adjust tidyselect to use ""

Author: marcburri

R/graphs.R

@@ -185,8 +185,8 @@ plot_vintages <- function(
   n <- length(unique(df[[dim_col]]))
 
   df <- df %>%
-    dplyr::group_by(.data$time) %>%
-    dplyr::arrange(dplyr::desc(abs(.data$value)), .by_group = TRUE) %>%
+    dplyr::group_by("time") %>%
+    dplyr::arrange(dplyr::desc(abs("value")), .by_group = TRUE) %>%
     dplyr::ungroup()
 
   if (n > 1) {
@@ -209,20 +209,20 @@ plot_vintages <- function(
     if (type == "line") {
       p <- p +
         ggplot2::geom_line(
-          ggplot2::aes(x = !!time_col, y = .data$value), data = df
+          ggplot2::aes(x = !!time_col, y = "value"), data = df
         ) +
         scale_color_reviser()
     } else if (type == "point") {
       p <- p +
         ggplot2::geom_point(
-          ggplot2::aes(x = !!time_col, y = .data$value),
+          ggplot2::aes(x = !!time_col, y = "value"),
           data = df
         ) +
         scale_color_reviser()
     } else if (type == "bar") {
       p <- p +
         ggplot2::geom_bar(
-          ggplot2::aes(x = !!time_col, y = .data$value),
+          ggplot2::aes(x = !!time_col, y = "value"),
           data = df,
           position = "identity",
           stat = "identity"
@@ -240,14 +240,14 @@ plot_vintages <- function(
     if (type == "line") {
       p <- p +
         ggplot2::geom_line(
-          ggplot2::aes(x = !!time_col, y = .data$value, color = !!dim_col),
+          ggplot2::aes(x = !!time_col, y = "value", color = !!dim_col),
           data = df
         ) +
         scale_color_reviser()
     } else if (type == "point") {
       p <- p +
         ggplot2::geom_point(
-          ggplot2::aes(x = !!time_col, y = .data$value, color = !!dim_col),
+          ggplot2::aes(x = !!time_col, y = "value", color = !!dim_col),
           data = df
         ) +
         scale_color_reviser()
@@ -256,7 +256,7 @@ plot_vintages <- function(
         ggplot2::geom_bar(
           ggplot2::aes(
             x = !!time_col,
-            y = .data$value,
+            y = "value",
             color = !!dim_col,
             fill = !!dim_col
           ),
@@ -270,7 +270,7 @@ plot_vintages <- function(
       p <- p +
         ggplot2::geom_boxplot(
           ggplot2::aes(
-            x = !!time_col, y = .data$value, fill = factor(!!time_col)
+            x = !!time_col, y = "value", fill = factor(!!time_col)
           ),
           data = df
         ) +
@@ -345,14 +345,14 @@ plot.revision_model <- function(x, state = NULL, type = "filtered", ...) {
     ggplot2::geom_ribbon(
       data = in_sample_data,
       ggplot2::aes(
-        x = .data$time, ymin = .data$lower, ymax = .data$upper, fill = sample
+        x = "time", ymin = "lower", ymax = "upper", fill = sample
       ),
       alpha = 0.2
     ) +
     ggplot2::geom_line(
       data = in_sample_data,
       ggplot2::aes(
-        x = .data$time, y = .data$estimate, color = sample, linetype = sample
+        x = "time", y = "estimate", color = sample, linetype = sample
       ),
       linewidth = 0.8
     )
@@ -364,10 +364,10 @@ plot.revision_model <- function(x, state = NULL, type = "filtered", ...) {
       ggplot2::geom_crossbar(
         data = oos_data,
         ggplot2::aes(
-          x = .data$time,
-          y = .data$estimate,
-          ymin = .data$lower,
-          ymax = .data$upper,
+          x = "time",
+          y = "estimate",
+          ymin = "lower",
+          ymax = "upper",
           color = sample,
           fill = sample
         ),
@@ -377,7 +377,7 @@ plot.revision_model <- function(x, state = NULL, type = "filtered", ...) {
       ggplot2::geom_point(
         data = oos_data,
         ggplot2::aes(
-          x = .data$time, y = .data$estimate, color = sample, fill = sample
+          x = "time", y = "estimate", color = sample, fill = sample
         ),
         size = 2
       )
@@ -386,14 +386,14 @@ plot.revision_model <- function(x, state = NULL, type = "filtered", ...) {
       ggplot2::geom_ribbon(
         data = oos_data,
         ggplot2::aes(
-          x = .data$time, ymin = .data$lower, ymax = .data$upper, fill = sample
+          x = "time", ymin = "lower", ymax = "upper", fill = sample
         ),
         alpha = 0.2
       ) +
       ggplot2::geom_line(
         data = oos_data,
         ggplot2::aes(
-          x = .data$time, y = .data$estimate, color = sample, linetype = sample
+          x = "time", y = "estimate", color = sample, linetype = sample
         ),
         linewidth = 0.8
       )

R/jvn.R

@@ -168,7 +168,7 @@ jvn_nowcast <- function(df,
   # Arrange data
   df_intern <- df[, 1:(e + 1)]
 
-  y_mat <- as.matrix(dplyr::select(df_intern, -.data$time))
+  y_mat <- as.matrix(dplyr::select(df_intern, -"time"))
   rownames(y_mat) <- as.character(df$time)
 
   # Build model structure
@@ -715,7 +715,7 @@ jvn_nowcast <- function(df,
 
   # Optional: Convert to tibble if using tidyverse
   states_long <- dplyr::as_tibble(states_long) %>%
-    dplyr::arrange(.data$filter, .data$state, .data$time)
+    dplyr::arrange("filter", "state", "time")
 
   # Prepare results
   results <- list(

R/kk.R

@@ -525,7 +525,7 @@ kk_nowcast <- function(
 
   # Optional: Convert to tibble if using tidyverse
   states_long <- dplyr::as_tibble(states_long) %>%
-    dplyr::arrange(.data$filter, .data$state, .data$time)
+    dplyr::arrange("filter", "state", "time")
 
 
   # Remove the parameters from the model matrices