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Louis Lacoste 2022-12-05 17:46:15 +01:00
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# ouverture du dataset
forest <- read.csv("forest.txt", sep="", stringsAsFactors=TRUE)
forest$Observation <- as.factor(forest$Observation) # observation comme facteur
summary(forest)
### Q1
forest_P <- forest[,1:10]
library(ade4)
forest_pca <- dudi.pca(forest_P)
# pourcentage expliqué par chaque variable
forest_pca$eig/sum(forest_pca$eig)
# premier 57.27 % et le deuxième 15.83%
### Q2
s.corcircle(forest_pca$co)
### Q3
boxplot(forest$FWI ~ forest$Observation,
xlab = "Présence de feu",
ylab = "FWI",
names = c("pas de feu", "feu"),
col = c("blue","orange" ),
main = "FWI en fonction de la présence de feu")
hist(forest$FWI[forest$Observation=="0"])
hist(forest$FWI[forest$Observation=="1"])
var.test(forest$FWI ~ forest$Observation)
t.test(forest$FWI ~ forest$Observation)
wilcox.test(forest$FWI ~ forest$Observation)
### Q4
reg <- lm(forest$FWI ~ forest$Temperature + forest$Ws)
summary(reg)
# les deux sont significatifs
# une augmentation d'un degré augmente le FWI de 1.28
# une augmentation du vent de 1 km/h augmente le FWI de 0.55
plot(reg)
# cond application ok mais bof
### Q5
summary(lm(forest$FWI ~ forest$Temperature * forest$Ws))
# température et vent plus significatifs
# mais forte intéraction entre les deux
cor.test(forest$Temperature , forest$Ws)
cor(forest$Ws , forest$Temperature)
# forte corrélation
### Q6
modèle <- glm(forest$FWI ~ forest$FFMC + forest$DMC + forest$DC + forest$ISI + forest$BUI)
exp(modèle$coefficients)
summary(modèle)
mod <- lm(forest$FWI ~ forest$FFMC + forest$ISI + forest$BUI)
summary(mod)
anova(modèle, mod)
### Q7
library(MASS)
mon_image<-kde2d(x=forest$FFMC + forest$ISI + forest$BUI,y=forest$FWI,n=100)
image(mon_image,
legend = T,
las=1)
plot(mod)
# y a des outliers
### Q8
mode <- glm(forest$Observation ~ forest$Temperature + forest$RH + forest$Ws + forest$Region, family = "binomial")
summary(mode)
# humidité et température effet significatif
exp(mode$coefficients)
# température qui multiplie l'OR = risque de 1.38 donc qd température augmente d'un degré le risque augmente de 38 %
# humidité augmente d'une unité diminutio du risque d'envirion 3% (1-0.97)
### Q9
model <- glm(forest$Observation ~ forest$Region, family = "binomial")
