tomhopper · June 25, 2023 17:36 · Dec 9, 2019 · Dec 8, 2019 · Sep 21, 2014
diff --git a/plot_aligned_series2.R b/plot_aligned_series2.R
@@ -0,0 +1,39 @@
+# To plot two series vertically aligned with only one labelled x-axis,
+# we can remove the axes from the top plot and then plot the two graphs
+# together using either the egg package or the cowplot package
+
+library(ggplot2) # 3.2.1
+library(dplyr)
+library(lubridate)
+library(cowplot) # 1.0.0
+library(egg) # 0.4.5
+
+#' Create some data to play with. Two time series with the same timestamp.
+df <- data.frame(DateTime = ymd("2010-07-01") + c(0:8760) * hours(2), 
+                 series1 = rnorm(8761), 
+                 series2 = rnorm(8761, 100))
+
+#' Create the two plots.
+plot1 <- df %>%
+  select(DateTime, series1) %>%
+  na.omit() %>%
+  ggplot() +
+  geom_point(aes(x = DateTime, y = series1), size = 0.5, alpha = 0.75) +
+  ylab("Red dots / m") +
+  theme_minimal() +
+  theme(axis.title.x = element_blank(),
+        axis.text.x = element_blank())
+
+plot2 <- df %>%
+  select(DateTime, series2) %>%
+  na.omit() %>%
+  ggplot() +
+  geom_point(aes(x = DateTime, y = series2), size = 0.5, alpha = 0.75) +
+  ylab("Blue drops / L") +
+  theme_minimal() +
+  theme(axis.title.x = element_blank())
+
+# Draw the two plot aligned vertically, with the top plot 1/3 of the height
+# of the bottom plot
+cowplot::plot_grid(plot1, plot2, align = "v", ncol = 1, rel_heights = c(0.25, 0.75))
+egg::ggarrange(plot1, plot2, heights = c(0.25, 0.75))
diff --git a/plot_aligned_series.R b/plot_aligned_series.R
@@ -13,6 +13,7 @@
 library(ggplot2)
 library(grid)
 library(dplyr)
+library(lubridate)
 
 #' Create some data to play with. Two time series with the same timestamp.
 df <- data.frame(DateTime = ymd("2010-07-01") + c(0:8760) * hours(2), series1 = rnorm(8761), series2 = rnorm(8761, 100))

diff --git a/plot_aligned_series.R b/plot_aligned_series.R
@@ -0,0 +1,41 @@
+#' When plotting multiple data series that share a common x axis but different y axes,
+#' we can just plot each graph separately. This suffers from the drawback that the shared axis will typically
+#' not align across graphs due to different plot margins.
+#' One easy solution is to reshape2::melt() the data and use ggplot2's facet_grid() mapping. However, there is
+#' no way to label individual y axes.
+#' facet_grid() and facet_wrap() were designed to plot small multiples, where both x- and y-axis ranges are
+#' shared acros all plots in the facetting. While the facet_ calls allow us to use different scales with
+#' the \code{scales = "free"} argument, they should not be used this way.
+#' A more robust approach is to the grid package grid.draw(), rbind() and ggplotGrob() to create a grid of 
+#' individual plots where the plot axes are properly aligned within the grid.
+#' Thanks to https://rpubs.com/MarkusLoew/13295 for the grid.arrange() idea.
+
+library(ggplot2)
+library(grid)
+library(dplyr)
+
+#' Create some data to play with. Two time series with the same timestamp.
+df <- data.frame(DateTime = ymd("2010-07-01") + c(0:8760) * hours(2), series1 = rnorm(8761), series2 = rnorm(8761, 100))
+
+#' Create the two plots.
+plot1 <- df %>%
+  select(DateTime, series1) %>%
+  na.omit() %>%
+  ggplot() +
+  geom_point(aes(x = DateTime, y = series1), size = 0.5, alpha = 0.75) +
+  ylab("Red dots / m") +
+  theme_minimal() +
+  theme(axis.title.x = element_blank())
+
+plot2 <- df %>%
+  select(DateTime, series2) %>%
+  na.omit() %>%
+  ggplot() +
+  geom_point(aes(x = DateTime, y = series2), size = 0.5, alpha = 0.75) +
+  ylab("Blue drops / L") +
+  theme_minimal() +
+  theme(axis.title.x = element_blank())
+
+grid.newpage()
+grid.draw(rbind(ggplotGrob(plot1), ggplotGrob(plot2), size = "last"))
+
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