diff --git a/R/f-eval.R b/R/f-eval.R
index da19382..0308e1b 100644
--- a/R/f-eval.R
+++ b/R/f-eval.R
@@ -10,6 +10,14 @@
 #' \code{.env} and \code{.data}. These are thin wrappers around \code{.data}
 #' and \code{.env} that throw errors if you try to access non-existent values.
 #'
+#' You can also provide additional sources of data by supplying named
+#' lists or data frames in \code{...}. Each of these arguments will
+#' get a pronoun based on the argument name. These names are
+#' automatically prefixed with a dot. Contrarily to \code{data}, these
+#' additional sources are not directly accessible, you have to
+#' explicitly qualify them with the relevant pronoun to access these
+#' data sources.
+#'
 #' @param f A one-sided formula. Any expressions wrapped in \code{ uq() } will
 #'   will be "unquoted", i.e. they will be evaluated, and the results inserted
 #'   back into the formula. See \code{\link{f_interp}} for more details.
@@ -17,6 +25,9 @@
 #'   find the data associated with a given object. If you want to make
 #'   \code{f_eval} work for your own objects, you can define a method for this
 #'   generic.
+#' @param ... Additional sources of pronouns. These should be named
+#'   lists or data frames. The names of the pronouns are automatically
+#'   prefixed with a dot.
 #' @param x An object for which you want to find associated data.
 #' @export
 #' @examples
@@ -40,6 +51,14 @@
 #' f_eval(~ .data$cyl, mtcars)
 #' f_eval(~ .env$cyl, mtcars)
 #'
+#' # Additional pronouns can be added by supplying named lists or data
+#' # frames as argument:
+#' f_eval(~ .iris$Species, iris = iris)
+#'
+#' # The data contained in these sources can only be accessed
+#' # explicitly, through the pronoun. Direct access will fail:
+#' \dontrun{f_eval(~ Species, iris = iris)}
+#'
 #' # Imagine you are computing the mean of a variable:
 #' f_eval(~ mean(cyl), mtcars)
 #' # How can you change the variable that's being computed?
@@ -56,15 +75,29 @@
 #'
 #' # Instead we need to use the prefix form of `$`.
 #' f_eval(~ mean( `$`(.data, uq(var) )), mtcars)
-f_eval <- function(f, data = NULL) {
+f_eval <- function(f, data = NULL, ...) {
   expr <- f_rhs(f_interp(f))
 
   data <- find_data(data)
   env <- environment(f)
+  explicit <- list(...)
+
+  if (length(explicit)) {
+    if (is.null(names(explicit))) {
+      stop("`explicit` should be named", call. = FALSE)
+    }
+    if (!all(vapply(explicit, is.list, logical(1)))) {
+      stop("`explicit` should contain lists or data frames", call. = FALSE)
+    }
+  }
+  names(explicit) <- vapply(names(explicit),
+    function(x) paste0(".", x), character(1))
 
   expr_env <- new.env(parent = env)
-  expr_env$.env <- complain(env)
-  expr_env$.data <- complain(data)
+  sources <- c(.env = env, .data = list(data), explicit)
+  for (source in names(sources)) {
+    expr_env[[source]] <- complain(sources[[source]])
+  }
 
   eval(expr, data, expr_env)
 }
diff --git a/man/f_eval.Rd b/man/f_eval.Rd
index 63b5912..4c7ca19 100644
--- a/man/f_eval.Rd
+++ b/man/f_eval.Rd
@@ -5,7 +5,7 @@
 \alias{find_data}
 \title{Evaluate a formula}
 \usage{
-f_eval(f, data = NULL)
+f_eval(f, data = NULL, ...)
 
 find_data(x)
 }
@@ -19,6 +19,10 @@ find the data associated with a given object. If you want to make
 \code{f_eval} work for your own objects, you can define a method for this
 generic.}
 
+\item{...}{Additional sources of pronouns. These should be named
+lists or data frames. The names of the pronouns are automatically
+prefixed with a dot.}
+
 \item{x}{An object for which you want to find associated data.}
 }
 \description{
@@ -32,6 +36,14 @@ When used with \code{data}, \code{f_eval} provides two pronouns to make it
 possible to be explicit about where you want values to come from:
 \code{.env} and \code{.data}. These are thin wrappers around \code{.data}
 and \code{.env} that throw errors if you try to access non-existent values.
+
+You can also provide additional sources of data by supplying named
+lists or data frames in \code{...}. Each of these arguments will
+get a pronoun based on the argument name. These names are
+automatically prefixed with a dot. Contrarily to \code{data}, these
+additional sources are not directly accessible, you have to
+explicitly qualify them with the relevant pronoun to access these
+data sources.
 }
 \examples{
 f_eval(~ 1 + 2 + 3)
@@ -54,6 +66,14 @@ cyl <- 10
 f_eval(~ .data$cyl, mtcars)
 f_eval(~ .env$cyl, mtcars)
 
+# Additional pronouns can be added by supplying named lists or data
+# frames as argument:
+f_eval(~ .iris$Species, iris = iris)
+
+# The data contained in these sources can only be accessed
+# explicitly, through the pronoun. Direct access will fail:
+\dontrun{f_eval(~ Species, iris = iris)}
+
 # Imagine you are computing the mean of a variable:
 f_eval(~ mean(cyl), mtcars)
 # How can you change the variable that's being computed?
diff --git a/tests/testthat/test-f-eval.R b/tests/testthat/test-f-eval.R
index 69262c2..a110e76 100644
--- a/tests/testthat/test-f-eval.R
+++ b/tests/testthat/test-f-eval.R
@@ -36,3 +36,17 @@ test_that("f_eval does quasiquoting", {
   x <- 10
   expect_equal(f_eval(~ uq(quote(x))), 10)
 })
+
+test_that("look into explicit pronouns", {
+  expect_equal(f_eval(~ .mtcars$cyl, mtcars = mtcars), mtcars$cyl)
+})
+
+test_that("data of explicit pronouns cannot be directly accessed", {
+  expect_error(f_eval(~ cyl, mtcars = mtcars), "not found")
+})
+
+test_that("fails when explicit is malformed", {
+  expect_error(f_eval(~ ., iris, mtcars), "should be named")
+  expect_error(f_eval(~ ., mtcars = "string"), "should contain lists")
+})
+