diff --git a/DESCRIPTION b/DESCRIPTION
index 2ed1150ae..0a7fb9594 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: datawizard
 Title: Easy Data Wrangling and Statistical Transformations
-Version: 0.11.0.2
+Version: 0.11.0.3
 Authors@R: c(
     person("Indrajeet", "Patil", , "patilindrajeet.science@gmail.com", role = "aut",
            comment = c(ORCID = "0000-0003-1995-6531", Twitter = "@patilindrajeets")),
diff --git a/NAMESPACE b/NAMESPACE
index 5926d19ab..a08798db1 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,5 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(as.data.frame,datawizard_crosstabs)
+S3method(as.data.frame,datawizard_tables)
 S3method(as.double,parameters_kurtosis)
 S3method(as.double,parameters_skewness)
 S3method(as.double,parameters_smoothness)
@@ -69,9 +71,9 @@ S3method(describe_distribution,grouped_df)
 S3method(describe_distribution,list)
 S3method(describe_distribution,numeric)
 S3method(format,data_codebook)
+S3method(format,datawizard_crosstab)
+S3method(format,datawizard_table)
 S3method(format,dw_data_peek)
-S3method(format,dw_data_tabulate)
-S3method(format,dw_data_xtabulate)
 S3method(format,dw_groupmeans)
 S3method(format,parameters_distribution)
 S3method(kurtosis,data.frame)
@@ -93,12 +95,12 @@ S3method(normalize,numeric)
 S3method(plot,visualisation_recipe)
 S3method(print,data_codebook)
 S3method(print,data_seek)
+S3method(print,datawizard_crosstab)
+S3method(print,datawizard_crosstabs)
+S3method(print,datawizard_table)
+S3method(print,datawizard_tables)
 S3method(print,dw_data_peek)
 S3method(print,dw_data_summary)
-S3method(print,dw_data_tabulate)
-S3method(print,dw_data_tabulates)
-S3method(print,dw_data_xtabulate)
-S3method(print,dw_data_xtabulates)
 S3method(print,dw_groupmeans)
 S3method(print,dw_groupmeans_list)
 S3method(print,dw_transformer)
@@ -107,16 +109,16 @@ S3method(print,parameters_kurtosis)
 S3method(print,parameters_skewness)
 S3method(print,visualisation_recipe)
 S3method(print_html,data_codebook)
+S3method(print_html,datawizard_crosstab)
+S3method(print_html,datawizard_crosstabs)
+S3method(print_html,datawizard_table)
+S3method(print_html,datawizard_tables)
 S3method(print_html,dw_data_peek)
-S3method(print_html,dw_data_tabulate)
-S3method(print_html,dw_data_tabulates)
-S3method(print_html,dw_data_xtabulate)
-S3method(print_html,dw_data_xtabulates)
 S3method(print_md,data_codebook)
+S3method(print_md,datawizard_crosstab)
+S3method(print_md,datawizard_table)
+S3method(print_md,datawizard_tables)
 S3method(print_md,dw_data_peek)
-S3method(print_md,dw_data_tabulate)
-S3method(print_md,dw_data_tabulates)
-S3method(print_md,dw_data_xtabulate)
 S3method(ranktransform,data.frame)
 S3method(ranktransform,factor)
 S3method(ranktransform,grouped_df)
diff --git a/NEWS.md b/NEWS.md
index 1e49e91a4..ada1f08ea 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,10 +1,21 @@
 # datawizard 0.11.0.1
 
-## Changes
+BREAKING CHANGES
+
+* Class names for objects returned by `data_tabulate()` have been changed to
+  `datawizard_table` and `datawizard_crosstable` (resp. the plural forms,
+  `*_tables`), to provide a clearer and more consistent naming scheme.
+
+CHANGES
 
 * `data_select()` can directly rename selected variables when a named vector
   is provided in `select`, e.g. `data_select(mtcars, c(new1 = "mpg", new2 = "cyl"))`.
 
