I have a tidygraph and I want to have each location's neighborhood edge data as a list column.

I can easily retrieve the neighborhood as a list column using `igraph::neighborhood()`

but I cannot so easily retrieve edge data in a nested list form.

Take the following example where I retrieve the neighbor as a list

```
library(sf, quietly = TRUE)
#> Linking to GEOS 3.9.1, GDAL 3.2.3, PROJ 7.2.1; sf_use_s2() is TRUE
library(sfnetworks, quietly = TRUE)
library(tidygraph, quietly = TRUE)
#>
#> Attaching package: 'tidygraph'
#> The following object is masked from 'package:stats':
#>
#> filter
net <- as_sfnetwork(roxel)
# get neighbors as a list column
mutate(net, nb = igraph::neighborhood(.G()))
#> # A sfnetwork with 701 nodes and 851 edges
#> #
#> # CRS: EPSG:4326
#> #
#> # A directed multigraph with 14 components with spatially explicit edges
#> #
#> # Node Data: 701 × 2 (active)
#> # Geometry type: POINT
#> # Dimension: XY
#> # Bounding box: xmin: 7.522622 ymin: 51.94151 xmax: 7.546705 ymax: 51.9612
#> geometry nb
#> <POINT [°]> <list>
#> 1 (7.533722 51.95556) <igrph.vs [5]>
#> 2 (7.533461 51.95576) <igrph.vs [4]>
#> 3 (7.532442 51.95422) <igrph.vs [5]>
#> 4 (7.53209 51.95328) <igrph.vs [4]>
#> 5 (7.532709 51.95209) <igrph.vs [4]>
#> 6 (7.532869 51.95257) <igrph.vs [5]>
#> # … with 695 more rows
#> #
#> # Edge Data: 851 × 5
#> # Geometry type: LINESTRING
#> # Dimension: XY
#> # Bounding box: xmin: 7.522594 ymin: 51.94151 xmax: 7.546705 ymax: 51.9612
#> from to name type geometry
#> <int> <int> <chr> <fct> <LINESTRING [°]>
#> 1 1 2 Havixbecker Strasse residential (7.533722 51.95556, 7.533461 51…
#> 2 3 4 Pienersallee secondary (7.532442 51.95422, 7.53236 51.…
#> 3 5 6 Schulte-Bernd-Strasse residential (7.532709 51.95209, 7.532823 51…
#> # … with 848 more rows
```

GOAL: I want associated edge data. The only way I've been able to do this is by creating this custom semi-janky function.

```
# get a variable nested as list from edges
sfn_var_from_edges <- function(var) {
e_df <- .E()
x <- rlang::ensym(var)
res <- tapply(e_df[[x]], e_df[["from"]], FUN = c)
names(res) <- NULL
res
}
```

This works but only when each node has a from value in the edge dataframe. In this case, many of the edges are mutual so the node wont be recorded in a from and to value and the result of `tapply()`

will have fewer observations than nodes.

Using the above structure doesn't work because the sizing is wrong.

```
mutate(net, sfn_var_from_edges(name))
#> Error in `stopifnot()`:
#> ! Problem while computing `..1 = sfn_var_from_edges(name)`.
#> ✖ `..1` must be size 701 or 1, not 494.
#> Run `rlang::last_error()` to see where the error occurred.
```

Here's a working example with the above function

```
library(dplyr)
library(sfdep)
library(tidygraph)
library(sfnetworks)
nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"))
# get a variable nested as list (weights) from edges
sfn_var_from_edges <- function(var) {
e_df <- .E()
x <- rlang::ensym(var)
res <- tapply(e_df[[x]], e_df[["from"]], FUN = c)
names(res) <- NULL
res
}
# cast nc as an sfnetwork
sfn <- nc |>
mutate(nb = st_contiguity(geometry)) |>
st_as_graph(nb)
e_cols <- sfn |>
activate(edges) |>
# calculate edge length
mutate(e_len = edge_length()) |>
# activate nodes to create nb and wt columns
activate(nodes) |>
# create nb and wt columns
mutate(wt = sfn_var_from_edges(e_len)) |>
# cast to tibble
as_tibble()
head(e_cols$wt, 3)
#> [[1]]
#> Units: [m]
#> [1] 32956.24 37369.89 26405.30
#>
#> [[2]]
#> Units: [m]
#> [1] 32956.24 40467.33 29276.62
#>
#> [[3]]
#> Units: [m]
#> [1] 40467.33 41036.56 46884.54 24304.08 49931.95
```

Is anyone aware of a way to get nested edge data for tidygraph objects?