Gallery: Barplots and time series line plots

altdoc/pkgdown.yml

@@ -2,7 +2,7 @@ altdoc: 0.7.2
 pandoc: '3.10'
 pkgdown: 2.1.3
 pkgdown_sha: ~
-last_built: 2026-06-18T17:31:05+0000
+last_built: 2026-06-20T19:18:00+0000
 urls:
   reference: https://grantmcdermott.com/tinyplot/man
   article: https://grantmcdermott.com/tinyplot/vignettes

vignettes/gallery.qmd

@@ -76,6 +76,20 @@ Click on a plot to get the link to its code.
 #| file: "gallery_figs/direct-labels-aq.R"
 ```
 
+```{r}
+#| lightbox:
+#|   group: r-graph
+#|   description: "[Code](https://github.com/grantmcdermott/tinyplot/blob/main/vignettes/gallery_figs/line-ipcc.R){target='_blank'}"
+#| file: "gallery_figs/line-ipcc.R"
+```
+
+```{r}
+#| lightbox:
+#|   group: r-graph
+#|   description: "[Code](https://github.com/grantmcdermott/tinyplot/blob/main/vignettes/gallery_figs/line-eustockmarkets.R){target='_blank'}"
+#| file: "gallery_figs/line-eustockmarkets.R"
+```
+
 ```{r}
 #| lightbox:
 #|   group: r-graph
@@ -90,6 +104,20 @@ Click on a plot to get the link to its code.
 #| file: "gallery_figs/ridge-aq.R"
 ```
 
+```{r}
+#| lightbox:
+#|   group: r-graph
+#|   description: "[Code](https://github.com/grantmcdermott/tinyplot/blob/main/vignettes/gallery_figs/barplot-fifa2026.R){target='_blank'}"
+#| file: "gallery_figs/barplot-fifa2026.R"
+```
+
+```{r}
+#| lightbox:
+#|   group: r-graph
+#|   description: "[Code](https://github.com/grantmcdermott/tinyplot/blob/main/vignettes/gallery_figs/barplot-meat.R){target='_blank'}"
+#| file: "gallery_figs/barplot-meat.R"
+```
+
 ```{r}
 #| lightbox:
 #|   group: r-graph

vignettes/gallery_figs/barplot-fifa2026.R

@@ -0,0 +1,31 @@
+fifa2026 = c(Spain = 14462, England = 12426, France = 12365, Germany = 11246, Portugal = 8909, Argentina = 8240,
+  Netherlands = 5576, Brazil = 4720, Belgium = 2992, Norway = 2602, Switzerland = 2083, Croatia = 1373,
+  Colombia = 1303, Japan = 1274, Morocco = 990, `United States` = 954, Uruguay = 945, Senegal = 945,
+  Sweden = 886, Ecuador = 752, Austria = 657, Turkey = 651, Canada = 616, Mexico = 601, `South Korea` = 481, 
+  `Ivory Coast` = 281, Algeria = 250, Australia = 222, `Czech Republic` = 212, Scotland = 206, Paraguay = 143,
+  Egypt = 121, `Bosnia and Herzegovina` = 113, `DR Congo` = 71, Ghana = 70, Tunisia = 59, Iran = 36,
+  `Cape Verde` = 31, Uzbekistan = 29, Panama = 26, Haiti = 24, `New Zealand` = 18, 
+  `Saudi Arabia` = 12, Curaçao = 11, `South Africa` = 7, Iraq = 6, Qatar = 2, Jordan = 1) / 1e5
+
+library("tinyplot")
+tinyplot(
+  x = 1:48,
+  y = fifa2026,
+  type = "barplot",
+  xlab = NA,
+  ylab = NA,
+  xaxt = "n",
+  yaxl = "%",
+  main = "Spain most likely to (not) win the 2026 FIFA World Cup",
+  cap = "Source: https://www.zeileis.org/news/fifa2026/",
+  theme = list("broadsheet", mar = c(4, 0.1, 0.6, 0.6), col.default = "#2A9D8F")
+)
+text(
+  1:48,
+  -0.001,
+  labels = names(fifa2026),
+  adj = c(1, 1.15),
+  cex = 0.5,
+  srt = 45,
+  xpd = TRUE
+)

