I have a faceted plot like this:
df %>%
ggplot(aes(x = x, y = IND_all, colour = Story))+
facet_wrap(. ~ Story, scales = 'free_x') +
geom_line(alpha = 0.5)+
geom_point(alpha = 0.6)+
geom_smooth(method = "lm", formula = y ~ poly(x, 2), se = FALSE, #colour = "grey60",
linetype = 1, lwd = 1)+
geom_smooth(method = "lm", linetype = 2, lwd = 1, se = FALSE)+
theme(legend.position = "none")+
to which I need to add some text information, for example one unique Mean_deriv
value and one unique Slope
value; ideally this value should be located topleft; also the values should be preceded by the strings "Mean derivative = " and "Slope = "; however adding a geom_text
like this prints all (duplicated) Mean_deriv
values:
geom_text(aes(label = Mean_deriv[1]))
How can I add exactly one Mean_deriv
and one Slope
value per facet?
Data:
df <- structure(list(Story = c("Beer for plants ", "Beer for plants ",
"Beer for plants ", "Drawing in the dark ", "Drawing in the dark ",
"Drawing in the dark ", "Drawing in the dark ", "Drawing in the dark ",
"Drawing in the dark ", "Drawing in the dark ", "Drawing in the dark ",
"Drawing in the dark ", "Drawing in the dark ", "Easy work ",
"Easy work ", "Easy work ", "Easy work ", "Easy work ", "Easy work ",
"Easy work ", "Easy work ", "Easy work ", "Guessing game ", "Guessing game ",
"Guessing game ", "Guessing game ", "Guessing game ", "Hiking in Serbia ",
"Hiking in Serbia ", "Hiking in Serbia ", "Hiking in Serbia ",
"Hiking in Serbia ", "Hiking in Serbia ", "Hiking in Serbia ",
"Hiking in Serbia ", "Letters in the toilet ", "Letters in the toilet ",
"Letters in the toilet ", "Letters in the toilet ", "Letters in the toilet ",
"Letters in the toilet ", "Letters in the toilet ", "Letters in the toilet ",
"Letters in the toilet ", "Letters in the toilet ", "Missing it ",
"Missing it ", "Missing it ", "Missing it ", "Missing it ", "Missing it ",
"Missing it ", "Missing it ", "Missing it ", "Missing it ", "Narrow streets ",
"Narrow streets ", "Narrow streets ", "Narrow streets ", "Narrow streets ",
"Narrow streets ", "Narrow streets ", "Narrow streets ", "Playing with pirates ",
"Playing with pirates ", "Playing with pirates ", "Playing with pirates ",
"Playing with pirates ", "Playing with pirates ", "Pocket lady ",
"Pocket lady ", "Pocket lady ", "Pocket lady ", "Pocket lady ",
"Pocket lady ", "Pocket lady ", "Pocket lady ", "Pocket lady ",
"Pocket lady ", "Quiet carriage ", "Quiet carriage ", "Quiet carriage ",
"Quiet carriage ", "Quiet carriage ", "Quiet carriage ", "Quiet carriage ",
"Quiet carriage ", "Quiet carriage ", "Quiet carriage ", "Sad story ",
"Sad story ", "Sad story ", "Sad story ", "Sad story ", "Sad story ",
"Sad story ", "Sad story ", "Sad story ", "Sad story ", "Stupid mask ",
"Stupid mask ", "Stupid mask ", "Stupid mask ", "Stupid mask ",
"Stupid mask ", "Stupid mask ", "Stupid mask ", "Toilet woman ",
"Toilet woman ", "Toilet woman ", "Toilet woman ", "Toilet woman ",
"Toilet woman ", "Toilet woman ", "Toilet woman ", "Toilet woman ",
"Toilet woman "), IND_all = c(0, 0.142857142857143, 0.214285714285714,
0.0714285714285714, 0.0714285714285714, 0.0714285714285714, 0,
0.0714285714285714, 0.0714285714285714, 0.142857142857143, 0.142857142857143,
0.142857142857143, 0.0714285714285714, 0.214285714285714, 0.142857142857143,
0.0714285714285714, 0.142857142857143, 0.142857142857143, 0.142857142857143,
0.214285714285714, 0.142857142857143, 0.142857142857143, 0.142857142857143,
