R get linear regression equation for boxplots - r

I didn´t found a sufficient answer in this forum yet, so I decided to raise my own question.
I want to get the linear regression equation of a linear fit from a boxplot. I have this data:
library(ggplot2)
data <- structure(list(x = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L
), .Label = c("1", "2", "3", "4", "5", "6"), class = "factor"),
y = c(169, 79.5, 78.5, 75, 99.5, 68, 14, 30.5, 107.5, 51,
43, 33, 21.5, 35, 11, 1, 38, 54.5, 26.5, 143, 158, 171, 31.5,
67.5, 1, 57.5, 12, 36.5, 1, 23.5, 22.5, 71, 141, 218, 7.5,
1, 129, 144.5, 76, 46.5, 75.5, 45, 12, 24, 67, 65.5, 44.5,
37.5, 25.5, 19, 15, 1, 17.5, 50, 22.5, 90, 226, 220, 32,
69.5, 1, 79.5, 7, 44, 1, 15.5, 22, 75.5, 178, 153, 4.5, 1,
159, 89, 57, 71, 98.5, 47.5, 18.5, 30, 119, 57.5, 41, 33.5,
30, 31, 10, 1, 12, 43.5, 20.5, 98, 146.5, 145, 34, 64.5,
1, 40.5, 17, 41, 1, 14.5, 16.5, 71, 181, 168, 2, 1, 159,
103, 69, 65.5, 97.5, 37.5, 21, 15.5, 120.5, 46, 27, 29.5,
16.5, 20, 7.5, 1, 15.5, 42.5, 21.5, 111, 102.5, 124, 20.5,
51.5, 1, 22.5, 15, 42, 1, 13, 13.5, 64.5, 138, 155, 4.9,
1, 190, 89.5, 74.5, 79, 78, 59.5, 19.5, 21, 88.5, 44, 18,
19, 10, 13, 4, 1, 9.5, 44, 17, 140.5, 98, 112.5, 29.5, 62.56,
1, 31, 11.5, 49.5, 1, 10, 8.5, 40.5, 121, 141, 2.5, 1, 170,
87.5, 92, 77, 65, 34, 8, 26, 98, 51.5, 26, 19, 9, 8.5, 7.5,
1, 4.5, 0, 15.5, 80, 69, 59, 28, 44.5, 1, 38.5, 10, 51.5,
1, 3, 5, 65, 107, 152, 5, 1)), row.names = c(NA, -216L), class = "data.frame")
p <- ggplot(data = data) +
aes(x = x,
y = y) +
geom_boxplot(outlier.shape = NA) + geom_jitter(shape = 1, position = position_jitter(0.1)) +
ylim(0, NA) +
theme_light() +
geom_smooth(method = "lm",se = TRUE, formula = y ~ x, aes(group = 1))
print(p)
fit <- lm(y ~ x, data = data)
fit
which results in this output:
How can I extract the regression equation for this dataset? The function fit <- lm(y ~ x, data = data) just gives me one intercept and 5 coefficients, which is not my desired output. I want a simple regression equation in the form of y = a + bx.
How can I put this equation into the diagramm? I´ve already looked into ggpmisc::stat_poly_eq(), but this doesn´t seem to work with boxplot linear regression.
Can you guys help me out?

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putting segments on a plot with multiple plots and y variables

