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  Blaarmeersen

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# Je dient eerst onderstaande biliotheken te installeren via # > install.packages(c("rvest", "polite")) # dit is slechts één keer nodig # De bibliotheken inladen doe je via: # > library(rvest, polite) cols <- c("datum", "kwaliteit", "enterococcus", "e_coli", "temp") data <- data.frame(matrix(nrow = 0, ncol = length(cols))) # Data uit een aantal pagina's extraheren for (i in 0:20){ url <- paste0("https://kwaliteitzwemwater.be/nl/blaarmeersen/blaarmeersen-z", "wemsportzone-gent?page=", i) result <- as.data.frame( polite::bow(url) %>% polite::scrape(content="text/html; charset=UTF-8") %>% rvest::html_nodes(".views-table") %>% rvest::html_table()) data <- rbind(data, result[, !(names(result) %in% c("Cyanobacteriën"))]) } colnames(data) <- cols data$temp <- as.numeric(sub(",", ".", data$temp, fixed = TRUE)) data$datum <- as.Date(data$datum, "%d-%m-%Y") # Geef hieronder een antwoord op het gevraagde:
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  Python sandbox

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