I would like to use osmdata and get the other_tags as explicit columns.
Example code:
library(osmextract)
library(osmdata)
itsleeds = oe_get("ITS Leeds")
oe_get_keys(itsleeds)
I am interested in extracting the other_tags col from itsleeds data.
Thank you.
We can use tidyverse methods to split and reshape the 'other_tags' column into two columns - select the column of interest, with separate_rows expand the data by splitting at the ,, use separate to create two columns 'key', 'value' from the 'other_tags', by splitting at the => and finally remove the double quotes with str_remove_all in those columns
library(osmextract)
library(osmdata)
library(dplyr)
library(tidyr)
library(stringr)
itsleeds %>%
select(other_tags) %>%
separate_rows(other_tags, sep=",") %>%
separate(other_tags, into = c("key", "value"), sep="=>") %>%
mutate(across(c(key, value), str_remove_all, '"'))
-output
Simple feature collection with 297 features and 2 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: -1.562458 ymin: 53.80471 xmax: -1.548076 ymax: 53.81105
Geodetic CRS: WGS 84
# A tibble: 297 x 3
key value geometry
* <chr> <chr> <LINESTRING [°]>
1 <NA> <NA> (-1.560083 53.80855, -1.560152 53.80865, -1.560228 53.80878, -1.560672 53.80962, -1.56...
2 bicycle designated (-1.559709 53.80815, -1.559756 53.80813, -1.559842 53.80812, -1.559919 53.80814, -1.55...
3 foot designated (-1.559709 53.80815, -1.559756 53.80813, -1.559842 53.80812, -1.559919 53.80814, -1.55...
4 website http://woodhousemooronline.com/the-cannon-destroyer/ (-1.5609 53.80851, -1.560663 53.80859, -1.560228 53.80878, -1.560025 53.80903, -1.5599...
5 access permissive (-1.552587 53.80712, -1.552541 53.8072, -1.55251 53.80725, -1.552479 53.8073, -1.55241...
6 lanes 1 (-1.552587 53.80712, -1.552541 53.8072, -1.55251 53.80725, -1.552479 53.8073, -1.55241...
7 oneway yes (-1.552587 53.80712, -1.552541 53.8072, -1.55251 53.80725, -1.552479 53.8073, -1.55241...
8 lanes 1 (-1.551771 53.8073, -1.551929 53.80727, -1.552007 53.80727, -1.552181 53.80728, -1.552...
9 oneway yes (-1.551771 53.8073, -1.551929 53.80727, -1.552007 53.80727, -1.552181 53.80728, -1.552...
10 lanes 2 (-1.552894 53.809, -1.552663 53.8089, -1.55246 53.80881, -1.552261 53.8087)
# … with 287 more rows