diff --git a/DESCRIPTION b/DESCRIPTION
index 9a8d4e2..51dacdc 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: autospc
 Title: Automatically Partitioned SPC Charts
-Version: 0.0.0.9040
+Version: 0.0.0.9041
 Authors@R: c(
     person("Thomas", "Woodcock", , "woodcock.thomas@gmail.com", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0002-4735-4856")),
@@ -14,6 +14,7 @@ Imports:
     DiagrammeR,
     dplyr,
     fpCompare,
+    ggnewscale,
     ggplot2,
     lifecycle,
     magrittr,
diff --git a/R/add_annotation_data.R b/R/add_annotation_data.R
index db505c9..b9d7410 100644
--- a/R/add_annotation_data.R
+++ b/R/add_annotation_data.R
@@ -128,12 +128,17 @@ add_annotations_to_plot_pp <- function(p,
   if(annotation_arrows) {
     
     p_annotated <- p + ggrepel::geom_text_repel(
+      data = . %>% dplyr::filter(series %in% c("cl"),
+                                 !is.na(annotation_level)),
       ggplot2::aes(x = x,
-                   y = cl,
+                   y = value,
                    label = cl_label),
-      position = ggpp::position_nudge_to(y = df %>%
-                                           dplyr::filter(!is.na(y)) %>%
-                                           dplyr::pull(annotation_level)),
+      position = ggpp::position_nudge_to(
+        y = df %>%
+          dplyr::filter(series %in% c("cl"),
+                        !is.na(value),
+                        !is.na(annotation_level)) %>%
+          dplyr::pull(annotation_level)),
       color = "grey40",
       size = annotation_size,
       fontface = "bold",
@@ -143,7 +148,9 @@ add_annotations_to_plot_pp <- function(p,
       hjust             = 0,
       segment.size      = 0.75,
       segment.curvature = df %>%
-        dplyr::filter(!is.na(y)) %>%
+        dplyr::filter(series %in% c("cl"),
+                      !is.na(value),
+                      !is.na(annotation_level)) %>%
         dplyr::pull(annotation_curvature),
       segment.ncp = 4,
       segment.inflect = FALSE,
@@ -153,12 +160,17 @@ add_annotations_to_plot_pp <- function(p,
       max.overlaps = Inf)
   } else {
     p_annotated <- p + ggrepel::geom_text_repel(
+      data = . %>% dplyr::filter(series %in% c("cl"),
+                                 !is.na(annotation_level)),
       ggplot2::aes(x = x,
-                   y = cl,
+                   y = value,
                    label = cl_label),
-      position = ggpp::position_nudge_to(y = df %>%
-                                           dplyr::filter(!is.na(y)) %>%
-                                           dplyr::pull(annotation_level)),
+      position = ggpp::position_nudge_to(
+        y = df %>%
+          dplyr::filter(series %in% c("cl"),
+                        !is.na(value),
+                        !is.na(annotation_level)) %>%
+          dplyr::pull(annotation_level)),
       color = "grey40",
       size = annotation_size,
       fontface = "bold",
@@ -184,14 +196,17 @@ add_annotations_to_plot_basic <- function(p,
   x_nudge <- x_range/25
   
   p_annotated <- p +
-    ggplot2::geom_text(mapping = ggplot2::aes(x = x,
-                                              y = annotation_level,
-                                              label = cl_label),
-                       nudge_x = x_nudge,
-                       na.rm = TRUE,
-                       color = "grey40",
-                       size = annotation_size,
-                       fontface = "bold")
+    ggplot2::geom_text(
+      data = . %>% dplyr::filter(series %in% c("cl"),
+                                 !is.na(annotation_level)),
+      mapping = ggplot2::aes(x = x,
+                             y = annotation_level,
+                             label = cl_label),
+      nudge_x = x_nudge,
+      na.rm = TRUE,
+      color = "grey40",
+      size = annotation_size,
+      fontface = "bold")
   
   return(p_annotated)
   