summary(model)
# région B plus que feu que région A significatif
# être région B augmente risque de feu de 94%
exp(model$coefficients)
#OR départ 1
1.94/(1+1.94)
# nv proba = 0.66 => 66 %
### Q11
chisq.test(table(forest$Observation, forest$Region))
# c'est bien significatif
table(forest$Observation, forest$Region)
# plus de feu en B que en A

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"Temperature" "RH" "Ws" "Rain" "FFMC" "DMC" "DC" "ISI" "BUI" "FWI" "Observation" "Region"
29 57 18 0 65.7 3.4 7.6 1.3 3.4 0.5 0 "A"
29 61 13 1.3 64.4 4.1 7.6 1 3.9 0.4 0 "A"
26 82 22 13.1 47.1 2.5 7.1 0.3 2.7 0.1 0 "A"
25 89 13 2.5 28.6 1.3 6.9 0 1.7 0 0 "A"
27 77 16 0 64.8 3 14.2 1.2 3.9 0.5 0 "A"
31 67 14 0 82.6 5.8 22.2 3.1 7 2.5 1 "A"
33 54 13 0 88.2 9.9 30.5 6.4 10.9 7.2 1 "A"
30 73 15 0 86.6 12.1 38.3 5.6 13.5 7.1 1 "A"
25 88 13 0.2 52.9 7.9 38.8 0.4 10.5 0.3 0 "A"
28 79 12 0 73.2 9.5 46.3 1.3 12.6 0.9 0 "A"
31 65 14 0 84.5 12.5 54.3 4 15.8 5.6 1 "A"
26 81 19 0 84 13.8 61.4 4.8 17.7 7.1 1 "A"
27 84 21 1.2 50 6.7 17 0.5 6.7 0.2 0 "A"
30 78 20 0.5 59 4.6 7.8 1 4.4 0.4 0 "A"
28 80 17 3.1 49.4 3 7.4 0.4 3 0.1 0 "A"
29 89 13 0.7 36.1 1.7 7.6 0 2.2 0 0 "A"
30 89 16 0.6 37.3 1.1 7.8 0 1.6 0 0 "A"
31 78 14 0.3 56.9 1.9 8 0.7 2.4 0.2 0 "A"
31 55 16 0.1 79.9 4.5 16 2.5 5.3 1.4 0 "A"
30 80 16 0.4 59.8 3.4 27.1 0.9 5.1 0.4 0 "A"
30 78 14 0 81 6.3 31.6 2.6 8.4 2.2 1 "A"
31 67 17 0.1 79.1 7 39.5 2.4 9.7 2.3 0 "A"
32 62 18 0.1 81.4 8.2 47.7 3.3 11.5 3.8 1 "A"
32 66 17 0 85.9 11.2 55.8 5.6 14.9 7.5 1 "A"
31 64 15 0 86.7 14.2 63.8 5.7 18.3 8.4 1 "A"
31 64 18 0 86.8 17.8 71.8 6.7 21.6 10.6 1 "A"
34 53 18 0 89 21.6 80.3 9.2 25.8 15 1 "A"
32 55 14 0 89.1 25.5 88.5 7.6 29.7 13.9 1 "A"
32 47 13 0.3 79.9 18.4 84.4 2.2 23.8 3.9 0 "A"
33 50 14 0 88.7 22.9 92.8 7.2 28.3 12.9 1 "A"
29 68 19 1 59.9 2.5 8.6 1.1 2.9 0.4 0 "A"
27 75 19 1.2 55.7 2.4 8.3 0.8 2.8 0.3 0 "A"
32 76 20 0.7 63.1 2.6 9.2 1.3 3 0.5 0 "A"
33 78 17 0 80.1 4.6 18.5 2.7 5.7 1.7 0 "A"
33 66 14 0 85.9 7.6 27.9 4.8 9.1 4.9 1 "A"
32 63 14 0 87 10.9 37 5.6 12.5 6.8 1 "A"
35 64 18 0.2 80 9.7 40.4 2.8 12.1 3.2 0 "A"
33 68 19 0 85.6 12.5 49.8 6 15.4 8 1 "A"
32 68 14 1.4 66.6 7.7 9.2 1.1 7.4 0.6 0 "A"