Is there a way to put arrows on a plot with multiple plots with different y axes? I would like to put arrows across the time series on the same x axis locations but different y locations. I cant just use "annotate("segment", x = 37, xend = 84, y = 0.0, yend = 0.0,colour = "black", size = 1, arrow = arrow(ends='both'))" because then it puts them at 0 on the y axis for all variables when I actually want to just put the arrows at the bottom of the y axis which is different for every variable.
Current code:
fin_plot <- ggplot(melted_data, aes(x = `Distance`, y = value, group = variable)) + geom_line() + theme_bw() + labs(y="", x= "") + theme_classic() + theme(text=element_text(size=16, family="serif", face = "bold", color = "black")) +
facet_wrap(variable~., scales = "free_y",ncol=2) +
scale_x_continuous(limits = c(0, 250),labels = scales::number_format(accuracy = 1)) + theme(axis.line = element_line(colour = 'black', size = 1)) +
theme(axis.ticks = element_line(colour = "black", size = 1)) + scale_y_continuous(labels = scales::number_format(accuracy = 0.1))+ theme(axis.ticks.length = unit(.3, "cm")) + coord_capped_cart(bottom='right', left='none', gap = 0.15) + geom_vline(xintercept=c(58, 132, 204, 250, 309), linetype='dashed', col = 'black')
Current output
desired output
data:
melted_data <- structure(list(Distance = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,
44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75,
76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,
92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105,
106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118,
119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131,
132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144,
145, 146, 147, 148, 149, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28,
29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76,
77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,
93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106,
107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119,
120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132,
133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145,
146, 147, 148, 149, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,
14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,
46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61,
62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,
78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93,
94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107,
108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120,
121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133,
134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146,
147, 148, 149, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46,
47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62,
63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78,
79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94,
95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108,
109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121,
122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134,
135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147,
148, 149, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95,
96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108,
109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121,
122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134,
135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147,
148, 149), variable = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L), .Label = c("Mg", "Mn", "Zn", "Ba", "All"), class = "factor"),
value = c(0.903247645, 0.912560748, 0.896003508, 0.909572697,