diff --git a/R/add_floating_median.R b/R/add_floating_median.R
new file mode 100644
index 0000000..a61923b
--- /dev/null
+++ b/R/add_floating_median.R
@@ -0,0 +1,38 @@
+# Add floating median line to the plot p
+add_floating_median <- function(df,
+                                p,
+                                floating_median_n) {
+  
+  p <- p +
+    ggplot2::geom_line(data = df %>%
+                         dplyr::filter(series == "cl"), 
+                       ggplot2::aes(x, median),
+                       linetype = "75551555",
+                       colour = "gray50",
+                       linewidth = 0.5,
+                       show.legend = TRUE,
+                       na.rm = TRUE) +
+    ggplot2::annotate(
+      "text",
+      x = df %>%
+        dplyr::filter(series == "cl") %>%
+        dplyr::filter(dplyr::row_number() ==
+                        nrow(df %>%
+                               dplyr::filter(series == "cl")) -
+                        floating_median_n + 1L) %>%
+        dplyr::pull(x),
+      y = df %>%
+        dplyr::filter(series == "cl") %>%
+        dplyr::filter(dplyr::row_number() ==
+                        nrow(df %>%
+                               dplyr::filter(series == "cl")) -
+                        floating_median_n + 1L) %>%
+        dplyr::pull(median)*0.95,
+      label = "Median",
+      size = 3,
+      colour = "gray50",
+      na.rm = TRUE)
+  
+  return(p)
+  
+}
\ No newline at end of file
diff --git a/R/algorithm_helpers.R b/R/algorithm_helpers.R
index 3b392f2..86212e5 100644
--- a/R/algorithm_helpers.R
+++ b/R/algorithm_helpers.R
@@ -481,39 +481,6 @@ floating_median_column <- function(df,
 }
 
 
-# Add floating median line to the plot p
-add_floating_median <- function(df,
-                                p,
-                                floating_median_n) {
-  
-  p <- p +
-    ggplot2::geom_line(data = df, 
-                       ggplot2::aes(x, median),
-                       linetype = "75551555",
-                       colour = "gray50",
-                       linewidth = 0.5,
-                       show.legend = TRUE,
-                       na.rm = TRUE) +
-    ggplot2::annotate(
-      "text",
-      x = df %>%
-        dplyr::filter(dplyr::row_number() == nrow(df) -
-                        floating_median_n + 1L) %>%
-        dplyr::pull(x),
-      y = df %>%
-        dplyr::filter(dplyr::row_number() == nrow(df) -
-                        floating_median_n + 1L) %>%
-        dplyr::pull(median)*0.95,
-      label = "Median",
-      size = 3,
-      colour = "gray50",
-      na.rm = TRUE)
-  
-  return(p)
-  
-}
-
-
 sign_chr <- function(x) {
   y <- dplyr::case_when(
     x < 0 ~ "01",
diff --git a/R/visualisation.R b/R/visualisation.R
index f5161b3..65aad81 100644
--- a/R/visualisation.R
+++ b/R/visualisation.R
@@ -29,9 +29,22 @@ create_spc_plot <- function(df,
                             x_date_format = "%Y-%m-%d",
                             split_rows = NULL) {
   
+  df_long <- df %>%
+    tidyr::pivot_longer(cols = c(y, cl, ucl, lcl),
+                        names_to = "series",
+                        values_to = "value")
+  
+  df_long <- df_long %>%
+    dplyr::select(x,
+                  series,
+                  value,
+                  everything())
+  
   # Create initial plot object without formatting
-  pct <- ggplot2::ggplot(df %>% dplyr::filter(!is.na(y)),
-                         ggplot2::aes(x,y))
+  pct <- ggplot2::ggplot(df_long %>%
+                           dplyr::filter(!is.na(value)),
+                         ggplot2::aes(x = x,
+                                      y = value))
   
   if(use_caption) {
     caption <- paste(chart_type,
@@ -46,8 +59,9 @@ create_spc_plot <- function(df,
     rule_title <- "Rule triggered"
   }
   
+  # Apply autospc formatting
   p <- format_SPC(pct,
-                  df = df,
+                  df_long = df_long,
                   r1_col = r1_col,
                   r2_col = r2_col,
                   point_size = point_size,
@@ -62,16 +76,18 @@ create_spc_plot <- function(df,
                                 breaks = scales::breaks_pretty(),
                                 labels = scales::label_number(big.mark = ","))
   
+  # Add floating median to chart if needed
   if("median" %in% colnames(df)) {
     p <- add_floating_median(p = p,
-                             df = df,
+                             df = df_long,
                              floating_median_n = floating_median_n)
   }
   
