## -----------------------------------------------------------------------------
library(wikilake)

## ----category url, eval = FALSE-----------------------------------------------
#  res <- WikipediR::page_info("en", "wikipedia",
#    page = "Category:Lakes of Michigan")

## ----scrape names, eval = FALSE-----------------------------------------------
#  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, eval = FALSE------------------------------------------
#  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, eval = FALSE----------------------------------------------
#  res <- lapply(res, lake_wiki)
#  
#  # remove missing coordinates
#  res <- res[unlist(lapply(res, function(x) !is.na(x[, "Lat"])))]

## ----collapse list to data.frame, eval = FALSE--------------------------------
#  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
#  }

## ----echo=FALSE, eval=FALSE---------------------------------------------------
#  good_cols <- data.frame(as.numeric(as.character(apply(res_df,
#    2, function(x) sum(!is.na(x))))))
#  good_cols <- cbind(good_cols, names(res_df))
#  good_cols <- good_cols[good_cols[, 1] > 20, 2]
#  good_cols <- as.character(good_cols)
#  
#  res_df <- res_df[, good_cols]

## ----echo = FALSE-------------------------------------------------------------
data(milakes)
res_df <- milakes

## ----map lakes, fig.height=6,fig.align="center"-------------------------------
library(sp)

coordinates(res_df) <- ~ Lon + Lat
map("state", region = "michigan", mar = c(0, 0, 0, 0))
points(res_df, col = "red", pch = 19)

## ----lake depth distribution--------------------------------------------------
hist(log(res_df$`Max. depth`), main = "", xlab = "Max depth (log(m))")