Generate list of Michigan Lakes
Get Wikipedia URL of Category
res <- WikipediR::page_info("en", "wikipedia",
page = "Category:Lakes of Michigan")Scrape lake names
res <- xml2::read_html(res$query$pages[[1]]$canonicalurl)
res <- rvest::html_nodes(res, "#mw-pages .mw-category")
res <- rvest::html_nodes(res, "li")
res <- rvest::html_nodes(res, "a")
res <- rvest::html_attr(res, "title")Remove junk names
res <- res[!(seq_len(length(res)) %in% grep("List", res))]
res <- res[!(seq_len(length(res)) %in% grep("Watershed", res))]
res <- res[!(seq_len(length(res)) %in% grep("lakes", res))]
res <- res[!(seq_len(length(res)) %in% grep("Mud Lake", res))]Scrape tables
res <- lapply(res, lake_wiki)
# remove missing coordinates
res <- res[unlist(lapply(res, function(x) !is.na(x[, "Lat"])))]Collapse list to data.frame
res_df_names <- unique(unlist(lapply(res, names)))
res_df <- data.frame(matrix(NA, nrow = length(res),
ncol = length(res_df_names)))
names(res_df) <- res_df_names
for (i in seq_len(length(res))) {
dt_pad <- data.frame(matrix(NA, nrow = 1,
ncol = length(res_df_names) - ncol(res[[i]])))
names(dt_pad) <- res_df_names[!(res_df_names %in% names(res[[i]]))]
dt <- cbind(res[[i]], dt_pad)
dt <- dt[, res_df_names]
res_df[i, ] <- dt
}Map lakes
library(sp)
coordinates(res_df) <- ~ Lon + Lat
map("state", region = "michigan", mar = c(0, 0, 0, 0))
points(res_df, col = "red", pch = 19)
hist(log(res_df$`Max. depth`), main = "", xlab = "Max depth (log(m))")