+  # Add annotations to chart if needed
   if(include_annotations == TRUE){
     
     p <- add_annotations_to_plot(p = p,
-                                 df = df,
+                                 df = df_long,
                                  basic_annotations = basic_annotations,
                                  annotation_size = annotation_size,
                                  annotation_arrows = annotation_arrows,
@@ -79,62 +95,14 @@ create_spc_plot <- function(df,
   }
   
   # Format x-axis depending on x type
-  if(any(xType == "Date")) {
-    if(is.null(x_break)) {
-      p <- p + 
-        ggplot2::scale_x_date(labels = scales::date_format(x_date_format),
-                              breaks = scales::breaks_pretty(),
-                              limits = c(as.Date(start_x),
-                                         as.Date(end_x)))
-    } else {
-      p <- p + 
-        ggplot2::scale_x_date(labels = scales::date_format(x_date_format),
-                              breaks = seq(as.Date(start_x),
-                                           as.Date(end_x),
-                                           x_break),
-                              limits = c(as.Date(start_x),
-                                         as.Date(end_x)))
-    }
-  } else if(any(xType == "integer")) {
-    if(is.null(x_break)) {
-      p <- p + 
-        ggplot2::scale_x_continuous(breaks = scales::breaks_extended(),
-                                    limits = c(start_x,
-                                               end_x))
-    } else {
-      p <- p + 
-        ggplot2::scale_x_continuous(breaks = seq(start_x,
-                                                 end_x,
-                                                 x_break),
-                                    limits = c(start_x,
-                                               end_x))
-    }
-  } else if(any(xType == "POSIXct")) {
-    if(is.null(x_break)) {
-      p <- p + 
-        ggplot2::scale_x_datetime(breaks = scales::breaks_pretty(),
-                                  limits = c(start_x, end_x))
-    } else {
-      if(any(class(x_break) != "difftime")) {
-        rlang::abort(paste("Please specify x_break as a difftime object when",
-                           "x is POSIXct."))
-      }
-      p <- p + 
-        ggplot2::scale_x_datetime(breaks = seq(start_x, end_x, x_break),
-                                  limits = c(start_x, end_x))
-    }
-  } else {
-    if(is.null(x_break)) {
-      p <- p + 
-        ggplot2::scale_x_continuous(breaks = scales::breaks_extended(),
-                                    limits = c(start_x, end_x))
-    } else {
-      p <- p + 
-        ggplot2::scale_x_continuous(breaks = seq(start_x, end_x, x_break),
-                                    limits = c(start_x, end_x))
-    }
-  }
+  p <- format_x_axis(p = p,
+                     xType = xType,
+                     x_break = x_break,
+                     x_date_format = x_date_format,
+                     start_x = start_x,
+                     end_x = end_x)
   
+  # Facet by stages if needed
   if(!is.null(split_rows)) {
     p <- p +
       ggplot2::facet_wrap(facets = ggplot2::vars(stage),
@@ -142,6 +110,7 @@ create_spc_plot <- function(df,
     
   }
   
+  # Combine X and MR charts if needed
   if((chart_type == "XMR") & show_mr) {
     p <- p + 
       ggplot2::labs(caption = NULL,
@@ -190,25 +159,7 @@ create_timeseries_plot <- function(df,
     ggplot2::geom_line(colour = "black",
                        linewidth = 0.5*line_width_sf) +
     ggplot2::geom_point(colour = "black", size = point_size) +
-    ggplot2::theme(panel.grid.major.y = ggplot2::element_blank(),
-                   panel.grid.major.x = ggplot2::element_line(
-                     colour = "grey80"
-                   ),
-                   panel.grid.minor = ggplot2::element_blank(),
-                   panel.background = ggplot2::element_blank(),
-                   axis.text.x = ggplot2::element_text(angle = 45,
-                                                       hjust = 1,
-                                                       vjust = 1.0,
-                                                       size = 14),
-                   axis.text.y = ggplot2::element_text(size = 14),
-                   axis.title = ggplot2::element_text(size = 14),
-                   plot.title = ggplot2::element_text(size = 20,
-                                                      hjust = 0),
-                   plot.subtitle = ggplot2::element_text(size = 16,
-                                                         face = "italic"),
-                   axis.line = ggplot2::element_line(colour = "grey60"),
-                   plot.caption = ggplot2::element_text(size = 10,
-                                                        hjust = 0.5)) +
+    theme_autospc() +
     ggplot2::ggtitle(title,
                      subtitle = subtitle) +
     ggplot2::labs(x = override_x_title,
@@ -223,7 +174,7 @@ create_timeseries_plot <- function(df,
 
