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feat(ggplot2): implement dashboard-metrics-tiles (#7599)
## Implementation: `dashboard-metrics-tiles` - r/ggplot2 Implements the **r/ggplot2** version of `dashboard-metrics-tiles`. **File:** `plots/dashboard-metrics-tiles/implementations/r/ggplot2.R` **Parent Issue:** #3791 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/26203610104)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Markus Neusinger <2921697+MarkusNeusinger@users.noreply.github.com>
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‎plots/dashboard-metrics-tiles/implementations/r/ggplot2.R‎

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#' anyplot.ai
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#' dashboard-metrics-tiles: Real-Time Dashboard Tiles
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#' Library: ggplot2 3.5.1 | R 4.4.1
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#' Quality: 92/100 | Created: 2026-05-21
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library(ggplot2)
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library(dplyr)
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library(scales)
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library(ragg)
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set.seed(42)
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# --- Theme tokens -----------------------------------------------------------
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THEME <- Sys.getenv("ANYPLOT_THEME", "light")
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PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
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ELEVATED_BG <- if (THEME == "light") "#FFFDF6" else "#242420"
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INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
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INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
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COL_GOOD <- "#009E73" # Okabe-Ito 1 — good / brand
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COL_WARNING <- "#E69F00" # Okabe-Ito 5 — warning
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COL_CRITICAL <- "#D55E00" # Okabe-Ito 2 — critical / bad
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# --- Data -------------------------------------------------------------------
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# Server health metrics snapshot (6 tiles in 3x2 grid)
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metric_names <- c("CPU Usage", "Memory", "Response Time", "Disk I/O", "Throughput", "Error Rate")
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value_nums <- c(45.2, 72.1, 118, 38.6, 1247, 0.82)
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value_labels <- c("45.2%", "72.1%", "118 ms", "38.6%", "1,247 req/s", "0.82%")
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changes <- c(-5.2, 8.1, -14.7, 3.4, 12.3, -22.5)
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statuses <- c("good", "warning", "good", "good", "good", "good")
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up_is_good <- c(FALSE, FALSE, FALSE, FALSE, TRUE, FALSE)
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n_metrics <- length(metric_names)
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n_pts <- 24
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status_colors <- ifelse(
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statuses == "critical", COL_CRITICAL,
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ifelse(statuses == "warning", COL_WARNING, COL_GOOD)
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)
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change_colors <- ifelse(
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(changes > 0 & !up_is_good) | (changes < 0 & up_is_good),
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COL_CRITICAL, COL_GOOD
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)
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arrows <- ifelse(changes > 0, "▲", "▼")
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change_labels <- paste0(arrows, " ", sprintf("%.1f", abs(changes)), "%")
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metrics_df <- data.frame(
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metric = factor(metric_names, levels = metric_names),
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value_label = value_labels,
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change_label = change_labels,
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status_color = status_colors,
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change_color = change_colors,
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stringsAsFactors = FALSE
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)
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# Generate sparkline histories (end pinned to current value, with slight trend)
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spark_list <- lapply(seq_len(n_metrics), function(i) {
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base <- value_nums[i]
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chg <- changes[i] / 100 * base
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steps <- rnorm(n_pts, mean = chg / n_pts, sd = base * 0.035)
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vals <- base - chg + cumsum(steps)
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vals[n_pts] <- base
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data.frame(
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metric = metric_names[i],
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t = seq_len(n_pts),
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val = vals,
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status_color = status_colors[i],
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stringsAsFactors = FALSE
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)
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})
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spark_df <- do.call(rbind, spark_list)
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spark_df$metric <- factor(spark_df$metric, levels = metric_names)
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# Normalise each sparkline to [0.15, 0.65] within the panel's y space
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spark_df <- spark_df |>
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group_by(metric) |>
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mutate(val_norm = rescale(val, to = c(0.15, 0.65))) |>
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ungroup()
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spark_end <- spark_df[spark_df$t == n_pts, ]
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# Annotation positions within the normalised [−0.18, 1.55] y range
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label_df <- data.frame(
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metric = metrics_df$metric,
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x_mid = (n_pts + 1) / 2,
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y_value = 1.35,
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y_change = 1.08,
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y_name = -0.06,
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value_label = metrics_df$value_label,
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change_label = metrics_df$change_label,
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status_color = metrics_df$status_color,
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change_color = metrics_df$change_color,
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name_color = INK_SOFT,
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stringsAsFactors = FALSE
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)
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# --- Plot -------------------------------------------------------------------
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p <- ggplot() +
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# Shaded area under sparkline
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geom_area(
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data = spark_df,
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aes(x = t, y = val_norm, fill = status_color, group = metric),
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alpha = 0.15,
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show.legend = FALSE
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) +
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# Sparkline
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geom_line(
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data = spark_df,
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aes(x = t, y = val_norm, color = status_color, group = metric),
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linewidth = 0.9,
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show.legend = FALSE
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) +
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# Terminal dot
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geom_point(
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data = spark_end,
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aes(x = t, y = val_norm, color = status_color),
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size = 2.0,
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show.legend = FALSE
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) +
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# KPI value — large, status-coloured
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geom_text(
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data = label_df,
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aes(x = x_mid, y = y_value, label = value_label, color = status_color),
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size = 7,
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fontface = "bold",
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show.legend = FALSE
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) +
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# Change indicator with directional arrow
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geom_text(
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data = label_df,
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aes(x = x_mid, y = y_change, label = change_label, color = change_color),
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size = 3.2,
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show.legend = FALSE
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) +
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# Metric name label at bottom of tile
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geom_text(
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data = label_df,
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aes(x = x_mid, y = y_name, label = metric, color = name_color),
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size = 3.5,
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fontface = "bold",
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show.legend = FALSE
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) +
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scale_color_identity() +
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scale_fill_identity() +
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facet_wrap(~metric, nrow = 2, ncol = 3) +
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scale_y_continuous(limits = c(-0.18, 1.55), expand = c(0, 0)) +
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scale_x_continuous(expand = expansion(mult = 0.05)) +
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labs(
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title = "Server Health · dashboard-metrics-tiles · r · ggplot2 · anyplot.ai"
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) +
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theme_minimal(base_size = 8) +
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theme(
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plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
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panel.background = element_rect(fill = ELEVATED_BG, color = INK_SOFT, linewidth = 0.4),
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panel.grid = element_blank(),
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axis.text = element_blank(),
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axis.title = element_blank(),
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axis.ticks = element_blank(),
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strip.text = element_blank(),
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plot.title = element_text(color = INK, size = 11, hjust = 0.5),
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plot.margin = margin(t = 20, r = 20, b = 20, l = 20),
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panel.spacing.x = unit(1.5, "lines"),
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panel.spacing.y = unit(1.5, "lines")
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)
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# --- Save -------------------------------------------------------------------
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ggsave(
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filename = sprintf("plot-%s.png", THEME),
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plot = p,
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device = ragg::agg_png,
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width = 8,
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height = 4.5,
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units = "in",
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dpi = 400
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)

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