vignettes/gallery_figs/barplot-meat.R

@@ -0,0 +1,25 @@
+meat = data.frame(
+  consumption = c(8.1, 14.6, 23.2, 30.8, 38, 0.7, 1.3, 4, 7.7, 9.2, 1.2, 1.7, 5.8, 10.3, 12.9, 4.5,
+    6.8, 17.9, 27.4, 36.8, 28.5, 29.7, 29.6, 29.7, 27.4, 55.5, 49.2, 44.7, 43.8, 37.8, 22.7, 31.1,
+    43.8, 50.9, 52.8, 15.2, 18.8, 21.8, 23, 21.6),
+  country = factor(rep(1:2, each = 20), labels = c("China", "United States")),
+  decade = factor(rep(paste0(197:201, "0s"), 8)),
+  type = factor(rep(c(1:4, 1:4), each = 5), labels = c("Pork", "Beef & other", "Poultry", "Fish & seafood"))
+)
+
+library("tinyplot")
+tinyplot(
+  consumption ~ decade | type,
+  facet = country ~ 1,
+  data = meat,
+  type = "barplot",
+  grid = "X",
+  flip = TRUE,
+  legend = list("bottom!", title = NULL),
+  theme = list("minimal", palette.qualitative = palette.colors(palette = "Set 3")[c(4, 6, 1, 5)]),
+  main = "Per capita meat and fish consumption by decade",
+  sub = "Measured in kilograms per person and year",
+  xlab = "",
+  ylab = "",
+  cap = "Source: Food and Agriculture Organization of the United Nations (via OurWorldInData.org)"
+)

vignettes/gallery_figs/line-eustockmarkets.R

@@ -0,0 +1,21 @@
+## note: replace with tinyplot.ts method once #558 is merged
+
+data("EuStockMarkets", package = "datasets")
+
+eu = data.frame(
+  time = rep(time(EuStockMarkets), ncol(EuStockMarkets)),
+  market = rep(colnames(EuStockMarkets), each = nrow(EuStockMarkets)),
+  value = as.numeric(EuStockMarkets)
+)
+
+library("tinyplot")
+tinyplot(
+  value ~ time | market,
+  data = eu,
+  facet = "by", legend = FALSE,
+  type = "l",
+  theme = "clean2",
+  main = "EU stock markets performance",
+  xlab = NA, ylab = NA,
+  yaxl = ","
+)

