EMERGENCIAS AMBIENTALES ASOCIADAS A SUSTANCIAS QUÍMICAS EN MÉXICO 2017
Equipo 8
30/11/2021
Datos
datos = read.csv(file = "C:\\Users\\karel\\OneDrive\\Documentos\\TAREAS KARELY 2\\CONSULTORIA\\8.- emergencias_ambientales (1).csv", header = T, sep = ",")
datos## ESTADO DERRAME EXPLOSION FUGA INCENDIO OTRO
## 1 AGUASCALIENTES 0 3 0 0 0
## 2 BAJA CALIFORNIA 2 0 1 5 0
## 3 BAJA CALIFORNIA SUR 1 0 0 0 0
## 4 CAMPECHE 0 0 0 0 0
## 5 CHIAPAS 0 2 3 0 0
## 6 CHIHUAHUA 3 1 4 0 0
## 7 CIUDAD DE MEXICO 3 9 26 9 1
## 8 COAHUILA 5 2 1 4 0
## 9 COLIMA 1 0 1 0 0
## 10 DURANGO 3 0 1 2 0
## 11 GUANAJUATO 3 3 5 8 0
## 12 GUERRERO 1 1 0 1 0
## 13 HIDALGO 10 4 1 7 1
## 14 JALISCO 7 5 2 12 0
## 15 MEXICO 4 9 8 13 1
## 16 MICHOACAN 8 1 0 6 0
## 17 MORELOS 1 3 1 1 0
## 18 NAYARIT 0 0 0 0 0
## 19 NUEVO LEON 5 0 1 10 0
## 20 OAXACA 2 2 2 2 0
## 21 PUEBLA 1 3 7 2 1
## 22 QUERETARO 1 3 2 2 1
## 23 QUINTANA ROO 2 1 0 0 0
## 24 SAN LUIS POTOSI 3 0 0 3 0
## 25 SINALOA 1 0 1 1 0
## 26 SONORA 2 3 1 1 0
## 27 TABASCO 1 0 4 3 0
## 28 TAMAULIPAS 7 2 3 4 0
## 29 TLAXCALA 0 2 0 0 0
## 30 VERACRUZ 25 4 4 7 0
## 31 YUCATAN 0 0 0 0 0
## 32 ZACATECAS 4 0 1 1 0Análisis
## DERRAME EXPLOSION FUGA INCENDIO OTRO
## 1 0 3 0 0 0
## 2 2 0 1 5 0
## 3 1 0 0 0 0
## 4 0 0 0 0 0
## 5 0 2 3 0 0
## 6 3 1 4 0 0
## 7 3 9 26 9 1
## 8 5 2 1 4 0
## 9 1 0 1 0 0
## 10 3 0 1 2 0
## 11 3 3 5 8 0
## 12 1 1 0 1 0
## 13 10 4 1 7 1
## 14 7 5 2 12 0
## 15 4 9 8 13 1
## 16 8 1 0 6 0
## 17 1 3 1 1 0
## 18 0 0 0 0 0
## 19 5 0 1 10 0
## 20 2 2 2 2 0
## 21 1 3 7 2 1
## 22 1 3 2 2 1
## 23 2 1 0 0 0
## 24 3 0 0 3 0
## 25 1 0 1 1 0
## 26 2 3 1 1 0
## 27 1 0 4 3 0
## 28 7 2 3 4 0
## 29 0 2 0 0 0
## 30 25 4 4 7 0
## 31 0 0 0 0 0
## 32 4 0 1 1 0## DERRAME EXPLOSION FUGA INCENDIO OTRO
## 1 -0.70371673 0.43657713 -0.5253543 -0.85301752 -0.4235542
## 2 -0.27883116 -0.83346544 -0.3152126 0.45931713 -0.4235542
## 3 -0.49127395 -0.83346544 -0.5253543 -0.85301752 -0.4235542
## 4 -0.70371673 -0.83346544 -0.5253543 -0.85301752 -0.4235542
## 5 -0.70371673 0.01322961 0.1050709 -0.85301752 -0.4235542
## 6 -0.06638837 -0.41011791 0.3152126 -0.85301752 -0.4235542
## 7 -0.06638837 2.97666227 4.9383305 1.50918484 2.2871926
## 8 0.35849720 0.01322961 -0.3152126 0.19685020 -0.4235542
## 9 -0.49127395 -0.83346544 -0.3152126 -0.85301752 -0.4235542
## 10 -0.06638837 -0.83346544 -0.3152126 -0.32808366 -0.4235542
## 11 -0.06638837 0.43657713 0.5253543 1.24671791 -0.4235542
## 12 -0.49127395 -0.41011791 -0.5253543 -0.59055059 -0.4235542
## 13 1.42071114 0.85992466 -0.3152126 0.98425098 2.2871926
## 14 0.78338278 1.28327218 -0.1050709 2.29658563 -0.4235542
## 15 0.14605442 2.97666227 1.1557795 2.55905256 2.2871926
## 16 0.99582557 -0.41011791 -0.5253543 0.72178406 -0.4235542
## 17 -0.49127395 0.43657713 -0.3152126 -0.59055059 -0.4235542
## 18 -0.70371673 -0.83346544 -0.5253543 -0.85301752 -0.4235542
## 19 0.35849720 -0.83346544 -0.3152126 1.77165177 -0.4235542
## 20 -0.27883116 0.01322961 -0.1050709 -0.32808366 -0.4235542
## 21 -0.49127395 0.43657713 0.9456378 -0.32808366 2.2871926
## 22 -0.49127395 0.43657713 -0.1050709 -0.32808366 2.2871926
## 23 -0.27883116 -0.41011791 -0.5253543 -0.85301752 -0.4235542
## 24 -0.06638837 -0.83346544 -0.5253543 -0.06561673 -0.4235542
## 25 -0.49127395 -0.83346544 -0.3152126 -0.59055059 -0.4235542
## 26 -0.27883116 0.43657713 -0.3152126 -0.59055059 -0.4235542
## 27 -0.49127395 -0.83346544 0.3152126 -0.06561673 -0.4235542
## 28 0.78338278 0.01322961 0.1050709 0.19685020 -0.4235542
## 29 -0.70371673 0.01322961 -0.5253543 -0.85301752 -0.4235542
## 30 4.60735296 0.85992466 0.3152126 0.98425098 -0.4235542
## 31 -0.70371673 -0.83346544 -0.5253543 -0.85301752 -0.4235542
## 32 0.14605442 -0.83346544 -0.3152126 -0.59055059 -0.4235542
## attr(,"scaled:center")
## DERRAME EXPLOSION FUGA INCENDIO OTRO
## 3.31250 1.96875 2.50000 3.25000 0.15625
## attr(,"scaled:scale")
## DERRAME EXPLOSION FUGA INCENDIO OTRO
## 4.707150 2.362126 4.758693 3.810004 0.368902## DERRAME EXPLOSION FUGA INCENDIO OTRO
## AGUASCALIENTES -0.70371673 0.43657713 -0.5253543 -0.85301752 -0.4235542
## BAJA CALIFORNIA -0.27883116 -0.83346544 -0.3152126 0.45931713 -0.4235542
## BAJA CALIFORNIA SUR -0.49127395 -0.83346544 -0.5253543 -0.85301752 -0.4235542
## CAMPECHE -0.70371673 -0.83346544 -0.5253543 -0.85301752 -0.4235542
## CHIAPAS -0.70371673 0.01322961 0.1050709 -0.85301752 -0.4235542
## CHIHUAHUA -0.06638837 -0.41011791 0.3152126 -0.85301752 -0.4235542
## CIUDAD DE MEXICO -0.06638837 2.97666227 4.9383305 1.50918484 2.2871926
## COAHUILA 0.35849720 0.01322961 -0.3152126 0.19685020 -0.4235542
## COLIMA -0.49127395 -0.83346544 -0.3152126 -0.85301752 -0.4235542
## DURANGO -0.06638837 -0.83346544 -0.3152126 -0.32808366 -0.4235542
## GUANAJUATO -0.06638837 0.43657713 0.5253543 1.24671791 -0.4235542
## GUERRERO -0.49127395 -0.41011791 -0.5253543 -0.59055059 -0.4235542
## HIDALGO 1.42071114 0.85992466 -0.3152126 0.98425098 