33 69 13 0.7 66.6 6 9.3 1.1 5.8 0.5 0 "A"
33 76 14 0 81.1 8.1 18.7 2.6 8.1 2.2 0 "A"
31 75 13 0.1 75.1 7.9 27.7 1.5 9.2 0.9 0 "A"
34 81 15 0 81.8 9.7 37.2 3 11.7 3.4 0 "A"
34 61 13 0.6 73.9 7.8 22.9 1.4 8.4 0.8 0 "A"
30 80 19 0.4 60.7 5.2 17 1.1 5.9 0.5 0 "A"
28 76 21 0 72.6 7 25.5 0.7 8.3 0.4 0 "A"
29 70 14 0 82.8 9.4 34.1 3.2 11.1 3.6 1 "A"
31 68 14 0 85.4 12.1 43.1 4.6 14.2 6 1 "A"
35 59 17 0 88.1 12 52.8 7.7 18.2 10.9 1 "A"
33 65 15 0.1 81.4 12.3 62.1 2.8 16.5 4 1 "A"
33 70 17 0 85.4 18.5 71.5 5.2 22.4 8.8 1 "A"
28 79 18 0.1 73.4 16.4 79.9 1.8 21.7 2.8 0 "A"
27 66 22 0.4 68.2 10.5 71.3 1.8 15.4 2.1 0 "A"
28 78 16 0.1 70 9.6 79.7 1.4 14.7 1.3 0 "A"
31 65 18 0 84.3 12.5 88.7 4.8 18.5 7.3 1 "A"
36 53 19 0 89.2 17.1 98.6 10 23.9 15.3 1 "A"
36 48 13 0 90.3 22.2 108.5 8.7 29.4 15.3 1 "A"
33 76 15 0 86.5 24.4 117.8 5.6 32.1 11.3 1 "A"
32 73 15 0 86.6 26.7 127 5.6 35 11.9 1 "A"
31 79 15 0 85.4 28.5 136 4.7 37.4 10.7 1 "A"
35 64 17 0 87.2 31.9 145.7 6.8 41.2 15.7 1 "A"
36 45 14 0 78.8 4.8 10.2 2 4.7 0.9 0 "A"
35 55 12 0.4 78 5.8 10 1.7 5.5 0.8 0 "A"
35 63 14 0.3 76.6 5.7 10 1.7 5.5 0.8 0 "A"
34 69 13 0 85 8.2 19.8 4 8.2 3.9 1 "A"
34 65 13 0 86.8 11.1 29.7 5.2 11.5 6.1 1 "A"
32 75 14 0 86.4 13 39.1 5.2 14.2 6.8 1 "A"
32 69 16 0 86.5 15.5 48.6 5.5 17.2 8 1 "A"
32 60 18 0.3 77.1 11.3 47 2.2 14.1 2.6 0 "A"
35 59 17 0 87.4 14.8 57 6.9 17.9 9.9 1 "A"
35 55 14 0 88.9 18.6 67 7.4 21.9 11.6 1 "A"
35 63 13 0 88.9 21.7 77 7.1 25.5 12.1 1 "A"
35 51 13 0.3 81.3 15.6 75.1 2.5 20.7 4.2 0 "A"
35 63 15 0 87 19 85.1 5.9 24.4 10.2 1 "A"
33 66 14 0 87 21.7 94.7 5.7 27.2 10.6 1 "A"
36 55 13 0.3 82.4 15.6 92.5 3.7 22 6.3 1 "A"
36 61 18 0.3 80.2 11.7 90.4 2.8 17.6 4.2 1 "A"
37 52 18 0 89.3 16 100.7 9.7 22.9 14.6 1 "A"
36 54 18 0 89.4 20 110.9 9.7 27.5 16.1 1 "A"
35 62 19 0 89.4 23.2 120.9 9.7 31.3 17.2 1 "A"
35 68 19 0 88.3 25.9 130.6 8.8 34.7 16.8 1 "A"
36 58 19 0 88.6 29.6 141.1 9.2 38.8 18.4 1 "A"
36 55 18 0 89.1 33.5 151.3 9.9 43.1 20.4 1 "A"
36 53 16 0 89.5 37.6 161.5 10.4 47.5 22.3 1 "A"
34 64 14 0 88.9 40.5 171.3 9 50.9 20.9 1 "A"
35 60 15 0 88.9 43.9 181.3 8.2 54.7 20.3 1 "A"
31 78 18 0 85.8 45.6 190.6 4.7 57.1 13.7 1 "A"
33 82 21 0 84.9 47 200.2 4.4 59.3 13.2 1 "A"
34 64 16 0 89.4 50.2 210.4 7.3 62.9 19.9 1 "A"
