diff --git a/R/ci.R b/R/ci.R
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+
+#' Add confidence interval and relative frequency variables
+#'
+#' Using \code{\link{prop.test}}, \code{ci} adds three columns to a data frame:
+#' 1. relative frequency (\code{f}) 2. lower bound of a confidence interval
+#' (\code{ci.low}) 3. upper bound of a confidence interval
+#'
+#' @param df table with columns for absolute and total frequencies.
+#' @param x  column with the observed absolute frequency.
+#' @param N  column with the total frequncies
+#' @param conf.level confidence level of the returned confidence interval. Must
+#'   be a single number between 0 and 1.
+#'
+#' @export
+#' @importFrom stats prop.test
+#' @examples
+#' library(ggplot2)
+#' kco <- new("KorAPConnection", verbose=TRUE)
+#' expand_grid(year=2015:2018, alternatives=c("Hate Speech", "Hatespeech")) %>%
+#'   bind_cols(corpusQuery(kco, .$alternatives, sprintf("pubDate in %d", .$year))) %>%
+#'   mutate(tokens=corpusStats(kco, vc=vc)$tokens) %>%
+#'   ci() %>%
+#'   ggplot(aes(x=year, y=f, fill=query, color=query, ymin=conf.low, ymax=conf.high)) +
+#'     geom_point() + geom_line() + geom_ribbon(alpha=.3)
+#'
+ci <- function(df, x = totalResults, N = tokens, conf.level = 0.95) {
+  x <- enquo(x)
+  N <- enquo(N)
+  df %>%
+    rowwise %>%
+    mutate(tst = list(broom::tidy(prop.test(!!x, !!N, conf.level = conf.level)) %>%
+                        select("estimate", starts_with("conf.")) %>%
+                        rename(f = estimate)
+    )) %>%
+    tidyr::unnest(tst)
+}
+
+
+## quiets concerns of R CMD check re: the .'s that appear in pipelines
+if(getRversion() >= "2.15.1")  utils::globalVariables(c("."))
+
+
+# ci.old <- function(df, x = totalResults, N = tokens, conf.level = 0.95) {
+#   x <- deparse(substitute(x))
+#   N <- deparse(substitute(N))
+#   df <- data.frame(df)
+#   df$f <- df[,x] / df[,N]
+#   df[, c("conf.low", "conf.high")] <- t(sapply(Map(function(a, b) prop.test(a, b, conf.level = conf.level), df[,x], df[,N]), "[[","conf.int"))
+#   return(df)
+# }