0.883631829, 0.905722594, 0.892465355, 0.909271173, 0.880506202,
0.889278401, 0.878534542, 0.959209459, 0.913303825, 0.929893977,
0.97778374, 0.9885554, 0.929716333, 1.028422583, 1.025638955,
1.011352651, 1.041343955, 1.092562951, 1.129761801, 1.088857171,
1.107257284, 1.116728405, 1.103053734, 1.041662037, 1.134182243,
1.104550315, 1.086952767, 1.106004784, 1.057688595, 1.034347579,
1.04641385, 1.139270945, 1.048446018, 1.033827731, 1.075554754,
1.029893202, 1.074749532, 1.001626205, 0.977053541, 0.987467665,
0.999540478, 0.945184816, 0.959677178, 0.962807712, 0.967023936,
1.024286493, 0.881264816, 0.967181342, 1.000316876, 0.956168258,
1.003214572, 1.00047837, 0.940103474, 0.929875987, 0.928227112,
0.982410241, 0.983035162, 0.976666772, 1.019755049, 1.075189042,
0.975380543, 0.981316782, 0.986876269, 1.026690916, 1.052379934,
1.001547298, 0.979888683, 1.008209647, 0.976098272, 0.944479556,
0.996767684, 1.018077758, 1.028862706, 1.08510417, 1.08963868,
1.048481179, 1.139954126, 1.107066353, 1.122920581, 1.23904326,
1.19449336, 1.179971969, 1.165865352, 1.068804094, 1.099436469,
1.073307737, 1.07045113, 1.101007051, 1.011962649, 1.11202545,
1.097883672, 1.05361424, 0.993283703, 1.046635444, 1.04951188,
1.055736151, 1.063705172, 0.977095039, 1.015650848, 1.029367222,
1.003814349, 0.973376993, 1.021665177, 0.925511352, 1.014703757,
0.933654542, 1.027336075, 0.961163947, 1.022921765, 0.910164297,
0.937410814, 0.935246588, 0.925900983, 0.934477753, 0.927973832,
0.946372309, 0.950554394, 0.9386026, 1.000712639, 0.947846812,
0.953585987, 0.967735737, 0.927914753, 0.943303715, 0.935435884,
0.987648375, 0.902379461, 0.939086878, 1.018529942, 0.973874968,
0.974093087, 0.984149676, 0.948669001, 0.934863295, 1.011232041,
0.942884239, 0.978044788, 1.023700208, 1.011714275, 0.999153709,
1.06822476, 0.967735328, 1.131133479, 1.011068503, 1.034903609,
0.086720869, 0.113119382, 0.088197332, 0.081547788, 0.079373211,
0.07888827, 0.072865285, 0.079637996, 0.066314774, 0.097585729,
0.185034982, 0.214466904, 0.294317625, 0.481389256, 0.531196058,
0.715842439, 0.865098887, 0.987242052, 1.081028291, 1.240920518,
1.313524957, 1.543771699, 1.78495042, 1.746572555, 2.048760527,
2.101438775, 1.967474033, 2.000286925, 2.014020838, 1.924470659,
1.75696549, 1.786681246, 1.633290961, 1.455799758, 1.315346538,
1.435348984, 1.27887702, 1.152818928, 1.095127218, 0.987502349,
1.062278922, 0.898540082, 0.83617998, 0.889057689, 0.825563648,
0.788347646, 0.790973555, 0.775541228, 0.815063004, 0.848723108,
0.66783059, 0.672629631, 0.747809615, 0.72338158, 0.666220438,
0.664051795, 0.597260657, 0.689282162, 0.663808452, 0.678551141,
0.672917354, 0.686199986, 0.724202364, 0.746195474, 0.686135659,
0.654148537, 0.713488795, 0.72446665, 0.699529989, 0.630120423,
0.661767463, 0.663290351, 0.705879842, 0.709399338, 0.76228353,
0.714368918, 0.720561695, 0.837036666, 0.923882149, 1.014163852,
1.221410703, 1.315825246, 1.368054705, 1.641746627, 1.630198312,
1.698589629, 1.562956393, 1.427322658, 1.53964983, 1.574583495,
1.527101216, 1.380123116, 1.28649445, 1.29251968, 1.330565441,
1.317758525, 1.19292313, 1.217953538, 1.218591815, 1.163372928,
1.091026791, 0.878691182, 0.903966928, 0.917620557, 0.838430901,
0.825709255, 0.839298558, 0.76309434, 0.97617394, 0.739885015,
0.822159341, 0.785335779, 0.771926988, 0.766619321, 0.832448556,
0.733734124, 0.787221188, 0.685452005, 0.740552711, 0.707414697,
0.781271754, 0.72652958, 0.729470139, 0.71649368, 0.681176551,
0.683977986, 0.711079301, 0.681092777, 0.747615639, 0.700953146,
0.692246657, 0.673560118, 0.820384633, 0.740567172, 0.72070082,
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3.117943428)), row.names = c(NA, -745L), class = "data.frame")