35 48 18 0 90.1 54.2 220.4 12.5 67.4 30.2 1 "A"
35 70 17 0.8 72.7 25.2 180.4 1.7 37.4 4.2 0 "A"
28 80 21 16.8 52.5 8.7 8.7 0.6 8.3 0.3 0 "A"
25 76 17 7.2 46 1.3 7.5 0.2 1.8 0.1 0 "A"
22 86 15 10.1 30.5 0.7 7 0 1.1 0 0 "A"
25 78 15 3.8 42.6 1.2 7.5 0.1 1.7 0 0 "A"
29 73 17 0.1 68.4 1.9 15.7 1.4 2.9 0.5 0 "A"
29 75 16 0 80.8 3.4 24 2.8 5.1 1.7 1 "A"
29 74 19 0.1 75.8 3.6 32.2 2.1 5.6 0.9 0 "A"
31 71 17 0.3 69.6 3.2 30.1 1.5 5.1 0.6 0 "A"
30 73 17 0.9 62 2.6 8.4 1.1 3 0.4 0 "A"
30 77 15 1 56.1 2.1 8.4 0.7 2.6 0.2 0 "A"
33 73 12 1.8 59.9 2.2 8.9 0.7 2.7 0.3 0 "A"
30 77 21 1.8 58.5 1.9 8.4 1.1 2.4 0.3 0 "A"
29 88 13 0 71 2.6 16.6 1.2 3.7 0.5 0 "A"
25 86 21 4.6 40.9 1.3 7.5 0.1 1.8 0 0 "A"
22 76 26 8.3 47.4 1.1 7 0.4 1.6 0.1 0 "A"
24 82 15 0.4 44.9 0.9 7.3 0.2 1.4 0 0 "A"
30 65 14 0 78.1 3.2 15.7 1.9 4.2 0.8 0 "A"
31 52 14 0 87.7 6.4 24.3 6.2 7.7 5.9 1 "A"
32 49 11 0 89.4 9.8 33.1 6.8 11.3 7.7 1 "A"
29 57 14 0 89.3 12.5 41.3 7.8 14.2 9.7 1 "A"
28 84 18 0 83.8 13.5 49.3 4.5 16 6.3 1 "A"
31 55 11 0 87.8 16.5 57.9 5.4 19.2 8.3 1 "A"
31 50 19 0.6 77.8 10.6 41.4 2.4 12.9 2.8 0 "A"
32 54 11 0.5 73.7 7.9 30.4 1.2 9.6 0.7 0 "A"
29 65 19 0.6 68.3 5.5 15.2 1.5 5.8 0.7 0 "A"
26 81 21 5.8 48.6 3 7.7 0.4 3 0.1 0 "A"
31 54 11 0 82 6 16.3 2.5 6.2 1.7 0 "A"
31 66 11 0 85.7 8.3 24.9 4 9 4.1 1 "A"
32 47 14 0.7 77.5 7.1 8.8 1.8 6.8 0.9 0 "A"
26 80 16 1.8 47.4 2.9 7.7 0.3 3 0.1 0 "A"
25 78 14 1.4 45 1.9 7.5 0.2 2.4 0.1 0 "A"
32 71 12 0.7 57.1 2.5 8.2 0.6 2.8 0.2 0 "B"
30 73 13 4 55.7 2.7 7.8 0.6 2.9 0.2 0 "B"
29 80 14 2 48.7 2.2 7.6 0.3 2.6 0.1 0 "B"
30 64 14 0 79.4 5.2 15.4 2.2 5.6 1 0 "B"
32 60 14 0.2 77.1 6 17.6 1.8 6.5 0.9 0 "B"
35 54 11 0.1 83.7 8.4 26.3 3.1 9.3 3.1 1 "B"
35 44 17 0.2 85.6 9.9 28.9 5.4 10.7 6 1 "B"
28 51 17 1.3 71.4 7.7 7.4 1.5 7.3 0.8 0 "B"
27 59 18 0.1 78.1 8.5 14.7 2.4 8.3 1.9 0 "B"
30 41 15 0 89.4 13.3 22.5 8.4 13.1 10 1 "B"
31 42 21 0 90.6 18.2 30.5 13.4 18 16.7 1 "B"
27 58 17 0 88.9 21.3 37.8 8.7 21.2 12.9 1 "B"
30 52 15 2 72.3 11.4 7.8 1.4 10.9 0.9 0 "B"
27 79 16 0.7 53.4 6.4 7.3 0.5 6.1 0.3 0 "B"
28 90 15 0 66.8 7.2 14.7 1.2 7.1 0.6 0 "B"
29 87 15 0.4 47.4 4.2 8 0.2 4.1 0.1 0 "B"
31 69 17 4.7 62.2 3.9 8 1.1 3.8 0.4 0 "B"
33 62 10 8.7 65.5 4.6 8.3 0.9 4.4 0.4 0 "B"
32 67 14 4.5 64.6 4.4 8.2 1 4.2 0.4 0 "B"