2.2871926
## JALISCO 0.78338278 1.28327218 -0.1050709 2.29658563 -0.4235542
## MEXICO 0.14605442 2.97666227 1.1557795 2.55905256 2.2871926
## MICHOACAN 0.99582557 -0.41011791 -0.5253543 0.72178406 -0.4235542
## MORELOS -0.49127395 0.43657713 -0.3152126 -0.59055059 -0.4235542
## NAYARIT -0.70371673 -0.83346544 -0.5253543 -0.85301752 -0.4235542
## NUEVO LEON 0.35849720 -0.83346544 -0.3152126 1.77165177 -0.4235542
## OAXACA -0.27883116 0.01322961 -0.1050709 -0.32808366 -0.4235542
## PUEBLA -0.49127395 0.43657713 0.9456378 -0.32808366 2.2871926
## QUERETARO -0.49127395 0.43657713 -0.1050709 -0.32808366 2.2871926
## QUINTANA ROO -0.27883116 -0.41011791 -0.5253543 -0.85301752 -0.4235542
## SAN LUIS POTOSI -0.06638837 -0.83346544 -0.5253543 -0.06561673 -0.4235542
## SINALOA -0.49127395 -0.83346544 -0.3152126 -0.59055059 -0.4235542
## SONORA -0.27883116 0.43657713 -0.3152126 -0.59055059 -0.4235542
## TABASCO -0.49127395 -0.83346544 0.3152126 -0.06561673 -0.4235542
## TAMAULIPAS 0.78338278 0.01322961 0.1050709 0.19685020 -0.4235542
## TLAXCALA -0.70371673 0.01322961 -0.5253543 -0.85301752 -0.4235542
## VERACRUZ 4.60735296 0.85992466 0.3152126 0.98425098 -0.4235542
## YUCATAN -0.70371673 -0.83346544 -0.5253543 -0.85301752 -0.4235542
## ZACATECAS 0.14605442 -0.83346544 -0.3152126 -0.59055059 -0.4235542
## attr(,"scaled:center")
## DERRAME EXPLOSION FUGA INCENDIO OTRO
## 3.31250 1.96875 2.50000 3.25000 0.15625
## attr(,"scaled:scale")
## DERRAME EXPLOSION FUGA INCENDIO OTRO
## 4.707150 2.362126 4.758693 3.810004 0.368902#Metodo Ward.D por la distancia Manhattan
hcward = hclust(dist(a.tipif, method="manhattan"), method = "ward.D")
hcward##
## Call:
## hclust(d = dist(a.tipif, method = "manhattan"), method = "ward.D")
##
## Cluster method : ward.D
## Distance : manhattan
## Number of objects: 32plot(hcward, main = NULL,ylab = "Distancias entre los clusters",
xlab="Clusteres por entidad fedarativa", sub="", cex=.9)
rect.hclust(hcward, k=3, border = 3)
#Me dice que estado a que cluster pertenece
estadoclus = cutree(hcward, k=3)
estadoclus## AGUASCALIENTES BAJA CALIFORNIA BAJA CALIFORNIA SUR CAMPECHE
## 1 1 1 1
## CHIAPAS CHIHUAHUA CIUDAD DE MEXICO COAHUILA
## 1 1 2 3
## COLIMA DURANGO GUANAJUATO GUERRERO
## 1 1 3 1
## HIDALGO JALISCO MEXICO MICHOACAN
## 2 3 2 3
## MORELOS NAYARIT NUEVO LEON OAXACA
## 1 1 3 1
## PUEBLA QUERETARO QUINTANA ROO SAN LUIS POTOSI
## 2 2 1 1
## SINALOA SONORA TABASCO TAMAULIPAS
## 1 1 1 3
## TLAXCALA VERACRUZ YUCATAN ZACATECAS
## 1 3 1 1#visualizar los cluster
estadoclus<- cutree(hcward, k=3) #Solo mostramos cluster