+* `data_tabulate()` gains an `as.data.frame()` method, to return the frequency
+  table as a data frame. The structure of the returned object is a nested data
+  frame, where the first column contains name of the variable for which
+  frequencies were calculated, and the second column contains the frequency table.
+
 # datawizard 0.11.0
 
 BREAKING CHANGES
diff --git a/R/data_tabulate.R b/R/data_tabulate.R
index 6a26a39c9..74f4f2e03 100644
--- a/R/data_tabulate.R
+++ b/R/data_tabulate.R
@@ -28,6 +28,13 @@
 #' @param ... not used.
 #' @inheritParams extract_column_names
 #'
+#' @details
+#' There is an `as.data.frame()` method, to return the frequency tables as a
+#' data frame. The structure of the returned object is a nested data frame,
+#' where the first column contains name of the variable for which frequencies
+#' were calculated, and the second column is a list column that contains the
+#' frequency tables as data frame. See 'Examples'.
+#'
 #' @section Crosstables:
 #' If `by` is supplied, a crosstable is created. The crosstable includes `<NA>`
 #' (missing) values by default. The first column indicates values of `x`, the
@@ -108,6 +115,12 @@
 #' # round percentages
 #' out <- data_tabulate(efc, "c172code", by = "e16sex", proportions = "column")
 #' print(out, digits = 0)
+#'
+#' # coerce to data frames
+#' result <- data_tabulate(efc, "c172code", by = "e16sex")
+#' as.data.frame(result)
+#' as.data.frame(result)$table
+#' as.data.frame(result, add_total = TRUE)$table
 #' @export
 data_tabulate <- function(x, ...) {
   UseMethod("data_tabulate")
@@ -242,7 +255,7 @@ data_tabulate.default <- function(x,
   attr(out, "total_n") <- sum(out$N, na.rm = TRUE)
   attr(out, "valid_n") <- valid_n
 
-  class(out) <- c("dw_data_tabulate", "data.frame")
+  class(out) <- c("datawizard_table", "data.frame")
 
   out
 }
@@ -292,9 +305,9 @@ data_tabulate.data.frame <- function(x,
   })
 
   if (is.null(by)) {
-    class(out) <- c("dw_data_tabulates", "list")
+    class(out) <- c("datawizard_tables", "list")
   } else {
-    class(out) <- c("dw_data_xtabulates", "list")
+    class(out) <- c("datawizard_crosstabs", "list")
   }
   attr(out, "collapse") <- isTRUE(collapse)
   attr(out, "is_weighted") <- !is.null(weights)
@@ -357,9 +370,9 @@ data_tabulate.grouped_df <- function(x,
     ))
   }
   if (is.null(by)) {
-    class(out) <- c("dw_data_tabulates", "list")
+    class(out) <- c("datawizard_tables", "list")
   } else {
-    class(out) <- c("dw_data_xtabulates", "list")
+    class(out) <- c("datawizard_crosstabs", "list")
   }
   attr(out, "collapse") <- isTRUE(collapse)
   attr(out, "is_weighted") <- !is.null(weights)
@@ -380,8 +393,64 @@ insight::print_html
 insight::print_md
 