Use geom_segment - this allows you to make use of the faceting variable. You will then want to pass a data frame with the respective x/xend/y/yend.
library(dplyr)
## create a data frame first for the segments
## it makes sense to use the mininimum of your y for each facet
annot_df <- melted_data %>%
group_by(variable) %>%
summarise(y = min(value), yend = min(value), x = 25, xend = 75)
ggplot(melted_data, aes(x = Distance, y = value, group = variable)) +
geom_line() +
## now use the new data frame for geom_segment
geom_segment(data = annot_df, aes(x = x, xend = xend, y = y, yend = yend),
arrow = arrow(ends = "both", length = unit(5, "pt"))) +
facet_wrap(variable~., scales = "free_y",ncol=2)
Created on 2022-07-14 by the reprex package (v2.0.1)

Plotting multiple variables in time series with greyscale and shapes [duplicate]

This question already has answers here:
Changing the line type in the ggplot legend
(2 answers)
ggplot2 for grayscale printouts
(3 answers)
Closed 7 months ago.
I am trying to make a time-series graph with multiple y values. I would like to change the shape of the different variables so some are solid, some are dashed etc. I would also like all the colors to be on greyscale.
Does anyone know how I can accomplish this?
I know how to melt my data so that I can plot them all together by the value of the variables but right now I cannot get the shapes to change or the greyscale. Thank you in advance.
ggplot(melted_data, aes(x = Distance, y = value, color = variable)) + geom_line()
data <- structure(list(Distance = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,
44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75,
76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,
92, 93, 94, 95, 96, 97, 98, 99, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26,
27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42,
43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58,
59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, 99, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41,
42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57,
58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 1, 2, 3, 4, 5, 6, 7,
8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55,
56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87,
88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99), variable = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
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2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
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3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("Mg",
"Mn", "Zn", "Ba"), class = "factor"), value = c(0.903247645,
0.912560748, 0.896003508, 0.909572697, 0.883631829, 0.905722594,
0.892465355, 0.909271173, 0.880506202, 0.889278401, 0.878534542,
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1.122761046, 1.137397845, 1.173190388, 1.138033979, 1.126494557,
1.144871399, 1.087042815, 0.981750792, 0.992888445, 0.955352455,
1.074357698, 1.027127808, 1.083248059, 1.010304962, 1.037776316,
1.052809984, 0.742734852, 0.839492568, 0.743899849, 0.817080816,
0.773569657, 0.735728339, 0.715168283, 0.78077814, 0.694280484,
0.773303425, 0.768041196, 0.883401699, 0.818274274, 0.715927964,
0.696938222, 0.832246446, 0.73089346, 0.790965216, 0.799717389,
0.865896893, 0.946771069, 0.954212275, 1.023740345, 1.027036123,
1.086336263, 1.064542815, 0.9463809, 0.924081609, 0.999832641,
0.911277648, 0.922871168, 0.953134033, 0.786732115, 0.802026729,
0.832863371, 0.863952475, 0.817833153, 0.748586924, 0.72095701,
0.738213943, 0.672736744, 0.704947698, 0.531743532, 0.634123809,
0.683548549, 0.733277161, 0.608993729, 0.752162246, 0.568705823,
0.643172511, 0.597251486, 0.655514695, 0.583437677, 0.557676441,
0.646713866, 0.527005047, 0.578023512, 0.576281064, 0.600923204,
0.578475648, 0.551957027, 0.585007991, 0.623858699, 0.630936819,
0.636198589, 0.565476603, 0.658861425, 0.577557604, 0.629178306,
0.646092809, 0.566079299, 0.60953767, 0.680135261, 0.500802233,
0.704656678, 0.61109605, 0.645344144, 0.667139888, 0.734969576,
0.780062983, 0.783090234, 0.83005691, 0.905356723, 0.933746319,
0.947613375, 0.923115827, 0.873482691, 0.746883952, 0.850273618,
0.795256154, 0.800825928, 0.772630039, 0.749567395, 0.7823457,
0.772609842, 0.736269985, 0.699705666, 0.716860238, 0.65909369
)), row.names = c(NA, -396L), class = "data.frame")

You can use the linetype parameter with the aestethics :
ggplot(data) +
geom_line(aes(x = Distance, y = value, color = variable, linetype = variable))