grafico <- fviz_cluster(list(data=a.tipif, cluster=estadoclus))
grafico + labs(title = NULL)
#Juntamos la base original para observar que entidad a que cluster pertenece
datos = cbind(datos,estadoclus)
datos = datos[,-1]
datos## DERRAME EXPLOSION FUGA INCENDIO OTRO estadoclus
## AGUASCALIENTES 0 3 0 0 0 1
## BAJA CALIFORNIA 2 0 1 5 0 1
## BAJA CALIFORNIA SUR 1 0 0 0 0 1
## CAMPECHE 0 0 0 0 0 1
## CHIAPAS 0 2 3 0 0 1
## CHIHUAHUA 3 1 4 0 0 1
## CIUDAD DE MEXICO 3 9 26 9 1 2
## COAHUILA 5 2 1 4 0 3
## COLIMA 1 0 1 0 0 1
## DURANGO 3 0 1 2 0 1
## GUANAJUATO 3 3 5 8 0 3
## GUERRERO 1 1 0 1 0 1
## HIDALGO 10 4 1 7 1 2
## JALISCO 7 5 2 12 0 3
## MEXICO 4 9 8 13 1 2
## MICHOACAN 8 1 0 6 0 3
## MORELOS 1 3 1 1 0 1
## NAYARIT 0 0 0 0 0 1
## NUEVO LEON 5 0 1 10 0 3
## OAXACA 2 2 2 2 0 1
## PUEBLA 1 3 7 2 1 2
## QUERETARO 1 3 2 2 1 2
## QUINTANA ROO 2 1 0 0 0 1
## SAN LUIS POTOSI 3 0 0 3 0 1
## SINALOA 1 0 1 1 0 1
## SONORA 2 3 1 1 0 1
## TABASCO 1 0 4 3 0 1
## TAMAULIPAS 7 2 3 4 0 3
## TLAXCALA 0 2 0 0 0 1
## VERACRUZ 25 4 4 7 0 3
## YUCATAN 0 0 0 0 0 1
## ZACATECAS 4 0 1 1 0 1#Se generaron distintas base para cada cluster y con ello sacar sus estadisticas
#descritivas de cada cluster y obtener la media y asi dar respuesta al objetivo
#especifico 2
#BASE DEL CLUSTER 1
base.1 = datos[c("CHIAPAS","AGUASCALIENTES","TLAXCALA","OAXACA","MORELOS","SONORA",
"ZACATECAS","DURANGO","SAN LUIS POTOSI","BAJA CALIFORNIA","TABASCO",
"YUCATAN","CAMPECHE","NAYARIT","SINALOA","BAJA CALIFORNIA SUR","COLIMA",
"CHIHUAHUA","GUERRERO","QUINTANA ROO"),]
base.1## DERRAME EXPLOSION FUGA INCENDIO OTRO estadoclus
## CHIAPAS 0 2 3 0 0 1
## AGUASCALIENTES 0 3 0 0 0 1
## TLAXCALA 0 2 0 0 0 1
## OAXACA 2 2 2 2 0 1
## MORELOS 1 3 1 1 0 1
## SONORA 2 3 1 1 0 1
## ZACATECAS 4 0 1 1 0 1
## DURANGO 3 0 1 2 0 1
## SAN LUIS POTOSI 3 0 0 3 0 1
## BAJA CALIFORNIA 2 0 1 5 0 1
## TABASCO 1 0 4 3 0 1
## YUCATAN 0 0 0 0 0 1
## CAMPECHE 0 0 0 0 0 1
## NAYARIT 0 0 0 0 0 1
## SINALOA 1 0 1 1 0 1
## BAJA CALIFORNIA SUR 1 0 0 0 0 1
## COLIMA 1 0 1 0 0 1
## CHIHUAHUA 3 1 4 0 0 1
## GUERRERO 1 1 0 1 0 1
## QUINTANA ROO 2 1 0 0 0 1summary(base.1)## DERRAME EXPLOSION FUGA INCENDIO OTRO
## Min. :0.00 Min. :0.0 Min. :0 Min. :0.00 Min. :0
## 1st Qu.:0.00 1st Qu.:0.0 1st Qu.:0 1st Qu.:0.00 1st Qu.:0
## Median :1.00 Median :0.0 Median :1 Median :0.50 Median :0
## Mean :1.35 Mean :0.9 Mean :1 Mean :1.00 Mean :0
## 3rd Qu.:2.00 3rd Qu.:2.0 3rd Qu.:1 3rd Qu.:1.25 3rd Qu.:0
## Max. :4.00 Max. :3.0 Max. :4 Max. :5.00 Max. :0
## estadoclus
## Min. :1
## 1st Qu.:1
## Median :1
## Mean :1
## 3rd Qu.:1
## Max. :1#BASE DEL CLUSTER 2
base.2 = datos[c("CIUDAD DE MEXICO","MEXICO","HIDALGO","PUEBLA","QUERETARO"),]