 
+#' @rdname data_tabulate
+#' @param add_total For crosstables (i.e. when `by` is not `NULL`), a row and
+#' column with the total N values are added to the data frame. `add_total` has
+#' no effect in `as.data.frame()` for simple frequency tables.
+#' @inheritParams base::as.data.frame
+#' @export
+as.data.frame.datawizard_tables <- function(x,
+                                            row.names = NULL,
+                                            optional = FALSE,
+                                            ...,
+                                            stringsAsFactors = FALSE,
+                                            add_total = FALSE) {
+  # extract variables of frequencies
+  selected_vars <- unlist(lapply(x, function(i) attributes(i)$varname))
+  # coerce to data frame, remove rownames
+  data_frames <- lapply(x, function(i) {
+    # the `format()` methods for objects returned by `data_tabulate()` call
+    # `as.data.frame()` - we have to pay attention to avoid infinite iterations
+    # here. At the moment, this is no problem, as objects we have at this stage
+    # are of class "datawizard_table" or "datawizard_crosstab", while this
+    # `as.data.frame()` method is only called for "datawizard_tables" (the plural)
+    # form). Else, we would need to modify the class attribute here,
+    # e.g. class(i) <- "data.frame"
+    if (add_total) {
+      # to add the total column and row, we simply can call `format()`
+      out <- as.data.frame(format(i))
+      for (cols in 2:ncol(out)) {
+        # since "format()" returns a character matrix, we want to convert
+        # the columns to numeric. We have to exclude the first column, as the
+        # first column is character, due to the added "Total" value.
+        out[[cols]] <- as.numeric(out[[cols]])
+      }
+      # after formatting, we have a "separator" row for nicer printing.
+      # this should also be removed
+      out <- remove_empty_rows(out)
+    } else {
+      out <- as.data.frame(i)
+    }
+    rownames(out) <- NULL
+    out
+  })
+  # create nested data frame
+  result <- data.frame(
+    var = selected_vars,
+    table = I(data_frames),
+    stringsAsFactors = stringsAsFactors
+  )
+  # consider additional arguments
+  rownames(result) <- row.names
+  result
+}
+
+#' @export
+as.data.frame.datawizard_crosstabs <- as.data.frame.datawizard_tables
+
+
 #' @export
-format.dw_data_tabulate <- function(x, format = "text", big_mark = NULL, ...) {
+format.datawizard_table <- function(x, format = "text", big_mark = NULL, ...) {
   # convert to character manually, else, for large numbers,
   # format_table() returns scientific notation
   x <- as.data.frame(x)
@@ -414,7 +483,7 @@ format.dw_data_tabulate <- function(x, format = "text", big_mark = NULL, ...) {
 
 
 #' @export
-print.dw_data_tabulate <- function(x, big_mark = NULL, ...) {
+print.datawizard_table <- function(x, big_mark = NULL, ...) {
   a <- attributes(x)
 
   # "table" header with variable label/name, and type
@@ -456,7 +525,7 @@ print.dw_data_tabulate <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print_html.dw_data_tabulate <- function(x, big_mark = NULL, ...) {
+print_html.datawizard_table <- function(x, big_mark = NULL, ...) {
   a <- attributes(x)
 
   # "table" header with variable label/name, and type
@@ -486,7 +555,7 @@ print_html.dw_data_tabulate <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print_md.dw_data_tabulate <- function(x, big_mark = NULL, ...) {
+print_md.datawizard_table <- function(x, big_mark = NULL, ...) {
   a <- attributes(x)
 
   # "table" header with variable label/name, and type
@@ -516,7 +585,7 @@ print_md.dw_data_tabulate <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print.dw_data_tabulates <- function(x, big_mark = NULL, ...) {
+print.datawizard_tables <- function(x, big_mark = NULL, ...) {
   # check if we have weights
   is_weighted <- isTRUE(attributes(x)$is_weighted)
 
@@ -555,7 +624,7 @@ print.dw_data_tabulates <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print_html.dw_data_tabulates <- function(x, big_mark = NULL, ...) {
+print_html.datawizard_tables <- function(x, big_mark = NULL, ...) {
   # check if we have weights
   is_weighted <- isTRUE(attributes(x)$is_weighted)
 
@@ -584,7 +653,7 @@ print_html.dw_data_tabulates <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print_md.dw_data_tabulates <- function(x, big_mark = NULL, ...) {
+print_md.datawizard_tables <- function(x, big_mark = NULL, ...) {
   # check if we have weights
   is_weighted <- isTRUE(attributes(x)$is_weighted)
 
diff --git a/R/data_xtabulate.R b/R/data_xtabulate.R
index 3cb25d62b..5c387ff95 100644
--- a/R/data_xtabulate.R
+++ b/R/data_xtabulate.R
@@ -74,8 +74,9 @@
   attr(out, "total_n") <- total_n
   attr(out, "weights") <- weights
   attr(out, "proportions") <- proportions
+  attr(out, "varname") <- obj_name
 