0.0714285714285714, 0.0714285714285714, 0.642857142857143, 0.214285714285714,
0.214285714285714, 0.285714285714286, 0.142857142857143, 0, 0,
0.0714285714285714, 0.285714285714286, 0.214285714285714, 0.0714285714285714,
0.142857142857143, 0.166666666666667, 0.214285714285714, 0.142857142857143,
0.142857142857143, 0.142857142857143, 0.142857142857143, 0, 0.214285714285714,
0.428571428571429, 0, 0, 0.142857142857143, 0.214285714285714,
0, 0.285714285714286, 0.166666666666667, 0.142857142857143, 0.0714285714285714,
0.285714285714286, 0.0714285714285714, 0.142857142857143, 0.214285714285714,
0.0714285714285714, 0.357142857142857, 0.214285714285714, 0.142857142857143,
0.285714285714286, 0.142857142857143, 0.214285714285714, 0.0833333333333333,
0.142857142857143, 0.142857142857143, 0.0714285714285714, 0.0714285714285714,
0.142857142857143, 0.142857142857143, 0.214285714285714, 0.214285714285714,
0, 0.285714285714286, 0.214285714285714, 0.214285714285714, 0.214285714285714,
0.0714285714285714, 0, 0, 0.0714285714285714, 0, 0.285714285714286,
0.142857142857143, 0.142857142857143, 0.285714285714286, 0.0714285714285714,
0.142857142857143, 0.142857142857143, 0.0714285714285714, 0.214285714285714,
0, 0.0714285714285714, 0.0714285714285714, 0.0714285714285714,
0.214285714285714, 0.142857142857143, 0.0714285714285714, 0.142857142857143,
0.0714285714285714, 0, 0.0714285714285714, 0.285714285714286,
0, 0.142857142857143, 0, 0.214285714285714, 0.0714285714285714,
0.0714285714285714, 0.142857142857143, 0, 0.285714285714286,
0.142857142857143, 0), x = c(1L, 2L, 3L, 1L, 2L, 3L, 4L, 5L,
6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L,
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L,
10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L,
6L, 7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L), Mean_deriv = c(0.107142857142857, 0.107142857142857,
0.107142857142857, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0.00892857142857143,
-0.00892857142857143, -0.00892857142857143, -0.00892857142857143,
-0.00892857142857143, -0.00892857142857143, -0.00892857142857143,
-0.00892857142857143, -0.00892857142857143, 0.0178571428571429,
0.0178571428571429, 0.0178571428571429, 0.0178571428571429, 0.0178571428571429,
-7.93016446160826e-18, -7.93016446160826e-18, -7.93016446160826e-18,
-7.93016446160826e-18, -7.93016446160826e-18, -7.93016446160826e-18,
-7.93016446160826e-18, -7.93016446160826e-18, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, -0.0210084033613445, -0.0210084033613445, -0.0210084033613445,
-0.0210084033613445, -0.0210084033613445, -0.0210084033613445,
-0.0210084033613445, -0.0210084033613445, -0.0210084033613445,
-0.0210084033613445, -0.0204081632653061, -0.0204081632653061,
-0.0204081632653061, -0.0204081632653061, -0.0204081632653061,
-0.0204081632653061, -0.0204081632653061, -0.0204081632653061,
-0.0285714285714286, -0.0285714285714286, -0.0285714285714286,
-0.0285714285714286, -0.0285714285714286, -0.0285714285714286,
0.00216450216450217, 0.00216450216450217, 0.00216450216450217,
0.00216450216450217, 0.00216450216450217, 0.00216450216450217,
0.00216450216450217, 0.00216450216450217, 0.00216450216450217,
0.00216450216450217, -0.00324675324675324, -0.00324675324675324,
-0.00324675324675324, -0.00324675324675324, -0.00324675324675324,
-0.00324675324675324, -0.00324675324675324, -0.00324675324675324,
-0.00324675324675324, -0.00324675324675324, 0.00446428571428571,
0.00446428571428571, 0.00446428571428571, 0.00446428571428571,
0.00446428571428571, 0.00446428571428571, 0.00446428571428571,