 
 format_SPC <- function(cht,
-                       df,
+                       df_long,
                        r1_col,
                        r2_col,
                        point_size,
@@ -236,91 +187,161 @@ format_SPC <- function(cht,
                      "None" = "black",
                      "Excluded from limits calculation" = "grey")
   
-  #get exemplar calculation and display periods
-  plot_periods <- df$plotPeriod
+  line_colours <- c("Calculation" = "black",
+                    "Display" = "grey50")
+  
+  # Prepare information on plot periods
+  plot_periods <- df_long$plotPeriod
   
   first_display_period <- plot_periods[grep("display",
                                             plot_periods)[1]]
   first_calc_period <- plot_periods[1]
   
-  suppressWarnings( # to avoid the warning about using alpha for discrete vars
-    cht + 
-      ggplot2::geom_line(colour = "black",
-                         linewidth = 0.5*line_width_sf,
-                         na.rm = TRUE) + 
-      ggplot2::geom_line(data = df, 
-                         ggplot2::aes(x,cl,
-                                      alpha = plotPeriod),
-                         linetype = "solid",
-                         linewidth = 0.75*line_width_sf,
-                         na.rm = TRUE) +
-      ggplot2::geom_line(data = df, 
-                         ggplot2::aes(x,lcl,
-                                      alpha = plotPeriod),
-                         linetype = "42",
-                         linewidth = 0.5*line_width_sf,
-                         show.legend = FALSE,
-                         na.rm = TRUE) +
-      ggplot2::geom_line(data = df, 
-                         ggplot2::aes(x,ucl,
-                                      alpha = plotPeriod),
-                         linetype = "42",
-                         linewidth = 0.5*line_width_sf,
-                         show.legend = FALSE,
-                         na.rm = TRUE) +
-      ggplot2::geom_point(ggplot2::aes(colour = highlight),
-                          size = point_size,
-                          na.rm = TRUE) +
-      ggplot2::scale_color_manual(rule_title,
-                                  values = point_colours) + 
-      ggplot2::scale_alpha_discrete("Period Type",
-                                    labels = if(!is.na(first_display_period)) {
-                                      c("Calculation", "Display")
-                                    } else {
-                                      c("Calculation")
-                                    },
-                                    range = if(!is.na(first_display_period)) {
-                                      c(1, 0.4)
-                                    } else {
-                                      c(1, 1)
-                                    },
-                                    breaks = if(!is.na(first_display_period)) {
-                                      c(first_calc_period,
-                                        first_display_period)
-                                    } else {
-                                      c(first_calc_period)
-                                    },
-                                    guide = ggplot2::guide_legend(
-                                      override.aes = list(
-                                        alpha = if(
-                                          !is.na(first_display_period)
-                                        ) {
-                                          c(1, 0.4)
-                                        } else {
-                                          c(1)
-                                        }
-                                      )
-                                    )
-      ) +
-      ggplot2::theme(panel.grid.major.y = ggplot2::element_blank(),
-                     panel.grid.major.x = ggplot2::element_line(
-                       colour = "grey80"
-                     ),
-                     panel.grid.minor = ggplot2::element_blank(),
-                     panel.background = ggplot2::element_blank(),
-                     axis.text.x = ggplot2::element_text(angle = 45,
-                                                         hjust = 1,
