2:columns}, sentiment) %>%
    summarize(count = n()) %>%
    na.omit() %>%
    pivot_wider(names_from = sentiment, values_from = count) %>%
    mutate(
    across(c(positive, negative), ~ replace_na(.x, 0)),
    positivity_binary = (positive – negative) / sum(positive, negative, na.rm = TRUE)
    ) %>%
    ungroup() %>%
    select(-positive,-negative) %>%
    full_join(sentiment_analysis)${1:dataset} % select(-word) %>%
    distinct() %>%
    full_join(${1:dataset}, by = c(” ${3:samecolumns} “))

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