有没有办法在 facet_grid 图中在 y 轴名称之外绘制分面条名称（切换 y）？
[英]Is there a way of plotting the facet strip names (switched y) outside the y-axis name in a facet_grid plot?
问题描述
I made a facetted plot (using ggplot2::facet_grid ) where I switched the y-axis, so the y-strip text is plotted on the left side of the plot and already used theme(strip.placement = "outside") to place the strip text outside the y-axis values.
我制作了一个ggplot2::facet_grid图（使用ggplot2::facet_grid ），在那里我切换了 y 轴，因此 y ggplot2::facet_grid本绘制在图的左侧并且已经使用了theme(strip.placement = "outside")来放置y 轴值之外的条带文本。 However, the strip titles are plotted between the y-axis name and the y-axis values.但是，条带标题绘制在 y 轴名称和 y 轴值之间。 I would like to plot the strip text outside the y-axis name, so that the y-axis name is plotted right next to the y-axis values.我想在 y 轴名称之外绘制条带文本，以便在 y 轴值旁边绘制 y 轴名称。 Is that possible?那可能吗？
Here is part of my data:这是我的部分数据：
df<-structure(list(place = c("Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site1", "Site1", "Site1", "Site1", "Site1",
"Site1", "Site1", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2", "Site2", "Site2", "Site2",
"Site2", "Site2", "Site2", "Site2"), year = c(2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
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2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
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2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L), month = c(1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L,
7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L), perc = c(0.01, 0.16, 0.06, 0.02, 0,
0, 0.01, 0.05, 0.17, 0.01, 0, 0.02, 0.17, 0.05, 0.02, 0, 0, 0.07,
0.15, 0.01, 0, 0, 0, 0.04, 0.03, 0.14, 0.02, 0.01, 0, 0, 0.01,
0.03, 0.14, 0.06, 0, 0, 0, 0, 0.02, 0.12, 0.03, 0.03, 0, 0, 0,
0, 0.02, 0.11, 0.05, 0.01, 0, 0, 0.02, 0.03, 0.13, 0.01, 0.01,
0, 0, 0, 0, 0.05, 0.08, 0.05, 0.01, 0, 0, 0, 0.04, 0.08, 0.05,
0.02, 0, 0, 0, 0.08, 0.09, 0.01, 0.01, 0, 0, 0, 0, 0.03, 0.14,
0.04, 0.03, 0.01, 0.01, 0, 0, 0.1, 0.1, 0.05, 0, 0, 0, 0, 0.11,
0.11, 0.02, 0.01, 0, 0, 0, 0, 0.03, 0.14, 0.07, 0.02, 0, 0, 0,
0.05, 0.02, 0.16, 0, 0.01, 0, 0, 0, 0, 0.08, 0.1, 0.06, 0.01,
0, 0, 0, 0.01, 0.04, 0.02, 0.03, 0.08, 0.02, 0.01, 0, 0, 0, 0,
0, 0, 0, 0, 0.02, 0.01, 0.05, 0.06, 0.04, 0, 0, 0, 0, 0, 0, 0,
0, 0.02, 0.06, 0.09, 0.02, 0, 0, 0, 0, 0, 0, 0.01, 0.02, 0.05,
0.06, 0.04, 0, 0, 0, 0.01, 0.01, 0.07, 0.07, 0.04, 0.01, 0, 0,
0, 0, 0.01, 0.04, 0.07, 0.04, 0.03, 0, 0, 0, 0, 0, 0.16, 0.03,
0.06, 0, 0, 0.15, 0.01, 0.08, 0.01, 0.11, 0.07, 0.07, 0, 0.09,
0.11, 0.04, 0, 0, 0.04, 0.11, 0.08, 0.02, 0, 0, 0, 0.06, 0.12,