-                                                         vjust = 1.0,
-                                                         size = 14),
-                     axis.text.y = ggplot2::element_text(size = 14),
-                     axis.title = ggplot2::element_text(size = 14),
-                     plot.title = ggplot2::element_text(size = 20,
-                                                        hjust = 0),
-                     plot.subtitle = ggplot2::element_text(size = 16,
-                                                           face = "italic"),
-                     axis.line = ggplot2::element_line(colour = "grey60"),
-                     plot.caption = ggplot2::element_text(size = 10,
-                                                          hjust = 0.5)) 
-  )
+  list_of_plot_periods <- unique(plot_periods)
+  
+  linecolour_scale <- grepl("calculation",
+                            list_of_plot_periods) %>%
+    ifelse(line_colours["Calculation"],
+           line_colours["Display"])
+  
+  names(linecolour_scale) <- list_of_plot_periods
+  
+  # Create spc plot components
+  cht <- cht + 
+    ggplot2::geom_line(data = . %>% dplyr::filter(
+      series %in% c("cl", "ucl", "lcl")),
+      ggplot2::aes(colour = plotPeriod,
+                   linetype = series,
+                   linewidth = series),
+      na.rm = TRUE) + 
+    ggplot2::geom_line(data = . %>% dplyr::filter(series %in% c("y")),
+                       ggplot2::aes(linetype = series,
+                                    linewidth = series),
+                       show.legend = FALSE,
+                       na.rm = TRUE) +
+    ggplot2::scale_colour_manual(
+      "Period Type",
+      values = linecolour_scale,
+      breaks = if(!is.na(first_display_period)) {
+        c(first_calc_period,
+          first_display_period)
+      } else {
+        c(first_calc_period)
+      },
+      labels = if(!is.na(first_display_period)) {
+        c("Calculation", "Display")
+      } else {
+        c("Calculation")
+      }
+    ) +
+    ggplot2::scale_linetype_manual(values = c("solid", "42", "42", "solid"),
+                                   guide = "none") +
+    ggplot2::scale_linewidth_manual(values =
+                                      c(0.75, 0.5, 0.5, 0.5)*line_width_sf,
+                                    guide = "none") +
+    ggnewscale::new_scale_colour() +
+    ggplot2::geom_point(data = . %>% dplyr::filter(series == "y"),
+                        ggplot2::aes(colour = highlight),
+                        size = point_size,
+                        na.rm = TRUE) +
+    ggplot2::scale_color_manual(rule_title,
+                                values = point_colours) + 
+    theme_autospc()
+  
+  return(cht)
+}
+
+
+theme_autospc <- function(){
+  
+  thm_aspc <- ggplot2::theme(panel.grid.major.y = ggplot2::element_blank(),
+                             panel.grid.major.x = ggplot2::element_line(
+                               colour = "grey80"
+                             ),
+                             panel.grid.minor = ggplot2::element_blank(),
+                             panel.background = ggplot2::element_blank(),
+                             axis.text.x = ggplot2::element_text(angle = 45,
+                                                                 hjust = 1,
+                                                                 vjust = 1.0,
+                                                                 size = 14),
+                             axis.text.y = ggplot2::element_text(size = 14),
+                             axis.title = ggplot2::element_text(size = 14),
+                             plot.title = ggplot2::element_text(size = 20,
+                                                                hjust = 0),
+                             plot.subtitle = ggplot2::element_text(size = 16,
+                                                                   face = "italic"),
+                             axis.line = ggplot2::element_line(colour = "grey60"),
+                             plot.caption = ggplot2::element_text(size = 10,
+                                                                  hjust = 0.5)) 
+  
+  return(thm_aspc)
+  
 }
 
