diff --git a/R/difference_join.R b/R/difference_join.R
index cbdfc6b..bdb6d47 100644
--- a/R/difference_join.R
+++ b/R/difference_join.R
@@ -13,7 +13,7 @@
 #' library(dplyr)
 #'
 #' head(iris)
-#' sepal_lengths <- data_frame(Sepal.Length = c(5, 6, 7), Type = 1:3)
+#' sepal_lengths <- tibble::tibble(Sepal.Length = c(5, 6, 7), Type = 1:3)
 #'
 #' iris %>%
 #'   difference_inner_join(sepal_lengths, max_dist = .5)
diff --git a/R/distance_join.R b/R/distance_join.R
index 319abe9..1a6e079 100644
--- a/R/distance_join.R
+++ b/R/distance_join.R
@@ -21,7 +21,7 @@
 #' library(dplyr)
 #'
 #' head(iris)
-#' sepal_lengths <- data_frame(Sepal.Length = c(5, 6, 7),
+#' sepal_lengths <- tibble::tibble(Sepal.Length = c(5, 6, 7),
 #'                             Sepal.Width = 1:3)
 #'
 #' iris %>%
diff --git a/R/geo_join.R b/R/geo_join.R
index e400026..948d5bd 100644
--- a/R/geo_join.R
+++ b/R/geo_join.R
@@ -36,9 +36,9 @@
 #'
 #' # find pairs of US states whose centers are within
 #' # 200 miles of each other
-#' states <- data_frame(state = state.name,
-#'                      longitude = state.center$x,
-#'                      latitude = state.center$y)
+#' states <- tibble::tibble(state = state.name,
+#'                          longitude = state.center$x,
+#'                          latitude = state.center$y)
 #'
 #' s1 <- rename(states, state1 = state)
 #' s2 <- rename(states, state2 = state)
diff --git a/R/regex_join.R b/R/regex_join.R
index 0112dfa..3cafd89 100644
--- a/R/regex_join.R
+++ b/R/regex_join.R
@@ -18,10 +18,10 @@
 #' library(ggplot2)
 #' data(diamonds)
 #'
-#' diamonds <- tbl_df(diamonds)
+#' diamonds <- tibble::as_tibble(diamonds)
 #'
-#' d <- data_frame(regex_name = c("^Idea", "mium", "Good"),
-#'                 type = 1:3)
+#' d <- tibble::tibble(regex_name = c("^Idea", "mium", "Good"),
+#'                     type = 1:3)
 #'
 #' # When they are inner_joined, only Good<->Good matches
 #' diamonds %>%
diff --git a/R/stringdist_join.R b/R/stringdist_join.R
index e01e675..a8c7e50 100644
--- a/R/stringdist_join.R
+++ b/R/stringdist_join.R
@@ -25,9 +25,9 @@
 #' library(ggplot2)
 #' data(diamonds)
 #'
-#' d <- data_frame(approximate_name = c("Idea", "Premiums", "Premioom",
-#'                                      "VeryGood", "VeryGood", "Faiir"),
-#'                 type = 1:6)
+#' d <- tibble::tibble(approximate_name = c("Idea", "Premiums", "Premioom",
+#'                                          "VeryGood", "VeryGood", "Faiir"),
+#'                     type = 1:6)
 #'
 #' # no matches when they are inner-joined:
 #' diamonds %>%
diff --git a/README.Rmd b/README.Rmd
index 9dc3e71..18dcfef 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -77,7 +77,7 @@ misspellings
 # use the dictionary of words from the qdapDictionaries package,
 # which is based on the Nettalk corpus.
 library(qdapDictionaries)
-words <- tbl_df(DICTIONARY)
+words <- tibble::as_tibble(DICTIONARY)
 
 words
 ```
diff --git a/man/difference_join.Rd b/man/difference_join.Rd
index 6ca5536..4cd7667 100644
--- a/man/difference_join.Rd
+++ b/man/difference_join.Rd
@@ -53,7 +53,7 @@ Join two tables based on absolute difference between their columns
 library(dplyr)
 
 head(iris)
-sepal_lengths <- data_frame(Sepal.Length = c(5, 6, 7), Type = 1:3)
+sepal_lengths <- tibble::tibble(Sepal.Length = c(5, 6, 7), Type = 1:3)
 
 iris \%>\%
   difference_inner_join(sepal_lengths, max_dist = .5)
diff --git a/man/distance_join.Rd b/man/distance_join.Rd
index b5cbbf5..c46329b 100644
--- a/man/distance_join.Rd
+++ b/man/distance_join.Rd
@@ -103,7 +103,7 @@ you are computing with longitude or latitude, you probably want to use
 library(dplyr)
 
 head(iris)
-sepal_lengths <- data_frame(Sepal.Length = c(5, 6, 7),
+sepal_lengths <- tibble::tibble(Sepal.Length = c(5, 6, 7),
                             Sepal.Width = 1:3)
 
 iris \%>\%
diff --git a/man/geo_join.Rd b/man/geo_join.Rd
index 71b68a9..eba52cd 100644
--- a/man/geo_join.Rd
+++ b/man/geo_join.Rd
@@ -128,9 +128,9 @@ data("state")
 
 # find pairs of US states whose centers are within
 # 200 miles of each other
-states <- data_frame(state = state.name,
-                     longitude = state.center$x,
-                     latitude = state.center$y)
+states <- tibble::tibble(state = state.name,
+                         longitude = state.center$x,
+                         latitude = state.center$y)
 
 s1 <- rename(states, state1 = state)
 s2 <- rename(states, state2 = state)
diff --git a/man/regex_join.Rd b/man/regex_join.Rd
index 960e748..90ccca6 100644
--- a/man/regex_join.Rd
+++ b/man/regex_join.Rd
@@ -46,10 +46,10 @@ library(dplyr)
 library(ggplot2)
 data(diamonds)
 
-diamonds <- tbl_df(diamonds)
+diamonds <- tibble::as_tibble(diamonds)
 
-d <- data_frame(regex_name = c("^Idea", "mium", "Good"),
-                type = 1:3)
+d <- tibble::tibble(regex_name = c("^Idea", "mium", "Good"),
+                    type = 1:3)
 
 # When they are inner_joined, only Good<->Good matches
 diamonds \%>\%
diff --git a/man/stringdist_join.Rd b/man/stringdist_join.Rd
index 059b2a7..c6cc8e2 100644
--- a/man/stringdist_join.Rd
+++ b/man/stringdist_join.Rd
@@ -71,9 +71,9 @@ library(dplyr)
 library(ggplot2)
 data(diamonds)
 
-d <- data_frame(approximate_name = c("Idea", "Premiums", "Premioom",
-                                     "VeryGood", "VeryGood", "Faiir"),
-                type = 1:6)
+d <- tibble::tibble(approximate_name = c("Idea", "Premiums", "Premioom",
+                                         "VeryGood", "VeryGood", "Faiir"),
+                    type = 1:6)
 
 # no matches when they are inner-joined:
 diamonds \%>\%
diff --git a/vignettes/stringdist_join.Rmd b/vignettes/stringdist_join.Rmd
index ad0f7a2..9de5f70 100644
--- a/vignettes/stringdist_join.Rmd
+++ b/vignettes/stringdist_join.Rmd
@@ -30,7 +30,7 @@ misspellings
 # use the dictionary of words from the qdapDictionaries package,
 # which is based on the Nettalk corpus.
 library(qdapDictionaries)
-words <- tbl_df(DICTIONARY)
+words <- tibble::as_tibble(DICTIONARY)
 
 words
 ```