remove a lot of unrequired hjust=0 duplicates

R/vis-dat.R

@@ -110,8 +110,7 @@ vis_dat <- function(
     # change the limits etc.
     ggplot2::guides(fill = ggplot2::guide_legend(title = "Type")) +
     # add info about the axes
-    ggplot2::scale_x_discrete(limits = col_order_index, position = "top") +
-    ggplot2::theme(axis.text.x = ggplot2::element_text(hjust = 0))
+    ggplot2::scale_x_discrete(limits = col_order_index, position = "top")
 
   if (!missing(facet)) {
     vis_dat_plot <- vis_dat_plot +

R/vis-expect.R

@@ -95,9 +95,6 @@ vis_expect <- function(data, expectation, show_perc = TRUE) {
     ggplot2::ggplot(ggplot2::aes(x = variable, y = rows)) +
     ggplot2::geom_raster(ggplot2::aes(fill = valueType)) +
     ggplot2::theme_minimal() +
-    ggplot2::theme(
-      axis.text.x = ggplot2::element_text(angle = 45, vjust = 1, hjust = 1)
-    ) +
     ggplot2::labs(x = "", y = "Observations") +
     # flip the axes
     ggplot2::scale_y_reverse() +
@@ -110,15 +107,18 @@ vis_expect <- function(data, expectation, show_perc = TRUE) {
         "grey"
       ),
       labels = c(p_expect_false_lab, p_expect_true_lab),
+      # light gray
       na.value = "#E5E5E5"
-    ) + # light gray
-    ggplot2::guides(fill = ggplot2::guide_legend(reverse = TRUE)) +
+    ) +
     # change the limits etc.
-    ggplot2::guides(fill = ggplot2::guide_legend(title = "Expectation")) +
+    ggplot2::guides(
+      fill = ggplot2::guide_legend(
+        title = "Expectation",
+        reverse = TRUE
+      )
+    ) +
     # add info about the axes
-    ggplot2::theme(legend.position = "bottom") +
-    # ggplot2::theme(axis.text.x = ggplot2::element_text(hjust = 0.5)) +
-    ggplot2::theme(axis.text.x = ggplot2::element_text(hjust = 0))
+    ggplot2::theme_sub_legend(position = "bottom")
 
   vis_expect_plot
 }

R/vis-guess.R

@@ -57,8 +57,7 @@ vis_guess <- function(x, palette = "default") {
   vis_plot <- vis_create_(d) +
     ggplot2::guides(fill = ggplot2::guide_legend(title = "Type")) +
     # flip the axes, add info for axes
-    ggplot2::scale_x_discrete(position = "top", limits = names(x)) +
-    ggplot2::theme(axis.text.x = ggplot2::element_text(hjust = 0))
+    ggplot2::scale_x_discrete(position = "top", limits = names(x))
 
   # specify a palette ----------------------------------------------------------
   add_vis_dat_pal(vis_plot, palette)

R/vis-histogram.R

@@ -34,7 +34,7 @@ vis_histogram_create <- function(data, ...) {
     ggplot2::theme_minimal() +
     ggplot2::labs(x = "", y = "") +
     ggplot2::guides(fill = ggplot2::guide_legend(title = "Histogram")) +
-    ggplot2::theme(
-      axis.text.x = ggplot2::element_text(angle = 45, hjust = 0.1)
+    ggplot2::theme_sub_axis_x(
+      text = ggplot2::element_text(angle = 45, hjust = 0.1)
     )
 }

R/vis-miss.R

@@ -140,37 +140,34 @@ vis_miss <- function(
       )
     ) +
     ggplot2::guides(fill = ggplot2::guide_legend(reverse = TRUE)) +
-    ggplot2::theme(legend.position = "bottom") +
-    # fix up the location of the text
-    ggplot2::theme(axis.text.x = ggplot2::element_text(hjust = 0))
-
-  # add the missingness column labels
-
-  # if there is only one colummn you don't need to sort the columns
-  # this is perhaps a bit of a hacky way around, but I can't see another
-  # way around it. Related issue: https://github.com/ropensci/visdat/issues/72
-  if (ncol(x) == 1) {
-    if (show_perc_col) {
-      return(
-        vis_miss_plot <- vis_miss_plot +
-          ggplot2::scale_x_discrete(
-            position = "top",
-            labels = label_col_missing_pct(
-              x_fingerprinted,
-              col_order_index
+    ggplot2::theme_sub_legend(position = "bottom") +
+    # add the missingness column labels
+
+    # if there is only one colummn you don't need to sort the columns
+    # this is perhaps a bit of a hacky way around, but I can't see another
+    # way around it. Related issue: https://github.com/ropensci/visdat/issues/72
+    if (ncol(x) == 1) {
+      if (show_perc_col) {
+        return(
+          vis_miss_plot <- vis_miss_plot +
+            ggplot2::scale_x_discrete(
+              position = "top",
+              labels = label_col_missing_pct(
+                x_fingerprinted,
+                col_order_index
+              )
             )
-          )
-      )
-    } else if (!show_perc_col) {
-      return(
-        vis_miss_plot <- vis_miss_plot +
-          ggplot2::scale_x_discrete(
-            position = "top",
-            labels = col_order_index
-          )
-      )
+        )
+      } else if (!show_perc_col) {
+        return(
+          vis_miss_plot <- vis_miss_plot +
+            ggplot2::scale_x_discrete(
+              position = "top",
+              labels = col_order_index
+            )
+        )
+      }
     }
-  }
 
   if (!missing(facet)) {
     vis_miss_plot <- vis_miss_plot +

R/vis-value.R

@@ -42,6 +42,5 @@ vis_value <- function(data, na_colour = "grey90", viridis_option = "D") {
     ggplot2::guides(fill = ggplot2::guide_legend(title = "Value")) +
     # add info about the axes
     ggplot2::scale_x_discrete(position = "top") +
-    ggplot2::theme(axis.text.x = ggplot2::element_text(hjust = 0)) +
     ggplot2::scale_fill_viridis_c(option = viridis_option, na.value = na_colour)
 }