+
+format_x_axis <- function(p,
+                          xType,
+                          x_break,
+                          x_date_format,
+                          start_x,
+                          end_x) {
+  
+  if(any(xType == "Date")) {
+    if(is.null(x_break)) {
+      p <- p + 
+        ggplot2::scale_x_date(labels = scales::date_format(x_date_format),
+                              breaks = scales::breaks_pretty(),
+                              limits = c(as.Date(start_x),
+                                         as.Date(end_x)))
+    } else {
+      p <- p + 
+        ggplot2::scale_x_date(labels = scales::date_format(x_date_format),
+                              breaks = seq(as.Date(start_x),
+                                           as.Date(end_x),
+                                           x_break),
+                              limits = c(as.Date(start_x),
+                                         as.Date(end_x)))
+    }
+  } else if(any(xType == "integer")) {
+    if(is.null(x_break)) {
+      p <- p + 
+        ggplot2::scale_x_continuous(breaks = scales::breaks_extended(),
+                                    limits = c(start_x,
+                                               end_x))
+    } else {
+      p <- p + 
+        ggplot2::scale_x_continuous(breaks = seq(start_x,
+                                                 end_x,
+                                                 x_break),
+                                    limits = c(start_x,
+                                               end_x))
+    }
+  } else if(any(xType == "POSIXct")) {
+    if(is.null(x_break)) {
+      p <- p + 
+        ggplot2::scale_x_datetime(breaks = scales::breaks_pretty(),
+                                  limits = c(start_x, end_x))
+    } else {
+      if(any(class(x_break) != "difftime")) {
+        rlang::abort(paste("Please specify x_break as a difftime object when",
+                           "x is POSIXct."))
+      }
+      p <- p + 
+        ggplot2::scale_x_datetime(breaks = seq(start_x, end_x, x_break),
+                                  limits = c(start_x, end_x))
+    }
+  } else {
+    if(is.null(x_break)) {
+      p <- p + 
+        ggplot2::scale_x_continuous(breaks = scales::breaks_extended(),
+                                    limits = c(start_x, end_x))
+    } else {
+      p <- p + 
+        ggplot2::scale_x_continuous(breaks = seq(start_x, end_x, x_break),
+                                    limits = c(start_x, end_x))
+    }
+  }
+  
+  return(p)
+  
+}
diff --git a/renv.lock b/renv.lock
index 9068339..03c2b05 100644
--- a/renv.lock
+++ b/renv.lock
@@ -1225,6 +1225,32 @@
       "Maintainer": "Hadley Wickham <hadley@posit.co>",
       "Repository": "CRAN"
     },
+    "ggnewscale": {
+      "Package": "ggnewscale",
+      "Version": "0.5.2",
+      "Source": "Repository",
+      "Language": "en-GB",
+      "Title": "Multiple Fill and Colour Scales in 'ggplot2'",
+      "Authors@R": "person(given = \"Elio\", family = \"Campitelli\", role = c(\"cre\", \"aut\"), email = \"eliocampitelli@gmail.com\", comment = c(ORCID = \"0000-0002-7742-9230\"))",
+      "Description": "Use multiple fill and colour scales in 'ggplot2'.",
+      "License": "GPL-3",
+      "URL": "https://eliocamp.github.io/ggnewscale/, https://github.com/eliocamp/ggnewscale",
+      "BugReports": "https://github.com/eliocamp/ggnewscale/issues",
+      "Encoding": "UTF-8",
+      "Imports": [
+        "ggplot2 (>= 3.5.0)"
+      ],
+      "RoxygenNote": "7.3.2",
+      "Suggests": [
+        "testthat",
+        "vdiffr",
+        "covr"
+      ],
+      "NeedsCompilation": "no",
+      "Author": "Elio Campitelli [cre, aut] (ORCID: <https://orcid.org/0000-0002-7742-9230>)",
+      "Maintainer": "Elio Campitelli <eliocampitelli@gmail.com>",
+      "Repository": "CRAN"
+    },
     "ggplot2": {
       "Package": "ggplot2",
       "Version": "3.5.2",
diff --git a/tests/testthat/test_linetypes.R b/tests/testthat/test_linetypes.R
index 0260223..e351ace 100644
--- a/tests/testthat/test_linetypes.R
+++ b/tests/testthat/test_linetypes.R
@@ -1,4 +1,3 @@
-#load in test data
 test_data <- readRDS("testdata/test_data.rds")
 
 test_that("Linetypes are formed correctly", {
@@ -6,18 +5,29 @@ test_that("Linetypes are formed correctly", {
   test_plt <- autospc(test_data,
                       chart_type = "C'")
   
+  # layer 1 holds the centre line and control limits
+  layer_1 <- ggplot2::layer_data(test_plt, 1) %>% dplyr::arrange(x)
+  # layer 2 holds the data series
   layer_2 <- ggplot2::layer_data(test_plt, 2) %>% dplyr::arrange(x)
-  layer_4 <- ggplot2::layer_data(test_plt, 4) %>% dplyr::arrange(x)
   
+  # layer 1 has 3n rows, as it holds three series
+  expect_equal(nrow(layer_1), 450L)
+  # layer 2 has n rows, as it holds one series
+  expect_equal(nrow(layer_2), 150L)
+  
+  rle_layer_1 <- rle(layer_1$linetype)
   rle_layer_2 <- rle(layer_2$linetype)
-  rle_layer_4 <- rle(layer_4$linetype)
   