0.00446428571428571, 0.00446428571428571, 0.00446428571428571,
-0.0204081632653061, -0.0204081632653061, -0.0204081632653061,
-0.0204081632653061, -0.0204081632653061, -0.0204081632653061,
-0.0204081632653061, -0.0204081632653061, 0.0119047619047619,
0.0119047619047619, 0.0119047619047619, 0.0119047619047619, 0.0119047619047619,
0.0119047619047619, 0.0119047619047619, 0.0119047619047619, 0.0119047619047619,
0.0119047619047619), Slope = c(x = 0.107142857142857, x = 0.107142857142857,
x = 0.107142857142857, x = 0.00779220779220779, x = 0.00779220779220779,
x = 0.00779220779220779, x = 0.00779220779220779, x = 0.00779220779220779,
x = 0.00779220779220779, x = 0.00779220779220779, x = 0.00779220779220779,
x = 0.00779220779220779, x = 0.00779220779220779, x = -2.95585848285666e-18,
x = -2.95585848285666e-18, x = -2.95585848285666e-18, x = -2.95585848285666e-18,
x = -2.95585848285666e-18, x = -2.95585848285666e-18, x = -2.95585848285666e-18,
x = -2.95585848285666e-18, x = -2.95585848285666e-18, x = 0.0714285714285714,
x = 0.0714285714285714, x = 0.0714285714285714, x = 0.0714285714285714,
x = 0.0714285714285714, x = -0.00255102040816327, x = -0.00255102040816327,
x = -0.00255102040816327, x = -0.00255102040816327, x = -0.00255102040816327,
x = -0.00255102040816327, x = -0.00255102040816327, x = -0.00255102040816327,
x = 0.00018896447467876, x = 0.00018896447467876, x = 0.00018896447467876,
x = 0.00018896447467876, x = 0.00018896447467876, x = 0.00018896447467876,
x = 0.00018896447467876, x = 0.00018896447467876, x = 0.00018896447467876,
x = 0.00018896447467876, x = -0.00464396284829722, x = -0.00464396284829722,
x = -0.00464396284829722, x = -0.00464396284829722, x = -0.00464396284829722,
x = -0.00464396284829722, x = -0.00464396284829722, x = -0.00464396284829722,
x = -0.00464396284829722, x = -0.00464396284829722, x = 0.00255102040816328,
x = 0.00255102040816328, x = 0.00255102040816328, x = 0.00255102040816328,
x = 0.00255102040816328, x = 0.00255102040816328, x = 0.00255102040816328,
x = 0.00255102040816328, x = -0.0241496598639456, x = -0.0241496598639456,
x = -0.0241496598639456, x = -0.0241496598639456, x = -0.0241496598639456,
x = -0.0241496598639456, x = -0.00128778784240969, x = -0.00128778784240969,
x = -0.00128778784240969, x = -0.00128778784240969, x = -0.00128778784240969,
x = -0.00128778784240969, x = -0.00128778784240969, x = -0.00128778784240969,
x = -0.00128778784240969, x = -0.00128778784240969, x = 0.00430547713156409,
x = 0.00430547713156409, x = 0.00430547713156409, x = 0.00430547713156409,
x = 0.00430547713156409, x = 0.00430547713156409, x = 0.00430547713156409,
x = 0.00430547713156409, x = 0.00430547713156409, x = 0.00430547713156409,
x = 0.00175070028011204, x = 0.00175070028011204, x = 0.00175070028011204,
x = 0.00175070028011204, x = 0.00175070028011204, x = 0.00175070028011204,
x = 0.00175070028011204, x = 0.00175070028011204, x = 0.00175070028011204,
x = 0.00175070028011204, x = -0.00255102040816326, x = -0.00255102040816326,
x = -0.00255102040816326, x = -0.00255102040816326, x = -0.00255102040816326,
x = -0.00255102040816326, x = -0.00255102040816326, x = -0.00255102040816326,
x = 0.00928571428571428, x = 0.00928571428571428, x = 0.00928571428571428,
x = 0.00928571428571428, x = 0.00928571428571428, x = 0.00928571428571428,
x = 0.00928571428571428, x = 0.00928571428571428, x = 0.00928571428571428,
x = 0.00928571428571428)), row.names = c(NA, -117L), class = c("tbl_df",
"tbl", "data.frame"))