unnest() does not work with data.frame columns.
unnest() works with list column of nested data.frames, but fails with a data.frame column for the same data. Given that this is a common data format (e.g. typical fromJSON() output) it feels like an unnecessary trap for the unaware.
The documentation does specify "list-column" in the title of the documentation, but otherwise this distinction of column-type isn't discussed. It feels to me that a column of nested data.frames is quite likely to be confused with a list column of nested data.frames.
require(jsonlite)
require(tidyr)
require(dplyr)
j = '{
"observations": [{
"id": "a",
"data": {
"count": 49,
"max": 100
}
}, {
"id": "b",
"data": {
"count": 93,
"max": 120
}
}, {
"id": "c",
"data": {
"count": 27,
"max": 88
}
}]
}'
d = fromJSON(j)$observations %>% as_tibble()
glimpse(d)
#> Rows: 3
#> Columns: 2
#> $ id <chr> "a", "b", "c"
#> $ data <df[,2]> <data.frame[3 x 2]>
d %>% unnest(data)
#> Error: Assigned data `map(data[[col]], as_df, col = col)` must be compatible with existing data.
#> x Existing data has 3 rows.
#> x Assigned data has 2 rows.
#> ℹ Only vectors of size 1 are recycled.
d %>% rowwise() %>% mutate(data = list(data)) %>% unnest(data)
#> # A tibble: 3 x 3
#> id count max
#> <chr> <int> <int>
#> 1 a 49 100
#> 2 b 93 120
#> 3 c 27 88
unnest() does not work with data.frame columns.
unnest()works with list column of nested data.frames, but fails with a data.frame column for the same data. Given that this is a common data format (e.g. typicalfromJSON()output) it feels like an unnecessary trap for the unaware.The documentation does specify "list-column" in the title of the documentation, but otherwise this distinction of column-type isn't discussed. It feels to me that a column of nested data.frames is quite likely to be confused with a list column of nested data.frames.