-  correct_answer_2 <- structure(list(lengths = 150L, values = "solid"),
+  correct_answer_1 <- structure(list(lengths = rep(c(1L, 2L),
+                                                   150),
+                                     values = rep(c("solid", "42"),
+                                                  150)),
                                 class = "rle")
-  correct_answer_4 <- structure(list(lengths = 150L, values = "42"),
+  correct_answer_2 <- structure(list(lengths = 150L,
+                                     values = "solid"),
                                 class = "rle")
   
+  expect_identical(rle_layer_1, correct_answer_1)
   expect_identical(rle_layer_2, correct_answer_2)
-  expect_identical(rle_layer_4, correct_answer_4)
   
 })
diff --git a/tests/testthat/test_median_plot.R b/tests/testthat/test_median_plot.R
index 996bd05..4f9c4fb 100644
--- a/tests/testthat/test_median_plot.R
+++ b/tests/testthat/test_median_plot.R
@@ -16,12 +16,13 @@ test_that("the series of medians being plotted are correctly calculated when flo
   chart_result_data <- chart_result$data 
   
   # Extract all median values from the result data  
-  result_median <- chart_result_data %>% 
+  result_median <- chart_result_data %>%
+    dplyr::filter(series == "y") %>%
     dplyr::filter(!is.na(median)) %>% 
     dplyr::pull(median)
   
   # Test that the length of the test_median__n points matches the length of the median points calculated
-  expect_equal(length(result_median),test_median_n)
+  expect_equal(length(result_median), test_median_n)
   
   # Identify how many distinct values for the median are being calculated 
   unique_result_median <- unique(result_median)
@@ -31,14 +32,17 @@ test_that("the series of medians being plotted are correctly calculated when flo
   
   # Summarises the column of medians into a singular median value
   result_median <- chart_result_data %>% 
+    dplyr::filter(series == "y") %>%
     dplyr::filter(!is.na(median)) %>% 
     dplyr::summarise(medi = median(median)) %>%
     dplyr::pull(medi)
   
   # Calculates the correct median from the data
   correct_median <- chart_result_data %>%
+    dplyr::filter(series == "y") %>%
     dplyr::slice((dplyr::n() - test_median_n + 1):dplyr::n()) %>%
-    dplyr::summarise(med = median(y, na.rm = TRUE)) %>%
+    dplyr::summarise(med = median(value,
+                                  na.rm = TRUE)) %>%
     dplyr::pull(med)
   
   # Test that the median displayed is calculated correctly 
@@ -80,6 +84,7 @@ test_that("the series of medians being plotted are correctly calculated when flo
   
   # Extract all median values from the result data  
   auto_result_median <- auto_median_result_data %>% 
+    dplyr::filter(series == "y") %>%
     dplyr::filter(!is.na(median)) %>% 
     dplyr::pull(median)
   
@@ -94,14 +99,16 @@ test_that("the series of medians being plotted are correctly calculated when flo
   
   # Summarises the column of medians into a singular median value
   auto_result_median <- auto_median_result_data %>% 
+    dplyr::filter(series == "y") %>%
     dplyr::filter(!is.na(median)) %>% 
     dplyr::summarise(med = median(median)) %>%
     dplyr::pull(med)
   
   # Calculates the correct median from the data
   correct_median_auto <- auto_median_result_data %>%
+    dplyr::filter(series == "y") %>%
     dplyr::slice((dplyr::n() - test_median_n + 1L):dplyr::n()) %>%
-    dplyr::summarise(med = median(y, na.rm = TRUE)) %>%
+    dplyr::summarise(med = median(value, na.rm = TRUE)) %>%
     dplyr::pull(med)
   
   # Test that the median displayed is calculated correctly 
@@ -153,6 +160,7 @@ test_that("NAs do not prevent median from being plotted",{
   
   # Test it is not NA and has the correct value
   result_median <- chart_result_data %>% 
+    dplyr::filter(series == "y") %>%
     dplyr::filter(!is.na(median)) %>% 
     dplyr::summarise(medi = median(median)) %>%
     dplyr::pull(medi)