-  class(out) <- c("dw_data_xtabulate", "data.frame")
+  class(out) <- c("datawizard_crosstab", "data.frame")
 
   out
 }
@@ -85,7 +86,7 @@
 
 
 #' @export
-format.dw_data_xtabulate <- function(x, format = "text", digits = 1, big_mark = NULL, ...) {
+format.datawizard_crosstab <- function(x, format = "text", digits = 1, big_mark = NULL, ...) {
   # convert to character manually, else, for large numbers,
   # format_table() returns scientific notation
   x <- as.data.frame(x)
@@ -178,7 +179,7 @@ format.dw_data_xtabulate <- function(x, format = "text", digits = 1, big_mark =
 
 
 #' @export
-print.dw_data_xtabulate <- function(x, big_mark = NULL, ...) {
+print.datawizard_crosstab <- function(x, big_mark = NULL, ...) {
   # grouped data? if yes, add information on grouping factor
   if (is.null(x[["Group"]])) {
     caption <- NULL
@@ -200,7 +201,7 @@ print.dw_data_xtabulate <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print_md.dw_data_xtabulate <- function(x, big_mark = NULL, ...) {
+print_md.datawizard_crosstab <- function(x, big_mark = NULL, ...) {
   # grouped data? if yes, add information on grouping factor
   if (is.null(x[["Group"]])) {
     caption <- NULL
@@ -222,7 +223,7 @@ print_md.dw_data_xtabulate <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print_html.dw_data_xtabulate <- function(x, big_mark = NULL, ...) {
+print_html.datawizard_crosstab <- function(x, big_mark = NULL, ...) {
   # grouped data? if yes, add information on grouping factor
   if (!is.null(x[["Group"]])) {
     x$groups <- paste0("Grouped by ", x[["Group"]][1])
@@ -240,7 +241,7 @@ print_html.dw_data_xtabulate <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print.dw_data_xtabulates <- function(x, big_mark = NULL, ...) {
+print.datawizard_crosstabs <- function(x, big_mark = NULL, ...) {
   for (i in seq_along(x)) {
     print(x[[i]], big_mark = big_mark, ...)
     cat("\n")
@@ -250,7 +251,7 @@ print.dw_data_xtabulates <- function(x, big_mark = NULL, ...) {
 
 
 #' @export
-print_html.dw_data_xtabulates <- function(x, big_mark = NULL, ...) {
+print_html.datawizard_crosstabs <- function(x, big_mark = NULL, ...) {
   if (length(x) == 1) {
     print_html(x[[1]], big_mark = big_mark, ...)
   } else {
diff --git a/man/data_tabulate.Rd b/man/data_tabulate.Rd
index b744c1f1b..3f17bb21c 100644
--- a/man/data_tabulate.Rd
+++ b/man/data_tabulate.Rd
@@ -4,6 +4,7 @@
 \alias{data_tabulate}
 \alias{data_tabulate.default}
 \alias{data_tabulate.data.frame}
+\alias{as.data.frame.datawizard_tables}
 \title{Create frequency and crosstables of variables}
 \usage{
 data_tabulate(x, ...)
@@ -35,6 +36,15 @@ data_tabulate(x, ...)
   verbose = TRUE,
   ...
 )
+
+\method{as.data.frame}{datawizard_tables}(
+  x,
+  row.names = NULL,
+  optional = FALSE,
+  ...,
+  stringsAsFactors = FALSE,
+  add_total = FALSE
+)
 }
 \arguments{
 \item{x}{A (grouped) data frame, a vector or factor.}
@@ -116,6 +126,24 @@ functions (see 'Details'), this argument may be used as workaround.}
 
