emoji_extract_unnest() returns one row per (row, emoji) pair with a count,
dropping rows that contain no emoji. .row_number refers to the position of
the entry in data.
Arguments
- data
A data frame or tibble containing a text column. Grouped data frames are accepted. The verbs that work a row at a time (adding columns, or keeping and expanding rows) carry the grouping through to their result, as
dplyr::mutate()anddplyr::filter()do. The verbs that pool across rows – the counts, the co-occurrence edge lists, the time series – warn that they ignore the grouping and return one corpus-wide answer.- text
The text column to scan, supplied unquoted. Any atomic column is accepted and read as character, so a
factorworks and a numeric,Dateor logical one simply contains no emoji. A list column – or a data-frame column – is refused rather than coerced, because coercing one deparses it and the emoji found would be in the code rather than in your data. What counts as an emoji is the same in every verb; see the Detection section of tidyEmoji for the one case that surprises people, code points that are emoji only when they carryU+FE0F.
Value
A tibble with columns .row_number, .emoji_unicode and
.emoji_count. The columns of data are not carried, so a grouping is
not either – join back on .row_number to recover them.
emoji_extract_nest() keeps your rows, and your grouping, instead.
See also
emoji_extract_nest() for the same emoji as a list-column that
keeps your rows, and emoji_tokens() for one row per occurrence with
metadata attached; emoji_frequency() for corpus-level counts.
Examples
df <- data.frame(text = c("hi \U0001f600\U0001f600", "none", "\U0001f44b"))
emoji_extract_unnest(df, text)
#> # A tibble: 2 × 3
#> .row_number .emoji_unicode .emoji_count
#> <int> <chr> <int>
#> 1 1 😀 2
#> 2 3 👋 1