Comments (3)
Ah thanks for the info. That makes sense.
The scraping script does not support non-standard structures like this. I may accept a Pull Request if someone wants to improve the code, but I am very unlikely to implement this myself.
Sorry.
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Glad you like it. Rdatasets only includes standard rectangular data frames in CSV format.
Is that a weird map object?
from rdatasets.
Actually it is a list of 13 dataframes, so it might be considered as a group of CSV files all with x
and y
columns:
> library(HistData)
> str(Snow.polygons)
List of 13
$ 1 :'data.frame': 5 obs. of 2 variables:
..$ x: num [1:5] 3.39 10.3 9.68 3.39 3.39
..$ y: num [1:5] 16.3 16.4 18.7 18.7 16.3
$ 2 :'data.frame': 5 obs. of 2 variables:
..$ x: num [1:5] 10.3 11.19 12.54 9.68 10.3
..$ y: num [1:5] 16.4 15.9 18.7 18.7 16.4
$ 3 :'data.frame': 6 obs. of 2 variables:
..$ x: num [1:6] 11.2 11.8 15.1 13.8 12.5 ...
..$ y: num [1:6] 15.9 14.7 14.3 18.7 18.7 ...
$ 4 :'data.frame': 7 obs. of 2 variables:
..$ x: num [1:7] 15.1 16.6 16.8 19.9 19.9 ...
..$ y: num [1:7] 14.3 13.7 13.7 15.3 18.7 ...
$ 5 :'data.frame': 7 obs. of 2 variables:
..$ x: num [1:7] 3.39 11.21 11.79 11.19 10.3 ...
..$ y: num [1:7] 13.4 14 14.7 15.9 16.4 ...
$ 6 :'data.frame': 6 obs. of 2 variables:
..$ x: num [1:6] 3.39 6.17 10.16 11.21 3.39 ...
..$ y: num [1:6] 8.83 8.88 10.23 14.02 13.4 ...
$ 7 :'data.frame': 8 obs. of 2 variables:
..$ x: num [1:8] 10.2 11.8 14.3 16.6 15.1 ...
..$ y: num [1:8] 10.23 9.52 10.16 13.69 14.27 ...
$ 8 :'data.frame': 6 obs. of 2 variables:
..$ x: num [1:6] 12.5 12.65 11.75 10.16 6.17 ...
..$ y: num [1:6] 4.36 4.7 9.52 10.23 8.88 ...
$ 9 :'data.frame': 5 obs. of 2 variables:
..$ x: num [1:5] 12.6 15.6 14.3 11.8 12.6
..$ y: num [1:5] 4.7 7.21 10.16 9.52 4.7
$ 10:'data.frame': 6 obs. of 2 variables:
..$ x: num [1:6] 15.6 18.2 16.8 16.6 14.3 ...
..$ y: num [1:6] 7.21 6.95 13.75 13.69 10.16 ...
$ 11:'data.frame': 5 obs. of 2 variables:
..$ x: num [1:5] 18.2 19.9 19.9 16.8 18.2
..$ y: num [1:5] 6.95 5.87 15.28 13.75 6.95
$ 12:'data.frame': 8 obs. of 2 variables:
..$ x: num [1:8] 12.6 12.5 12.5 19.9 19.9 ...
..$ y: num [1:8] 4.7 4.36 3.23 3.23 5.87 ...
$ 13:'data.frame': 6 obs. of 2 variables:
..$ x: num [1:6] 3.39 12.49 12.5 6.17 3.39 ...
..$ y: num [1:6] 3.23 3.23 4.36 8.88 8.83 ...
If included in your list, that could be collapsed using:
> library(dplyr)
> library(HistData)
> snow_polygons <- bind_rows(Snow.polygons, .id = "polygon")
> head(snow_polygons, 10)
polygon x y
221...1 1 3.390000 16.32146
22...2 1 10.296353 16.42222
19...3 1 9.678367 18.72500
4...4 1 3.390000 18.72500
2211 1 3.390000 16.32146
191 2 10.296353 16.42222
18...7 2 11.194356 15.85294
181...8 2 12.542312 18.72500
19...9 2 9.678367 18.72500
1911 2 10.296353 16.42222
Cheers
from rdatasets.
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from rdatasets.