 \item{collapse}{Logical, if \code{TRUE} collapses multiple tables into one larger
 table for printing. This affects only printing, not the returned object.}
+
+\item{row.names}{\code{NULL} or a character vector giving the row
+    names for the data frame.  Missing values are not allowed.}
+
+\item{optional}{logical. If \code{TRUE}, setting row names and
+    converting column names (to syntactic names: see
+    \code{\link[base]{make.names}}) is optional.  Note that all of \R's
+    \pkg{base} package \code{as.data.frame()} methods use
+    \code{optional} only for column names treatment, basically with the
+    meaning of \code{\link[base]{data.frame}(*, check.names = !optional)}.
+    See also the \code{make.names} argument of the \code{matrix} method.}
+
+\item{stringsAsFactors}{logical: should the character vector be converted
+    to a factor?}
+
+\item{add_total}{For crosstables (i.e. when \code{by} is not \code{NULL}), a row and
+column with the total N values are added to the data frame. \code{add_total} has
+no effect in \code{as.data.frame()} for simple frequency tables.}
 }
 \value{
 A data frame, or a list of data frames, with one frequency table
@@ -127,6 +155,13 @@ including the number of levels/values as well as the distribution of raw,
 valid and cumulative percentages. For crosstables, row, column  and cell
 percentages can be calculated.
 }
+\details{
+There is an \code{as.data.frame()} method, to return the frequency tables as a
+data frame. The structure of the returned object is a nested data frame,
+where the first column contains name of the variable for which frequencies
+were calculated, and the second column is a list column that contains the
+frequency tables as data frame. See 'Examples'.
+}
 \note{
 There are \code{print_html()} and \code{print_md()} methods available for printing
 frequency or crosstables in HTML and markdown format, e.g.
@@ -207,5 +242,11 @@ data_tabulate(
 # round percentages
 out <- data_tabulate(efc, "c172code", by = "e16sex", proportions = "column")
 print(out, digits = 0)
+
+# coerce to data frames
+result <- data_tabulate(efc, "c172code", by = "e16sex")
+as.data.frame(result)
+as.data.frame(result)$table
+as.data.frame(result, add_total = TRUE)$table
 \dontshow{\}) # examplesIf}
 }
diff --git a/tests/testthat/test-data_tabulate.R b/tests/testthat/test-data_tabulate.R
index 39f5d44c6..5108e29c2 100644
--- a/tests/testthat/test-data_tabulate.R
+++ b/tests/testthat/test-data_tabulate.R
@@ -81,7 +81,7 @@ test_that("data_tabulate data.frame", {
         "Variable", "Value", "N", "Raw %", "Valid %",
         "Cumulative %"
       ),
-      class = c("dw_data_tabulate", "data.frame"),
+      class = c("datawizard_table", "data.frame"),
       row.names = 1:3,
       type = "numeric",
       varname = "e16sex",
@@ -99,7 +99,7 @@ test_that("data_tabulate data.frame", {
         "Variable", "Value", "N", "Raw %", "Valid %",
         "Cumulative %"
       ),
-      class = c("dw_data_tabulate", "data.frame"),
+      class = c("datawizard_table", "data.frame"),
       row.names = 1:4,
       type = "numeric",
       varname = "c172code",
@@ -139,7 +139,7 @@ test_that("data_tabulate print", {
     attributes(out),
     list(
       names = c("Variable", "Value", "N", "Raw %", "Valid %", "Cumulative %"),
-      class = c("dw_data_tabulate", "data.frame"),
+      class = c("datawizard_table", "data.frame"),
       row.names = 1:4,
       type = "integer",
       varname = "Large Number",
@@ -197,7 +197,7 @@ test_that("data_tabulate grouped data.frame", {
         "Valid %",
         "Cumulative %"
       ),
-      class = c("dw_data_tabulate", "data.frame"),
+      class = c("datawizard_table", "data.frame"),
       row.names = 1:4,
       type = "numeric",
       varname = "c172code",
@@ -268,6 +268,7 @@ test_that("data_tabulate drop levels", {
 
 
 # select helpers ------------------------------
+
 test_that("data_tabulate regex", {
   data(mtcars)
   expect_identical(
@@ -296,6 +297,7 @@ test_that("data_tabulate exclude/include missing values", {
 
 
 # cross tables ------------------------------
+
 test_that("data_tabulate, cross tables", {
   data(efc, package = "datawizard")
   set.seed(123)
@@ -380,6 +382,7 @@ test_that("data_tabulate, cross tables, markdown", {
   expect_snapshot(print_md(data_tabulate(efc$c172code, by = efc$e16sex, proportions = "full", include_na = FALSE, weights = efc$weights))) # nolint
 })
 