31 72 14 0.2 60.2 3.8 8 0.8 3.7 0.3 0 "B"
32 55 14 0 86.2 8.3 18.4 5 8.2 4.9 1 "B"
33 46 14 1.1 78.3 8.1 8.3 1.9 7.7 1.2 0 "B"
33 59 16 0.8 74.2 7 8.3 1.6 6.7 0.8 0 "B"
35 68 16 0 85.3 10 17 4.9 9.9 5.3 1 "B"
34 70 16 0 86 12.8 25.6 5.4 12.7 6.7 1 "B"
36 62 16 0 87.8 16.5 34.5 7 16.4 9.5 1 "B"
36 55 15 0 89.1 20.9 43.3 8 20.8 12 1 "B"
37 37 13 0 92.5 27.2 52.4 11.7 27.1 18.4 1 "B"
37 36 13 0.6 86.2 17.9 36.7 4.8 17.8 7.2 1 "B"
34 42 15 1.7 79.7 12 8.5 2.2 11.5 2.2 0 "B"
28 58 18 2.2 63.7 3.2 8.5 1.2 3.3 0.5 0 "B"
33 48 16 0 87.6 7.9 17.8 6.8 7.8 6.4 1 "B"
34 56 17 0.1 84.7 9.7 27.3 4.7 10.3 5.2 1 "B"
34 58 18 0 88 13.6 36.8 8 14.1 9.9 1 "B"
34 45 18 0 90.5 18.7 46.4 11.3 18.7 15 1 "B"
35 42 15 0.3 84.7 15.5 45.1 4.3 16.7 6.3 1 "B"
38 43 13 0.5 85 13 35.4 4.1 13.7 5.2 1 "B"
35 47 18 6 80.8 9.8 9.7 3.1 9.4 3 1 "B"
36 43 15 1.9 82.3 9.4 9.9 3.2 9 3.1 1 "B"
34 51 16 3.8 77.5 8 9.5 2 7.7 1.3 0 "B"
34 56 15 2.9 74.8 7.1 9.5 1.6 6.8 0.8 0 "B"
36 44 13 0 90.1 12.6 19.4 8.3 12.5 9.6 1 "B"
39 45 13 0.6 85.2 11.3 10.4 4.2 10.9 4.7 1 "B"
34 45 17 0 90.5 18 24.1 10.9 17.7 14.1 1 "B"
31 83 17 0 84.5 19.4 33.1 4.7 19.2 7.3 1 "B"
32 81 17 0 84.6 21.1 42.3 4.7 20.9 7.7 1 "B"
33 68 15 0 86.1 23.9 51.6 5.2 23.9 9.1 1 "B"
34 58 16 0 88.1 27.8 61.1 7.3 27.7 13 1 "B"
36 50 16 0 89.9 32.7 71 9.5 32.6 17.3 1 "B"
36 29 18 0 93.9 39.6 80.6 18.5 39.5 30 1 "B"
32 48 18 0 91.5 44.2 90.1 13.2 44 25.4 1 "B"
31 71 17 0 87.3 46.6 99 6.9 46.5 16.3 1 "B"
33 63 17 1.1 72.8 20.9 56.6 1.6 21.7 2.5 0 "B"
39 64 9 1.2 73.8 11.7 15.9 1.1 11.4 0.7 0 "B"
35 58 10 0.2 78.3 10.8 19.7 1.6 10.7 1 0 "B"
29 87 18 0 80 11.8 28.3 2.8 11.8 3.2 0 "B"
33 57 16 0 87.5 15.7 37.6 6.7 15.7 9 1 "B"
34 59 16 0 88.1 19.5 47.2 7.4 19.5 10.9 1 "B"
36 56 16 0 88.9 23.8 57.1 8.2 23.8 13.2 1 "B"
37 55 15 0 89.3 28.3 67.2 8.3 28.3 14.5 1 "B"
38 52 14 0 78.3 4.4 10.5 2 4.4 0.8 0 "B"
40 34 14 0 93.3 10.8 21.4 13.8 10.6 13.5 1 "B"
39 33 17 0 93.7 17.1 32.1 17.2 16.9 19.5 1 "B"
38 35 15 0 93.8 23 42.7 15.7 22.9 20.9 1 "B"
34 42 17 0.1 88.3 23.6 52.5 19 23.5 12.6 1 "B"
30 54 14 3.1 70.5 11 9.1 1.3 10.5 0.8 0 "B"
34 63 13 2.9 69.7 7.2 9.8 1.2 6.9 0.6 0 "B"
37 56 11 0 87.4 11.2 20.2 5.2 11 5.9 1 "B"
39 43 12 0 91.7 16.5 30.9 9.6 16.4 12.7 1 "B"
39 39 15 0.2 89.3 15.8 35.4 8.2 15.8 10.7 1 "B"