ggplot2 - Survival Swimmer Plot Not Displaying Sorted Values

Using this question I've been assembling a customized Swimmer Plot, but despite my having sorted the patients by Therapy.Length, when I try to plot it the second half of the bars often come out much longer than they should be - putting the graph out of order.
I've checked and the symbols are in the correct place even when the bar is too long, so somehow the bar lengths are getting extended. By commenting out scale_y_continuous chunk, I'm able to get the proper length on the bars, but then all of the symbol placement is compressed.
ggplot(dat,
aes(Patient.ID, Therapy.Length)) +
geom_bar(stat="identity", aes(fill=factor(Disease.Stage)), width=0.7) +
geom_point(data=dat, aes(Patient.ID, value, colour=variable, shape=variable), size=4) +
geom_segment(data=dat %>% filter(Continued == 1),
aes(x=Patient.ID, xend=Patient.ID, y=Therapy.Length + 0.1, yend=Therapy.Length + 20),
arrow=arrow(type="closed", length=unit(0.13,"in"))) +
coord_flip() +
scale_fill_manual(values=hcl(seq(15,375,length.out=5)[1:4],100,70)) +
scale_colour_manual(values=c(hcl(seq(15,375,length.out=3)[1:2],100,40),c("black","darkgreen"))) +
scale_y_continuous(limits=c(-1,max(dat$Therapy.Length)), breaks=seq(0,max(dat$Therapy.Length),30)) +
labs(fill="Disease Stage", colour="", shape="", x="Subject Received Study Drug")
+ theme_bw() +
theme(panel.grid.minor=element_blank(),panel.grid.major=element_blank(),
axis.text.y=element_blank(),axis.ticks.y=element_blank())
Here's the rest of the code: [x]
ANSWER:
dat had originally been melted – changed dat to be unmelted (and created dat.m to be the melted version), and supplied dat.mto geom_point and geom_segment for adding points to bars.
data:
structure(list(Patient.ID = structure(c(1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 1L, 2L, 3L, 4L, 5L,
6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L), .Label = c("13",
"5", "14", "11", "6", "2", "7", "12", "3", "8", "1", "10", "4",
"15", "9"), class = "factor"), Disease.Stage = c(1L, 2L, 4L,
1L, 2L, 3L, 1L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 2L, 4L, 1L,
2L, 3L, 1L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 2L, 4L, 1L, 2L,
3L, 1L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L, 1L, 2L, 4L, 1L, 2L, 3L,
1L, 1L, 3L, 2L, 1L, 1L, 3L, 2L, 3L), Response.Start = c(15, 40,
51, 26, 36, 26, 32, 43, 67, 80, 93, 105, 160, 34, 94, 15, 40,
51, 26, 36, 26, 32, 43, 67, 80, 93, 105, 160, 34, 94, 15, 40,
51, 26, 36, 26, 32, 43, 67, 80, 93, 105, 160, 34, 94, 15, 40,
51, 26, 36, 26, 32, 43, 67, 80, 93, 105, 160, 34, 94), Therapy.Length = c(74,
84, 84, 108, 128, 185, 194, 198, 257, 274, 293, 311, 325, 336,
357, 74, 84, 84, 108, 128, 185, 194, 198, 257, 274, 293, 311,
325, 336, 357, 74, 84, 84, 108, 128, 185, 194, 198, 257, 274,
293, 311, 325, 336, 357, 74, 84, 84, 108, 128, 185, 194, 198,
257, 274, 293, 311, 325, 336, 357), Continued = c(1, 1, 1, NA,
1, NA, 1, NA, 1, NA, 1, NA, 1, NA, 1, 1, 1, 1, NA, 1, NA, 1,
NA, 1, NA, 1, NA, 1, NA, 1, 1, 1, 1, NA, 1, NA, 1, NA, 1, NA,
1, NA, 1, NA, 1, 1, 1, 1, NA, 1, NA, 1, NA, 1, NA, 1, NA, 1,
NA, 1), variable = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L), .Label = c("Response.End", "Durable", "Complete",
"Partial"), class = "factor"), value = c(40, 78, 78, 106, 89,
177, 108, 101, 138, 209, 279, 244, 311, 167, 271, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA, NA, NA, 40, NA, NA,
NA, NA, 32, 43, NA, NA, 93, NA, 160, NA, 94, 15, NA, 51, 26,
36, 26, NA, NA, 67, 80, NA, 105, NA, 34, NA)), row.names = c(NA,
-60L), .Names = c("Patient.ID", "Disease.Stage", "Response.Start",
"Therapy.Length", "Continued", "variable", "value"), class = "data.frame")

How can I write a function to shift regression line for each Facet?

