There’s no official database that I can find to define clearly some of the economic areas in Montreal, at least none that are free. However, wikipedia does seem to be rather well organized in this regard. Small scale scraping to identify FSAs for a particular locale, in the example below, Montérégie or “Rive-Sud” an affluent part of the greater Montreal area.
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library(rvest)
links <- read_html("https://en.wikipedia.org/wiki/South_Shore_(Montreal)") %>%
html_node(css = ".column-count-3") %>%
html_nodes("a") %>%
html_attr("href")
links <- paste0("http://en.wikipedia.org",links)
listing <- list()
for(link in links) {
listing[[link]] <- read_html(link) %>% html_node(".adr") %>% html_text()
}
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So far so good, but it looks like a bit of extra cleaning will be required.
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> listing %>% unlist() %>% as.character %>% strsplit(",") %>% unlist()
[1] "J3G to J3H" "J4B" "J4W to J4Z" "J5R" "J3L"
[6] "J3L" "J6J" " J6K" "J5B" "J0L1B0"
[11] NA "J5R" "J3Y" " J3Z" " J4G to J4N"
[16] " J4T" " J4V" "J4V" "J3Y" " J3Z"
[21] " J4T" NA NA "J3G 6N9" "J3H"
[26] "J3H 2M6" "J3L" "J0L 1N0" "J3N" "J3V"
[31] "J5A" "J0L 2A0" "J3E" "J5C" "J4P"
[36] " J4R" " J4S" "J3L 6Z5" "J0L 2K0" "J3X"
trim <- function (x) gsub("^\\s+|\\s+$", "", x)
listing %>%
unlist() %>%
as.character %>%
strsplit(",") %>%
unlist() %>%
strsplit("to") %>%
unlist %>%
na.omit() %>%
trim %>%
substr(start = 0, stop = 3)
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And we have a list of FSAs for Montérégie pulled from what we hope is a good resource:
J3G
J3H
J4B
J4W
J4Z
J5R
J3L
J3L
J6J
J6K
J5B
J0L
J5R
J3Y
J3Z
J4G
J4N
J4T
J4V
J4V
J3Y
J3Z
J4T
J3G
J3H
J3H
J3L
J0L
J3N
J3V
J5A
J0L
J3E
J5C
J4P
J4R
J4S
J3L
J0L
J3X