40 31 15 0 94.2 22.5 46.3 16.6 22.4 21.6 1 "B"
39 21 17 0.4 93 18.4 41.5 15.5 18.4 18.8 1 "B"
35 34 16 0.2 88.3 16.9 45.1 7.5 17.5 10.5 1 "B"
37 40 13 0 91.9 22.3 55.5 10.8 22.3 15.7 1 "B"
35 46 13 0.3 83.9 16.9 54.2 3.5 19 5.5 1 "B"
40 41 10 0.1 92 22.6 65.1 9.5 24.2 14.8 1 "B"
42 24 9 0 96 30.3 76.4 15.7 30.4 24 1 "B"
37 37 14 0 94.3 35.9 86.8 16 35.9 26.3 1 "B"
35 66 15 0.1 82.7 32.7 96.8 3.3 35.5 7.7 1 "B"
36 81 15 0 83.7 34.4 107 3.8 38.1 9 1 "B"
36 71 15 0 86 36.9 117.1 5.1 41.3 12.2 1 "B"
37 53 14 0 89.5 41.1 127.5 8 45.5 18.1 1 "B"
36 43 16 0 91.2 46.1 137.7 11.5 50.2 24.5 1 "B"
35 38 15 0 92.1 51.3 147.7 12.2 54.9 26.9 1 "B"
34 40 18 0 92.1 56.3 157.5 14.3 59.5 31.1 1 "B"
33 37 16 0 92.2 61.3 167.2 13.1 64 30.3 1 "B"
36 54 14 0 91 65.9 177.3 10 68 26.1 1 "B"
35 56 14 0.4 79.2 37 166 2.1 30.6 6.1 0 "B"
35 53 17 0.5 80.2 20.7 149.2 2.7 30.6 5.9 1 "B"
34 49 15 0 89.2 24.8 159.1 8.1 35.7 16 1 "B"
30 59 19 0 89.1 27.8 168.2 9.8 39.3 19.4 1 "B"
29 86 16 0 37.9 0.9 8.2 0.1 1.4 0 0 "B"
28 67 19 0 75.4 2.9 16.3 2 4 0.8 0 "B"
28 75 16 0 82.2 4.4 24.3 3.3 6 2.5 1 "B"
30 66 15 0.2 73.5 4.1 26.6 1.5 6 0.7 0 "B"
30 58 12 4.1 66.1 4 8.4 1 3.9 0.4 0 "B"
34 71 14 6.5 64.5 3.3 9.1 1 3.5 0.4 0 "B"
31 62 15 0 83.3 5.8 17.7 3.8 6.4 3.2 1 "B"
30 88 14 0 82.5 6.6 26.1 3 8.1 2.7 1 "B"
30 80 15 0 83.1 7.9 34.5 3.5 10 3.7 1 "B"
29 74 15 1.1 59.5 4.7 8.2 0.8 4.6 0.3 0 "B"
30 73 14 0 79.2 6.5 16.6 2.1 6.6 1.2 0 "B"
31 72 14 0 84.2 8.3 25.2 3.8 9.1 3.9 1 "B"
29 49 19 0 88.6 11.5 33.4 9.1 12.4 10.3 1 "B"
28 81 15 0 84.6 12.6 41.5 4.3 14.3 5.7 1 "B"
32 51 13 0 88.7 16 50.2 6.9 17.8 9.8 1 "B"
33 26 13 0 93.9 21.2 59.2 14.2 22.4 19.3 1 "B"
34 44 12 0 92.5 25.2 63.3 11.2 26.2 17.5 1 "B"
36 33 13 0.1 90.6 25.8 77.8 9 28.2 15.4 1 "B"
29 41 8 0.1 83.9 24.9 86 2.7 28.9 5.6 1 "B"
34 58 13 0.2 79.5 18.7 88 2.1 24.4 3.8 0 "B"
35 34 17 0 92.2 23.6 97.3 13.8 29.4 21.6 1 "B"
33 64 13 0 88.9 26.1 106.3 7.1 32.4 13.7 1 "B"
35 56 14 0 89 29.4 115.6 7.5 36 15.2 1 "B"
26 49 6 2 61.3 11.9 28.1 0.6 11.9 0.4 0 "B"
28 70 15 0 79.9 13.8 36.1 2.4 14.1 3 0 "B"
30 65 14 0 85.4 16 44.5 4.5 16.9 6.5 1 "B"
28 87 15 4.4 41.1 6.5 8 0.1 6.2 0 0 "B"
27 87 29 0.5 45.9 3.5 7.9 0.4 3.4 0.2 0 "B"
24 54 18 0.1 79.7 4.3 15.2 1.7 5.1 0.7 0 "B"
24 64 15 0.2 67.3 3.8 16.5 1.2 4.8 0.5 0 "B"