fit<-lm(log(all$fd) ~ log(all$area))
fintercept<-fit$coefficients[[1]] #intercept
fslope<-fit$coefficients[[2]] #slope
interceptmax<-max(log(all$fd)-fslope*log(all$area))
ggplot(all, aes(x=log(area), y=log(fd))) +
geom_point()+
geom_abline(aes(intercept=interceptmax,slope=fslope))+ #shifted regression line
#facet_wrap(~id)+
theme_bw()+
theme(panel.grid.major = element_line(colour = "#808080"))+
ggsave('test.png',width=6, height=4,dpi=300)
This ggplot2 gives me an envelope curve (a shifted regression line). If I remove facet_wrap(~id), it works as intended. But I want the lines to be computed for every facet separately. Any suggestions how I can do this for every facet? (Similar to how using 'lm' inside ggplot2 works)
Here subset of 'all' is:
structure(list(fd = c(11, 7.75, 55.25, 45.25, 9.5, 89, 14.5,
8, 84.25, 5.25, 79.5, 7.75, 71, 38.5, 242.25, 33, 32, 19, 58.5,
249.25, 19, 72.5, 6.25, 27.0333333333333, 26.5, 81, 30, 29, 39.75,
18.5, 64.25, 91, 4.5, 30.5, 74, 256.75, 9, 81, 27, 7.5, 107,
26.75, 47.25, 16, 57, 37, 48.25, 48, 36, 147.25, 23.5, 42, 1.08333333333333,
21.5, 6.51666666666667, 198, 47.5, 8.75, 16, 43.5, 34.75, 30.25,
132.25, 2.25, 12.5, 225, 37, 17.25, 63.5, 48, 19.75, 12, 62.5,
64, 27, 11, 72.25, 246, 27.75, 15.5, 178, 93.75, 3.75, 3, 46.25,
4, 6.25, 5.25, 20, 44, 44.5, 1, 33, 18.25, 14.5, 29.25, 9, 33,
133, 67), area = c(20168.2374, 432.528, 5780.8535, 1411.5435,
543.8975, 660.447, 24995.9752, 543.8975, 2659.9178, 277.1287,
147.8883, 153.0683, 2217.0298, 1188.8045, 4237.2205, 489.5078,
1051.5352, 1362.3337, 1401.1836, 169.3852, 1333.8439, 1051.5352,
29.5259, 1429.6734, 668.2169, 17068.0216, 660.447, 16860.8226,
116.5495, 3820.2325, 784.7664, 841.7461, 1696.4422, 85.9876,
2066.8105, 2090.1204, 121.7294, 9999.9441, 127.4274, 1152.5447,
934.9857, 1424.4935, 1774.1419, 543.8975, 784.7664, 237.5019,
3486.124, 1080.025, 6164.1717, 3348.8546, 236.2069, 510.2277,
31.5979, 916.8558, 1994.2908, 3501.6639, 1152.5447, 486.9178,
533.5376, 271.9488, 336.6985, 1103.3349, 9764.2552, 36.7778,
2375.0191, 512.8176, 422.1681, 859.8761, 1118.8749, 237.5019,
133.6434, 453.2479, 1787.0918, 6063.1622, 237.5019, 1383.0537,
668.2169, 1424.4935, 621.5971, 1486.6532, 7355.5662, 984.1955,
68.8937, 154.6223, 116.5495, 1665.3624, 43.5118, 450.6579, 510.2277,
1494.4231, 404.0381, 598.2873, 339.2884, 12406.043, 274.5387,
151.2553, 753.6865, 29059.6666, 3470.5841, 1885.5113), id = structure(c(3L,
2L, 2L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 3L,
4L, 3L, 1L, 3L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 4L, 4L, 3L, 4L, 4L,
3L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 4L, 2L, 4L, 3L, 4L, 4L, 3L, 4L,
3L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 4L, 3L, 4L, 4L, 3L, 4L, 4L, 4L,
4L, 4L, 2L, 3L, 4L, 2L, 3L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 2L,
1L, 4L, 2L, 4L, 2L, 4L, 2L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 3L, 4L,
2L, 2L, 4L), .Label = c("Csb", "Dfb(E)", "Dfa", "Cfa"), class = "factor")), .Names = c("fd",
"area", "id"), row.names = c("65775", "61848", "11286", "22467",
"34601", "53841", "14661", "8941", "88607", "47681", "7898",
"9598", "40615", "35550", "70985", "64634", "43864", "88065",
"37520", "100794", "74916", "76759", "48928", "17575", "7424",
"30848", "53970", "65662", "27392", "82248", "48004", "93560",
"51147", "42321", "30070", "22096", "25575", "49067", "23702",
"65877", "53617", "90727", "59449", "34568", "48155", "96101",
"31358", "40150", "75458", "71566", "1687", "86603", "77451",
"68075", "14478", "69151", "66028", "77394", "68580", "16328",
"26945", "73615", "24179", "19497", "82448", "25098", "23565",
"8113", "66312", "96062", "60313", "34767", "97877", "48598",
"96135", "36877", "7309", "71065", "49622", "65051", "55340",
"105109", "26480", "4550", "18935", "61714", "31667", "55035",
"27563", "17332", "35694", "20092", "44334", "21344", "22303",
"64816", "12814", "12391", "52770", "84979"), class = "data.frame")
Follow up to: How can I shift the regression line?

In order to have a different line per facet, you can calculate the slope and desired intercept separately for each id. It's often easiest to simply make a new dataset of the desired values and use it in geom_abline. This new dataset needs to contain an id column as well as the values to plot so you can get separate info per facet.
There are lots of ways that you could go about creating this dataset, including fitting the regressions one by one and collecting the values "by hand". I'll use functions from package dplyr to calculate the regression per id, save the slope, and calculate the new intercept using your formula.
library(dplyr)
all2 = all %>%
group_by(id) %>%
do({model = lm(log(fd) ~ log(area), data = .)
data.frame(fslope = coef(model)[2], interceptmax = max(log(.$fd) - coef(model)[2]*log(.$area)))
})
all2
Source: local data frame [4 x 3]
Groups: id [4]
id fslope interceptmax
(fctr) (dbl) (dbl)
1 Csb -0.5556930 8.3703705
2 Dfb(E) 0.5378457 0.5057893
3 Dfa 0.1227013 4.6143276
4 Cfa 0.3247770 3.3895178
Now use the new dataset in geom_abline.
ggplot(all, aes(x=log(area), y=log(fd))) +
geom_point() +
geom_abline(data = all2, aes(intercept=interceptmax, slope=fslope)) + #shifted regression line
facet_wrap(~id) +
theme_bw() +
theme(panel.grid.major = element_line(colour = "#808080"))
The resulting plot has different lines for each facet.

