diff --git a/R/visualisation_recipe.estimate_means.R b/R/visualisation_recipe.estimate_means.R
index c062f32fe..9a99ba43d 100644
--- a/R/visualisation_recipe.estimate_means.R
+++ b/R/visualisation_recipe.estimate_means.R
@@ -23,11 +23,11 @@
 #' data$new_factor <- as.factor(rep(c("A", "B"), length.out = nrow(mtcars)))
 #'
 #' model <- lm(mpg ~ new_factor * cyl * wt, data = data)
-#' x <- estimate_means(model, by =c("new_factor", "cyl"))
+#' x <- estimate_means(model, by = c("new_factor", "cyl"))
 #' plot(visualisation_recipe(x))
 #'
 #' # Modulations --------------
-#' x <- estimate_means(model, by =c("new_factor", "wt"))
+#' x <- estimate_means(model, by = c("new_factor", "wt"))
 #' plot(visualisation_recipe(x))
 #'
 #' # x <- estimate_means(model, by =c("new_factor", "cyl", "wt"))
diff --git a/R/visualisation_recipe.estimate_slopes.R b/R/visualisation_recipe.estimate_slopes.R
index 0f03bc614..f801a5260 100644
--- a/R/visualisation_recipe.estimate_slopes.R
+++ b/R/visualisation_recipe.estimate_slopes.R
@@ -6,18 +6,18 @@
 #' # ==============================================
 #' if (require("ggplot2")) {
 #'   model <- lm(Sepal.Width ~ Species * Petal.Length, data = iris)
-#'   x <- estimate_slopes(model, trend = "Petal.Length", by ="Species")
+#'   x <- estimate_slopes(model, trend = "Petal.Length", by = "Species")
 #'
 #'   layers <- visualisation_recipe(x)
 #'   layers
 #'   plot(layers)
 #'
 #'   model <- lm(Petal.Length ~ poly(Sepal.Width, 4), data = iris)
-#'   x <- estimate_slopes(model, by ="Sepal.Width", length = 20)
+#'   x <- estimate_slopes(model, by = "Sepal.Width", length = 20)
 #'   plot(visualisation_recipe(x))
 #'
 #'   model <- lm(Petal.Length ~ Species * poly(Sepal.Width, 3), data = iris)
-#'   x <- estimate_slopes(model, by =c("Sepal.Width", "Species"))
+#'   x <- estimate_slopes(model, by = c("Sepal.Width", "Species"))
 #'   plot(visualisation_recipe(x))
 #' }
 #' \donttest{
@@ -27,11 +27,11 @@
 #'   data$Petal.Length <- data$Petal.Length^2
 #'
 #'   model <- mgcv::gam(Sepal.Width ~ t2(Petal.Width, Petal.Length), data = data)
-#'   x <- estimate_slopes(model, by =c("Petal.Width", "Petal.Length"), length = 20)
+#'   x <- estimate_slopes(model, by = c("Petal.Width", "Petal.Length"), length = 20)
 #'   plot(visualisation_recipe(x))
 #'
 #'   model <- mgcv::gam(Sepal.Width ~ t2(Petal.Width, Petal.Length, by = Species), data = data)
-#'   x <- estimate_slopes(model, by =c("Petal.Width", "Petal.Length", "Species"), length = 10)
+#'   x <- estimate_slopes(model, by = c("Petal.Width", "Petal.Length", "Species"), length = 10)
 #'   plot(visualisation_recipe(x))
 #' }
 #' }
diff --git a/man/visualisation_recipe.estimate_predicted.Rd b/man/visualisation_recipe.estimate_predicted.Rd
index 152784e8c..ed153808e 100644
--- a/man/visualisation_recipe.estimate_predicted.Rd
+++ b/man/visualisation_recipe.estimate_predicted.Rd
@@ -126,11 +126,11 @@ data$cyl <- as.factor(data$cyl)
 data$new_factor <- as.factor(rep(c("A", "B"), length.out = nrow(mtcars)))
 
 model <- lm(mpg ~ new_factor * cyl * wt, data = data)
-x <- estimate_means(model, by =c("new_factor", "cyl"))
+x <- estimate_means(model, by = c("new_factor", "cyl"))
 plot(visualisation_recipe(x))
 
 # Modulations --------------
-x <- estimate_means(model, by =c("new_factor", "wt"))
+x <- estimate_means(model, by = c("new_factor", "wt"))
 plot(visualisation_recipe(x))
 
 # x <- estimate_means(model, by =c("new_factor", "cyl", "wt"))
@@ -257,18 +257,18 @@ if (require("ggplot2") && require("rstanarm")) {
 # ==============================================
 if (require("ggplot2")) {
   model <- lm(Sepal.Width ~ Species * Petal.Length, data = iris)
-  x <- estimate_slopes(model, trend = "Petal.Length", by ="Species")
+  x <- estimate_slopes(model, trend = "Petal.Length", by = "Species")
 
   layers <- visualisation_recipe(x)
   layers
   plot(layers)
 
   model <- lm(Petal.Length ~ poly(Sepal.Width, 4), data = iris)
-  x <- estimate_slopes(model, by ="Sepal.Width", length = 20)
+  x <- estimate_slopes(model, by = "Sepal.Width", length = 20)
   plot(visualisation_recipe(x))
 
   model <- lm(Petal.Length ~ Species * poly(Sepal.Width, 3), data = iris)
-  x <- estimate_slopes(model, by =c("Sepal.Width", "Species"))
+  x <- estimate_slopes(model, by = c("Sepal.Width", "Species"))
   plot(visualisation_recipe(x))
 }
 \donttest{
@@ -278,11 +278,11 @@ if (require("mgcv")) {
   data$Petal.Length <- data$Petal.Length^2
 
   model <- mgcv::gam(Sepal.Width ~ t2(Petal.Width, Petal.Length), data = data)
-  x <- estimate_slopes(model, by =c("Petal.Width", "Petal.Length"), length = 20)
+  x <- estimate_slopes(model, by = c("Petal.Width", "Petal.Length"), length = 20)
   plot(visualisation_recipe(x))
 
   model <- mgcv::gam(Sepal.Width ~ t2(Petal.Width, Petal.Length, by = Species), data = data)
-  x <- estimate_slopes(model, by =c("Petal.Width", "Petal.Length", "Species"), length = 10)
+  x <- estimate_slopes(model, by = c("Petal.Width", "Petal.Length", "Species"), length = 10)
   plot(visualisation_recipe(x))
 }
 }
diff --git a/tests/testthat/test-estimate_predicted.R b/tests/testthat/test-estimate_predicted.R
index 35089622c..1617520c2 100644
--- a/tests/testthat/test-estimate_predicted.R
+++ b/tests/testthat/test-estimate_predicted.R
@@ -169,6 +169,5 @@ test_that("estimate_response - VisMatrix", {
   vm <- visualisation_matrix(m, by = c("Petal.Length", "Petal.Width = seq(-3, 3)"))
   estim <- estimate_relation(vm)
   expect_identical(dim(estim), c(70L, 6L))
-  expect_named(estim, c("Petal.Length", "Petal.Width", "Predicted", "SE", "CI_low", "CI_high")
-  )
+  expect_named(estim, c("Petal.Length", "Petal.Width", "Predicted", "SE", "CI_low", "CI_high"))
 })