0.05, 0.02, 0.01, 0, 0, 0.05, 0.08, 0.05, 0.02, 0.01, 0, 0.08,
0.07, 0.04, 0.01, 0, 0, 0, 0.04, 0.09, 0.05, 0.02, 0, 0, 0, 0.02,
0.06, 0.07, 0.03, 0.01, 0, 0, 0.01, 0.05, 0.07, 0.05, 0.02, 0,
0, 0, 0.01, 0.07, 0.05, 0.05, 0.01, 0, 0, 0, 0.01, 0.07, 0.08,
0.06, 0.03, 0, 0, 0, 0.04, 0.07, 0.06, 0.06, 0.02, 0, 0, 0.03,
0.09, 0.08, 0.03, 0.01, 0, 0, 0.04, 0.09, 0.08, 0.03, 0, 0, 0,
0.06, 0.08, 0.07, 0.03, 0.01, 0, 0, 0.03, 0.08, 0.07, 0.05, 0.01,
0, 0, 0, 0.03, 0.06, 0.05, 0.03, 0.02, 0.01, 0, 0, 0, 0, 0.02,
0.06, 0.05, 0.04, 0.02, 0.01, 0, 0, 0, 0, 0.03, 0.08, 0.05, 0.02,
0.01, 0, 0, 0, 0, 0.02, 0.05, 0.05, 0.03, 0.03, 0.02, 0.01, 0,
0, 0, 0, 0, 0, 0.02, 0.04, 0.05, 0.04, 0.02, 0.01, 0.01, 0, 0,
0, 0, 0.01, 0.03, 0.05, 0.05, 0.03, 0.02, 0, 0, 0, 0, 0, 0),
category = c("0", "1", "2", "3", "4", "0", "1", "2", "3",
"4", "5", "0", "1", "2", "3", "4", "0", "1", "2", "3", "4",
"5", "6", "0", "1", "2", "3", "4", "5", "0", "1", "2", "3",
"4", "5", "6", "7 - 14", "0", "1", "2", "3", "4", "5", "6",
"0", "1", "2", "3", "4", "5", "6", "7 - 14", "0", "1", "2",
"3", "4", "5", "6", "0", "1", "2", "3", "4", "5", "6", "7 - 14",
"0", "1", "2", "3", "4", "5", "6", "0", "1", "2", "3", "4",
"5", "6", "7 - 14", "0", "1", "2", "3", "4", "5", "6", "7 - 14",
"0", "1", "2", "3", "4", "5", "6", "0", "1", "2", "3", "4",
"5", "6", "0", "1", "2", "3", "4", "5", "6", "7 - 14", "0",
"1", "2", "3", "4", "5", "6", "7 - 14", "7 - 14", "0", "1",
"2", "3", "4", "5", "6", "0", "1", "2", "3", "4", "5", "6",
"7 - 14", "7 - 14", "7 - 14", "7 - 14", "7 - 14", "7 - 14",
"7 - 14", "0", "1", "2", "3", "4", "5", "6", "7 - 14", "7 - 14",
"7 - 14", "7 - 14", "7 - 14", "7 - 14", "0", "1", "2", "3",
"4", "5", "6", "7 - 14", "7 - 14", "7 - 14", "7 - 14", "1",
"2", "3", "4", "5", "6", "7 - 14", "7 - 14", "7 - 14", "7 - 14",
"1", "2", "3", "4", "5", "6", "7 - 14", "7 - 14", "1", "2",
"3", "4", "5", "6", "7 - 14", "7 - 14", "7 - 14", "7 - 14",
"7 - 14", "0", "1", "2", "3", "4", "0", "1", "2", "3", "0",
"1", "2", "3", "0", "1", "2", "3", "4", "0", "1", "2", "3",
"4", "5", "6", "0", "1", "2", "3", "4", "5", "6", "0", "1",
"2", "3", "4", "5", "0", "1", "2", "3", "4", "5", "6", "0",
"1", "2", "3", "4", "5", "6", "0", "1", "2", "3", "4", "5",
"6", "0", "1", "2", "3", "4", "5", "6", "7 - 14", "0", "1",
"2", "3", "4", "5", "6", "7 - 14", "0", "1", "2", "3", "4",
"5", "6", "7 - 14", "0", "1", "2", "3", "4", "5", "6", "0",
"1", "2", "3", "4", "5", "6", "0", "1", "2", "3", "4", "5",
"6", "0", "1", "2", "3", "4", "5", "6", "0", "1", "2", "3",
"4", "5", "6", "7 - 14", "0", "1", "2", "3", "4", "5", "6",