How can I shift the regression line?

pfacet<-function(data,x,y){
ggplot(data, aes_string(x=x, y=y)) +
stat_density2d(aes(fill=..level..,contour=TRUE), geom="density2d",color="black") +
geom_smooth(method=lm, se=FALSE,color="black") +
facet_wrap(~id)+
theme_bw()+
theme(panel.grid.major = element_line(colour = "#808080"))+
guides(fill=FALSE)
}
Plotting
pfacet(data=df,x='log(area)',y='log(fd)')+
ggsave('test.png',width=6, height=4,dpi=300)
This gives me this figure.
BUT, I want to shift these regression lines to the highest value of each facet. i.e. make it an envelope curve. Eg. http://specialpapers.gsapubs.org/content/401/63/F11.large.jpg
Ordinarily, I would simply make a regression line and shift it, but I don't know how to do this inside a facet. Could you please give some pointers?
DATA
dput(droplevels(head(df, 100)))
structure(list(fd = c(11, 7.75, 55.25, 45.25, 9.5, 89, 14.5,
8, 84.25, 5.25, 79.5, 7.75, 71, 38.5, 242.25, 33, 32, 19, 58.5,
249.25, 19, 72.5, 6.25, 27.0333333333333, 26.5, 81, 30, 29, 39.75,
18.5, 64.25, 91, 4.5, 30.5, 74, 256.75, 9, 81, 27, 7.5, 107,
26.75, 47.25, 16, 57, 37, 48.25, 48, 36, 147.25), area = c(20168.2374,
432.528, 5780.8535, 1411.5435, 543.8975, 660.447, 24995.9752,
543.8975, 2659.9178, 277.1287, 147.8883, 153.0683, 2217.0298,
1188.8045, 4237.2205, 489.5078, 1051.5352, 1362.3337, 1401.1836,
169.3852, 1333.8439, 1051.5352, 29.5259, 1429.6734, 668.2169,
17068.0216, 660.447, 16860.8226, 116.5495, 3820.2325, 784.7664,
841.7461, 1696.4422, 85.9876, 2066.8105, 2090.1204, 121.7294,
9999.9441, 127.4274, 1152.5447, 934.9857, 1424.4935, 1774.1419,
543.8975, 784.7664, 237.5019, 3486.124, 1080.025, 6164.1717,
3348.8546), id = structure(c(3L, 2L, 2L, 4L, 4L, 3L, 4L, 4L,
4L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 3L, 4L, 3L, 1L, 3L, 4L, 4L, 4L,
4L, 4L, 3L, 3L, 4L, 4L, 3L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 3L,
3L, 4L, 2L, 4L, 3L, 4L, 4L, 3L, 4L, 3L), .Label = c("Csb", "Dfb(E)",
"Dfa", "Cfa"), class = "factor")), .Names = c("fd", "area", "id"
), row.names = c("65775", "61848", "11286", "22467", "34601",
"53841", "14661", "8941", "88607", "47681", "7898", "9598", "40615",
"35550", "70985", "64634", "43864", "88065", "37520", "100794",
"74916", "76759", "48928", "17575", "7424", "30848", "53970",
"65662", "27392", "82248", "48004", "93560", "51147", "42321",
"30070", "22096", "25575", "49067", "23702", "65877", "53617",
"90727", "59449", "34568", "48155", "96101", "31358", "40150",
"75458", "71566"), class = "data.frame")
> dput(droplevels(head(ddf2, 100)))
structure(list(fd = c(11, 7.75, 55.25, 45.25, 9.5, 89, 14.5,
8, 84.25, 5.25, 79.5, 7.75, 71, 38.5, 242.25, 33, 32, 19, 58.5,
249.25, 19, 72.5, 6.25, 27.0333333333333, 26.5, 81, 30, 29, 39.75,
18.5, 64.25, 91, 4.5, 30.5, 74, 256.75, 9, 81, 27, 7.5, 107,
26.75, 47.25, 16, 57, 37, 48.25, 48, 36, 147.25, 23.5, 42, 1.08333333333333,
