diff --git a/demo/frequenciesOverTime.R b/demo/frequenciesOverTime.R
index 475d2eb..56b576f 100644
--- a/demo/frequenciesOverTime.R
+++ b/demo/frequenciesOverTime.R
@@ -4,29 +4,19 @@
 #
 library(RKorAPClient)
 library(ggplot2)
+library(plotly)
 
-freqPerYear <- function(query, con = new("KorAPConnection", verbose = TRUE)) {
-  vc <- "pubDate since 2000 & pubDate until 2018 & textType = /Zeit.*/"
-  q <- corpusQuery(con, query = query, vc=vc)
-  q <- fetchAll(q)
-  tokensPerYear <- function(year) {
-    return(corpusStats(con, sprintf("%s & pubDate in %s", vc, year))@tokens)
-  }
-  df <- as.data.frame(table(as.numeric(format(q@collectedMatches$pubDate,"%Y")), dnn="year"),
-                      stringsAsFactors = FALSE)
-  df <- merge(data.frame(year=min(df$year):max(df$year)), df, all = TRUE)
-  df[is.na(df$Freq),]$Freq <- 0
-  df$total <- sapply(df$year, tokensPerYear)
-  df$freq <- df$Freq / df$total
-  df$ci <- t(sapply(Map(prop.test, df$Freq, df$total), "[[","conf.int"))
-  g <- ggplot(data = df, aes(x = year, y = freq, group=1)) +
-    geom_ribbon(aes(ymin=ci[, 1], ymax=ci[, 2]), alpha=.3) +
-    geom_point() +
-    geom_line() +
+freqPerYear <- function(query, kco = new("KorAPConnection", verbose = TRUE)) {
+  g <- data.frame(year = 2000:2018) %>%
+    cbind(frequencyQuery(kco, query, sprintf("pubDate in %d", .$year))) %>%
+    { . ->> df } %>%
+    ipm() %>%
+    ggplot(aes(year, ipm)) +
+    geom_freq_by_year_ci() +
     xlab("TIME") +
-    ylab(sprintf("Observed frequency of \u201c%s\u201d", query)) +
-    theme(axis.text.x = element_text(angle = 45, hjust = 1))
-  print(g)
+    ylab(sprintf("Observed frequency/million of \u201c%s\u201d", query))
+  p <- RKorAPClient::ggplotly(g)
+  print(p)
   df
 }
 #df <- freqPerYear("Car-Bikini")