"7 - 14", "7 - 14", "7 - 14", "0", "1", "2", "3", "4", "5",
"6", "7 - 14", "7 - 14", "7 - 14", "0", "1", "2", "3", "4",
"5", "6", "7 - 14", "7 - 14", "0", "1", "2", "3", "4", "5",
"6", "7 - 14", "7 - 14", "7 - 14", "7 - 14", "0", "1", "2",
"3", "4", "5", "6", "7 - 14", "7 - 14", "7 - 14", "7 - 14",
"7 - 14", "7 - 14", "0", "1", "2", "3", "4", "5", "6", "7 - 14",
"7 - 14", "7 - 14", "7 - 14", "7 - 14")), row.names = c(NA,
-379L), class = c("tbl_df", "tbl", "data.frame"))
Here is the code I used to build the plot.这是我用来构建情节的代码。
library(ggplot2)
library(lemon)
ggplot(df,aes(x = month,
y = perc,
fill = category)) +
geom_col(position = "fill") +
facet_rep_grid(place ~ year ,
repeat.tick.labels = T,
switch = "y") +
theme_minimal() +
theme(strip.text.y = element_text(angle = 180),
strip.placement = "outside")
And the resulting the plot:以及由此产生的情节：
Finally, this is the desired plot:最后，这是所需的情节：
2 个解决方案
解决方案1
2 已采纳 2020-01-31 19:10:47
I don't think there is a way within ggplot2 , but it can be done with additional packages.我认为ggplot2 中没有办法，但可以通过其他包来完成。
library(ggplot2)
library(lemon)
library(cowplot)
library(grid)
g <- ggplot(df,aes(x = month,
y = perc,
fill = category)) +
geom_col(position = "fill") +
facet_rep_grid(place ~ year ,
repeat.tick.labels = T) +
theme_minimal() +
theme(strip.text.y = element_blank())
a <- textGrob('Site 1', gp=gpar(fontsize=10))
b <- textGrob('Site 2', gp=gpar(fontsize=10))
plot_grid(plot_grid(a, b, ncol = 1), g, rel_widths = c(0.1, 1))
解决方案2
1 2020-01-31 23:04:06
I found what I think is a more direct method (re-positioning the axis-title, than constructing and placing new strip entries):我发现我认为是一种更直接的方法（重新定位轴标题，而不是构建和放置新的条带条目）：
# as above but with ...
+ theme(strip.text.y = element_text(angle = 180),
axis.title.y = element_text(vjust = -10), # value by experiment
strip.placement = "outside")
The vjust argument was taken relative to the y axis title orientation. vjust参数是相对于 y 轴标题方向进行的。 Using hjust moved it up and down.使用 hjust 上下移动它。 I'm guessing that this is units of "points".我猜这是“点”的单位。 It appeared to me that the hjust values were interpreted in units of "upc".在我看来， hjust值是以“upc”为单位解释的。
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不同的y轴标签facet_grid和尺寸 - Different y-Axis Labels facet_grid and sizes
使用facet_grid的每个子图的y轴 - y-axis for each subplot using facet_grid
如何在R中的facet_grid中调整y轴 - how to adjust y-axis in facet_grid in R
让facet_grid中的每个图都有自己的Y轴值 - Let each plot in facet_grid have its own Y-axis value
如何使用`facet_grid`在secong plot中插入第二个y轴 - How to insert second y-axis in the secong plot using `facet_grid`
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