21.5, 6.51666666666667, 198, 47.5, 8.75, 16, 43.5, 34.75, 30.25,
132.25, 2.25, 12.5, 225, 37, 17.25, 63.5, 48, 19.75, 12, 62.5,
64, 27, 11, 72.25, 246, 27.75, 15.5, 178, 93.75, 3.75, 3, 46.25,
4, 6.25, 5.25, 20, 44, 44.5, 1, 33, 18.25, 14.5, 29.25, 9, 33,
133, 67), area = c(20168.2374, 432.528, 5780.8535, 1411.5435,
543.8975, 660.447, 24995.9752, 543.8975, 2659.9178, 277.1287,
147.8883, 153.0683, 2217.0298, 1188.8045, 4237.2205, 489.5078,
1051.5352, 1362.3337, 1401.1836, 169.3852, 1333.8439, 1051.5352,
29.5259, 1429.6734, 668.2169, 17068.0216, 660.447, 16860.8226,
116.5495, 3820.2325, 784.7664, 841.7461, 1696.4422, 85.9876,
2066.8105, 2090.1204, 121.7294, 9999.9441, 127.4274, 1152.5447,
934.9857, 1424.4935, 1774.1419, 543.8975, 784.7664, 237.5019,
3486.124, 1080.025, 6164.1717, 3348.8546, 236.2069, 510.2277,
31.5979, 916.8558, 1994.2908, 3501.6639, 1152.5447, 486.9178,
533.5376, 271.9488, 336.6985, 1103.3349, 9764.2552, 36.7778,
2375.0191, 512.8176, 422.1681, 859.8761, 1118.8749, 237.5019,
133.6434, 453.2479, 1787.0918, 6063.1622, 237.5019, 1383.0537,
668.2169, 1424.4935, 621.5971, 1486.6532, 7355.5662, 984.1955,
68.8937, 154.6223, 116.5495, 1665.3624, 43.5118, 450.6579, 510.2277,
1494.4231, 404.0381, 598.2873, 339.2884, 12406.043, 274.5387,
151.2553, 753.6865, 29059.6666, 3470.5841, 1885.5113), id = structure(c(3L,
2L, 2L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 3L,
4L, 3L, 1L, 3L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 4L, 4L, 3L, 4L, 4L,
3L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 4L, 2L, 4L, 3L, 4L, 4L, 3L, 4L,
3L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 4L, 3L, 4L, 4L, 3L, 4L, 4L, 4L,
4L, 4L, 2L, 3L, 4L, 2L, 3L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 2L,
1L, 4L, 2L, 4L, 2L, 4L, 2L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 3L, 4L,
2L, 2L, 4L), .Label = c("Csb", "Dfb(E)", "Dfa", "Cfa"), class = "factor")), .Names = c("fd",
"area", "id"), row.names = c("65775", "61848", "11286", "22467",
"34601", "53841", "14661", "8941", "88607", "47681", "7898",
"9598", "40615", "35550", "70985", "64634", "43864", "88065",
"37520", "100794", "74916", "76759", "48928", "17575", "7424",
"30848", "53970", "65662", "27392", "82248", "48004", "93560",
"51147", "42321", "30070", "22096", "25575", "49067", "23702",
"65877", "53617", "90727", "59449", "34568", "48155", "96101",
"31358", "40150", "75458", "71566", "1687", "86603", "77451",
"68075", "14478", "69151", "66028", "77394", "68580", "16328",
"26945", "73615", "24179", "19497", "82448", "25098", "23565",
"8113", "66312", "96062", "60313", "34767", "97877", "48598",
"96135", "36877", "7309", "71065", "49622", "65051", "55340",
"105109", "26480", "4550", "18935", "61714", "31667", "55035",
"27563", "17332", "35694", "20092", "44334", "21344", "22303",
"64816", "12814", "12391", "52770", "84979"), class = "data.frame")

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