#' Function to check for repeated and wrong entries in the table
check_integrity_table <- function(ids_table) {
# check for certificates with different emails
# check for hashes associated with different emails
repeated_id_hashes <- id_table %>%
dplyr::select(id) %>%
dplyr::group_by(id) %>%
dplyr::summarise(num = dplyr::n()) %>%
dplyr::ungroup() %>%
dplyr::arrange(-num) %>%
dplyr::filter(num > 1) %>%
dplyr::pull(id)
if (isTRUE(length(repeated_id_hashes) > 0)) {
id_table %>%
dplyr::filter(id %in% repeated_id_hashes) %>%
dplyr::distinct() %>%
dplyr::arrange(email) %>%
print()
stop("Hashes not unique. Probably duplicate email entries.")
}
# check for emails associated with different names
repeated_emails <- id_table %>%
dplyr::select(email, name) %>%
dplyr::distinct() %>%
dplyr::group_by(email) %>%
dplyr::summarise(num = dplyr::n()) %>%
dplyr::ungroup() %>%
dplyr::arrange(-num) %>%
dplyr::filter(num > 1) %>%
dplyr::pull(email)
if (isTRUE(length(repeated_emails) > 0)) {
id_table %>%
dplyr::filter(email %in% repeated_emails) %>%
dplyr::distinct() %>%
dplyr::arrange(email) %>%
dplyr::select(email, name) %>%
print()
stop("Emails are not unique. Probably different name entries for the same email.")
}
# check for emails associated with different names
repeated_names <- id_table %>%
dplyr::select(name, email) %>%
dplyr::distinct() %>%
dplyr::group_by(name) %>%
dplyr::summarise(num = dplyr::n()) %>%
dplyr::ungroup() %>%
dplyr::arrange(-num) %>%
dplyr::filter(num > 1) %>%
dplyr::pull(name)
if (isTRUE(length(repeated_names) > 0)) {
id_table %>%
dplyr::filter(name %in% repeated_names) %>%
dplyr::distinct() %>%
dplyr::arrange(name) %>%
dplyr::select(name, email) %>%
print()
stop("Names are not unique. Probably different email entries for the same name.")
}
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.