+
 # validate against table -------------------------
 
 test_that("data_tabulate, validate against table", {
@@ -405,3 +408,68 @@ test_that("data_tabulate, correct 0% for proportions", {
   expect_identical(format(out[[1]])[[4]], c("0 (0%)", "0 (0%)", "0 (0%)", "0 (0%)", "", "0"))
   expect_snapshot(print(out[[1]]))
 })
+
+
+# coercing to data frame -------------------------
+
+test_that("data_tabulate, as.data.frame, frequency tables", {
+  data(mtcars)
+  # frequency table
+  x <- data_tabulate(mtcars$cyl)
+  out <- as.data.frame(x)
+  expect_named(out, c("Variable", "Value", "N", "Raw %", "Valid %", "Cumulative %"))
+  expect_identical(out$Variable, c("mtcars$cyl", "mtcars$cyl", "mtcars$cyl", "mtcars$cyl"))
+  expect_false(any(vapply(out[2:ncol(out)], is.character, logical(1))))
+  # frequency tables
+  x <- data_tabulate(mtcars, select = c("cyl", "am"))
+  out <- as.data.frame(x)
+  expect_named(out, c("var", "table"))
+  expect_equal(vapply(out, class, character(1)), c("character", "AsIs"), ignore_attr = TRUE)
+  expect_length(out$table, 2L)
+  expect_named(out$table[[1]], c("Variable", "Value", "N", "Raw %", "Valid %", "Cumulative %"))
+  expect_identical(out$table[[1]]$Variable, c("cyl", "cyl", "cyl", "cyl"))
+  expect_false(any(vapply(out$table[[1]][2:ncol(out$table[[1]])], is.character, logical(1))))
+})
+
+
+test_that("data_tabulate, as.data.frame, cross tables", {
+  data(mtcars)
+  # cross table
+  x <- data_tabulate(mtcars, "cyl", by = "am")
+  out <- as.data.frame(x)
+  expect_named(out, c("var", "table"))
+  expect_equal(vapply(out, class, character(1)), c("character", "AsIs"), ignore_attr = TRUE)
+  expect_length(out$table, 1L)
+  expect_named(out$table[[1]], c("cyl", "0", "1", "NA"))
+  expect_identical(nrow(out$table[[1]]), 4L)
+  # cross tables
+  x <- data_tabulate(mtcars, c("cyl", "vs"), by = "am")
+  out <- as.data.frame(x)
+  expect_named(out, c("var", "table"))
+  expect_equal(vapply(out, class, character(1)), c("character", "AsIs"), ignore_attr = TRUE)
+  expect_length(out$table, 2L)
+  expect_named(out$table[[1]], c("cyl", "0", "1", "NA"))
+  expect_identical(nrow(out$table[[1]]), 4L)
+})
+
+
+test_that("data_tabulate, as.data.frame, cross tables with total N", {
+  # cross table, with total
+  x <- data_tabulate(mtcars, "cyl", by = "am")
+  out <- as.data.frame(x, add_total = TRUE)
+  expect_named(out, c("var", "table"))
+  expect_equal(vapply(out, class, character(1)), c("character", "AsIs"), ignore_attr = TRUE)
+  expect_length(out$table, 1L)
+  expect_named(out$table[[1]], c("cyl", "0", "1", "<NA>", "Total"))
+  expect_identical(nrow(out$table[[1]]), 5L)
+  expect_identical(out$table[[1]]$cyl, c("4", "6", "8", NA, "Total"))
+  # cross tables, with total
+  x <- data_tabulate(mtcars, c("cyl", "vs"), by = "am")
+  out <- as.data.frame(x, add_total = TRUE)
+  expect_named(out, c("var", "table"))
+  expect_equal(vapply(out, class, character(1)), c("character", "AsIs"), ignore_attr = TRUE)
+  expect_length(out$table, 2L)
+  expect_named(out$table[[1]], c("cyl", "0", "1", "<NA>", "Total"))
+  expect_identical(nrow(out$table[[1]]), 5L)
+  expect_identical(out$table[[1]]$cyl, c("4", "6", "8", NA, "Total"))
+})