diff --git a/R/stats/ci_commons.R b/R/stats/ci_commons.R
new file mode 100644
index 0000000000000000000000000000000000000000..8a87865cde036e458385bf95291f2ca22d359c86
--- /dev/null
+++ b/R/stats/ci_commons.R
@@ -0,0 +1,98 @@
+
+# requires
+# devtools::source_url("https://raw.githubusercontent.com/holgerbrandl/datautils/v1.43/R/core_commons.R")
+
+calc_ci = function(df, variable, ci_interval=0.95){
+    variable <- enquo(variable)
+
+    # http://dplyr.tidyverse.org/articles/programming.html
+    mean_name <- paste0( quo_name(variable), "_mean")
+    ci_name <- paste0(quo_name(variable), "_ci")
+    # echo(glue::glue("varname is {ci_name}"))
+
+    df %>% summarize(
+    mean=mean(!!variable),
+    sd=sd(!!variable),
+    N = n(),
+    se=sd/sqrt(N),
+    !!ci_name := qt(ci_interval/2+0.5, N-1)*se,
+    !!mean_name := mean
+    ) %>% select(-c(mean, sd, N, se, mean))
+}
+
+iris %>% group_by(Species) %>% calc_ci(Sepal.Length)
+iris %>% group_by(Species, Sepal.Width>3) %>% calc_ci(Sepal.Length)
+
+
+#' now with plotting
+plot_ci = function(grpData, variable, ci_interval=0.95){
+    variable <- enquo(variable)
+
+    # calculte ci intervals
+    ciData = grpData %>% summarize(
+        mean=mean(!!variable),
+        sd=sd(!!variable),
+        N = n(),
+        se=sd/sqrt(N),
+        ci = qt(ci_interval/2+0.5, N-1)*se,
+    )
+
+
+    #fail if there are more than one group attributes
+    assert(length(groups(grpData)) < 3, "more than 2 groups are not supported")
+
+    groupVar1 = groups(grpData)[[1]]
+
+    gg = ggplot(grpData, aes(x= eval(rlang::UQE(groupVar1)), y= eval(rlang::UQE(variable)))) +
+        geom_jitter(alpha=0.3, height=0) +
+        geom_errorbar(aes(ymin= mean-ci, ymax= mean+ci, y=NULL), data=ciData, width=.2, size=0.9)
+
+    # if 2 grouping variables are present add facetting on second grouping attribute
+    if(length(groups(grpData)) ==2){
+        # https://stackoverflow.com/questions/21588096/pass-string-to-facet-grid-ggplot2
+        gg =  gg + facet_wrap(as.formula(paste("~",groups(grpData)[[2]])))
+    }
+
+    gg + xlab(groupVar1) + ylab()
+}
+
+
+########################################################################################################################
+### DEV PLAYGROUND
+
+if(F){
+
+    # iris %>% ggplot(aes(Sepal.Width)) + geom_histogram()
+    iris %>%
+        group_by(Species) %>%
+        plot_ci(Petal.Length)
+    iris %>%
+        group_by(Sepal.Width > 3, Species) %>%
+        plot_ci(Petal.Length)
+    iris %>%
+        group_by(Sepal.Width > 3, Sepal.Width > 4, Species) %>%
+        plot_ci(Petal.Length)
+
+
+
+    ## see https://stackoverflow.com/questions/43405843/how-to-use-the-devel-version-of-dplyrs-enquo-and-quo-name-in-a-function-with-ti/43601059
+    ## also see https://stackoverflow.com/questions/45279287/use-dplyr-se-with-ggplot2
+
+    #' generic simple examples
+    some_plot = function(data, var){
+        variable <- enquo(var)
+        tt = quo_name(variable)
+        ggplot(data, aes_string(tt)) + geom_histogram()
+    }
+    some_plot(iris, Sepal.Length) -> works
+
+    ## without using aes_string
+    some_plot = function(data, var){
+        variable <- enquo(var)
+        # ggplot(data, aes(eval(rlang::UQE(variable))+eval(rlang::UQE(variable)))) + geom_histogram()
+        ggplot(data, aes(eval(rlang::UQE(variable)))) + geom_histogram()
+    }
+    some_plot(iris, Petal.Length)
+
+}
+