vignettes/gallery_figs/line-ipcc.R

@@ -0,0 +1,50 @@
+ipcc = data.frame(
+  scenario = rep(c("", "SSP1 - 1.9", "SSP1 - 2.6", "SSP2 - 4.5", "SSP3 - 7.0", "SSP5 - 8.5"), c(65, 85, 85, 85, 85, 85)), 
+  year = c(1950:2014, rep(2015:2099, 5)), 
+  temperature = c(
+    0.252, 0.275, 0.274, 0.253, 0.246, 0.273, 0.270, 0.268, 0.259, 0.258, 0.276, 0.279, 0.243, 0.146, 0.068, 0.089, 0.137, 0.132, 0.163, 0.198, 0.212, 0.229,
+    0.203, 0.226, 0.247, 0.212, 0.220, 0.278, 0.282, 0.311, 0.347, 0.378, 0.337, 0.232, 0.303, 0.355, 0.388, 0.438, 0.472, 0.516, 0.586, 0.565, 0.292, 0.348,
+    0.450, 0.491, 0.566, 0.638, 0.646, 0.682, 0.735, 0.799, 0.820, 0.856, 0.866, 0.884, 0.899, 0.929, 0.943, 0.962, 1.003, 1.036, 1.061, 1.085, 1.100,
+    1.099, 1.123, 1.149, 1.175, 1.201, 1.225, 1.252, 1.277, 1.300, 1.321, 1.344, 1.367, 1.388, 1.407, 1.426, 1.444, 1.459, 1.474, 1.488, 1.499, 1.510, 1.520,
+    1.528, 1.535, 1.543, 1.550, 1.554, 1.559, 1.563, 1.566, 1.568, 1.567, 1.567, 1.567, 1.566, 1.565, 1.565, 1.563, 1.561, 1.560, 1.557, 1.553, 1.550, 1.547,
+    1.544, 1.540, 1.537, 1.533, 1.529, 1.525, 1.521, 1.518, 1.514, 1.511, 1.507, 1.503, 1.499, 1.496, 1.492, 1.489, 1.487, 1.483, 1.479, 1.475, 1.469, 1.464,
+    1.459, 1.455, 1.451, 1.447, 1.444, 1.439, 1.434, 1.430, 1.424, 1.418, 1.414, 1.411, 1.407, 1.403, 1.400, 1.396, 1.392, 1.388, 1.385,
+    1.099, 1.125, 1.151, 1.177, 1.202, 1.229, 1.254, 1.279, 1.302, 1.325, 1.351, 1.373, 1.396, 1.417, 1.440, 1.461, 1.480, 1.499, 1.518, 1.534, 1.550, 1.565,
+    1.579, 1.595, 1.610, 1.622, 1.635, 1.648, 1.660, 1.670, 1.680, 1.691, 1.700, 1.708, 1.716, 1.724, 1.733, 1.740, 1.747, 1.754, 1.760, 1.766, 1.770, 1.774,
+    1.778, 1.783, 1.786, 1.788, 1.792, 1.795, 1.797, 1.799, 1.799, 1.799, 1.801, 1.801, 1.800, 1.801, 1.800, 1.799, 1.799, 1.798, 1.796, 1.794, 1.792, 1.789,
+    1.787, 1.784, 1.781, 1.778, 1.775, 1.772, 1.769, 1.764, 1.761, 1.759, 1.754, 1.750, 1.746, 1.742, 1.739, 1.735, 1.732, 1.727, 1.724,
+    1.103, 1.127, 1.152, 1.177, 1.203, 1.230, 1.256, 1.281, 1.307, 1.333, 1.358, 1.381, 1.406, 1.433, 1.458, 1.483, 1.506, 1.529, 1.551, 1.573, 1.594, 1.617,
+    1.641, 1.665, 1.689, 1.712, 1.737, 1.762, 1.787, 1.809, 1.831, 1.855, 1.880, 1.902, 1.922, 1.946, 1.973, 1.994, 2.017, 2.039, 2.061, 2.084, 2.104, 2.125,
+    2.146, 2.165, 2.186, 2.205, 2.225, 2.245, 2.263, 2.281, 2.298, 2.316, 2.334, 2.350, 2.366, 2.386, 2.401, 2.421, 2.437, 2.449, 2.469, 2.485, 2.499, 2.513,
+    2.527, 2.542, 2.557, 2.572, 2.586, 2.601, 2.614, 2.627, 2.639, 2.650, 2.665, 2.675, 2.687, 2.698, 2.710, 2.721, 2.730, 2.740, 2.748,
+    1.094, 1.118, 1.143, 1.170, 1.195, 1.220, 1.247, 1.273, 1.299, 1.324, 1.349, 1.376, 1.403, 1.432, 1.460, 1.488, 1.517, 1.546, 1.574, 1.602, 1.630, 1.660,
+    1.691, 1.720, 1.749, 1.781, 1.815, 1.847, 1.876, 1.908, 1.940, 1.974, 2.006, 2.037, 2.066, 2.101, 2.133, 2.167, 2.200, 2.235, 2.268, 2.300, 2.334, 2.368,
+    2.404, 2.439, 2.473, 2.510, 2.547, 2.584, 2.622, 2.659, 2.696, 2.730, 2.765, 2.799, 2.837, 2.876, 2.912, 2.950, 2.987, 3.028, 3.066, 3.102, 3.141, 3.181,
+    3.218, 3.254, 3.293, 3.332, 3.371, 3.409, 3.448, 3.490, 3.530, 3.568, 3.606, 3.645, 3.684, 3.721, 3.758, 3.796, 3.835, 3.872, 3.909,
+    1.110, 1.137, 1.166, 1.195, 1.224, 1.254, 1.283, 1.316, 1.347, 1.377, 1.410, 1.442, 1.475, 1.509, 1.544, 1.577, 1.610, 1.644, 1.678, 1.713, 1.748, 1.783,
+    1.818, 1.854, 1.892, 1.933, 1.973, 2.011, 2.052, 2.094, 2.136, 2.178, 2.219, 2.261, 2.304, 2.348, 2.393, 2.439, 2.486, 2.531, 2.573, 2.619, 2.668, 2.713,
+    2.757, 2.797, 2.845, 2.893, 2.942, 2.989, 3.036, 3.086, 3.135, 3.181, 3.229, 3.280, 3.329, 3.376, 3.426, 3.478, 3.528, 3.579, 3.630, 3.679, 3.734, 3.784,
+    3.833, 3.886, 3.939, 3.990, 4.042, 4.093, 4.145, 4.198, 4.249, 4.300, 4.351, 4.402, 4.451, 4.499, 4.549, 4.597, 4.644, 4.690, 4.735))
+
+library("tinyplot")
+tinyplot(
+  temperature ~ year | scenario,
+  data = ipcc,
+  type = "l",
+  theme = "socviz",
+  col = c("#000000", "#00a9d1", "#29416e", "#e58c35", "#dd4048", "#942324"),
+  lwd = 3,
+  grid = "xY",
+  legend = "direct",
+  main = "Global surface temperature change relative to 1850-1900",
+  sub = "Intergovernmental Panel on Climate Change (IPCC), Sixth Assessment Report",
+  xlab = "",
+  ylab = "Temperature change [°C]",
+  draw = {
+    abline(v = 2014.5, lty = 2, col = "gray60")
+    text(2014, 0, "Historical", pos = 2, col = "gray60")
+    text(2015, 0, "Projection", pos = 4, col = "gray60")
+  }
+)
+
+