base.2## DERRAME EXPLOSION FUGA INCENDIO OTRO estadoclus
## CIUDAD DE MEXICO 3 9 26 9 1 2
## MEXICO 4 9 8 13 1 2
## HIDALGO 10 4 1 7 1 2
## PUEBLA 1 3 7 2 1 2
## QUERETARO 1 3 2 2 1 2summary(base.2)## DERRAME EXPLOSION FUGA INCENDIO OTRO
## Min. : 1.0 Min. :3.0 Min. : 1.0 Min. : 2.0 Min. :1
## 1st Qu.: 1.0 1st Qu.:3.0 1st Qu.: 2.0 1st Qu.: 2.0 1st Qu.:1
## Median : 3.0 Median :4.0 Median : 7.0 Median : 7.0 Median :1
## Mean : 3.8 Mean :5.6 Mean : 8.8 Mean : 6.6 Mean :1
## 3rd Qu.: 4.0 3rd Qu.:9.0 3rd Qu.: 8.0 3rd Qu.: 9.0 3rd Qu.:1
## Max. :10.0 Max. :9.0 Max. :26.0 Max. :13.0 Max. :1
## estadoclus
## Min. :2
## 1st Qu.:2
## Median :2
## Mean :2
## 3rd Qu.:2
## Max. :2#BASE DEL CLUSTER 3
base.3 = datos[c("VERACRUZ","MICHOACAN","COAHUILA","TAMAULIPAS","JALISCO",
"GUANAJUATO","NUEVO LEON"),]
base.3## DERRAME EXPLOSION FUGA INCENDIO OTRO estadoclus
## VERACRUZ 25 4 4 7 0 3
## MICHOACAN 8 1 0 6 0 3
## COAHUILA 5 2 1 4 0 3
## TAMAULIPAS 7 2 3 4 0 3
## JALISCO 7 5 2 12 0 3
## GUANAJUATO 3 3 5 8 0 3
## NUEVO LEON 5 0 1 10 0 3summary(base.3)## DERRAME EXPLOSION FUGA INCENDIO OTRO
## Min. : 3.000 Min. :0.000 Min. :0.000 Min. : 4.000 Min. :0
## 1st Qu.: 5.000 1st Qu.:1.500 1st Qu.:1.000 1st Qu.: 5.000 1st Qu.:0
## Median : 7.000 Median :2.000 Median :2.000 Median : 7.000 Median :0
## Mean : 8.571 Mean :2.429 Mean :2.286 Mean : 7.286 Mean :0
## 3rd Qu.: 7.500 3rd Qu.:3.500 3rd Qu.:3.500 3rd Qu.: 9.000 3rd Qu.:0
## Max. :25.000 Max. :5.000 Max. :5.000 Max. :12.000 Max. :0
## estadoclus
## Min. :3
## 1st Qu.:3
## Median :3
## Mean :3
## 3rd Qu.:3
## Max. :3#Usamos la base llamada "Promedios de los cluster"
#Con esto damos resouesta al objetivo 2
datos_1 = read.csv(file = "C:\\Users\\karel\\OneDrive\\Documentos\\TAREAS KARELY 2\\CONSULTORIA\\Promedios de los cluster.csv", header = T, sep = ",")
datos_1## X Cluster.1 Cluster.2 Cluster.3
## 1 Derrame 3.8 1.35 8.57
## 2 Explosion 5.6 0.90 2.42
## 3 Fuga 8.8 1.00 2.28
## 4 Incendio 6.6 1.00 7.28
## 5 Otro 1.0 0.00 0.00par(mfrow=c(1,3))
#Medias del cluster 1
g1 = barplot(datos_1$Cluster.1, ylim = c(0,12), main = "Cluster 1" ,ylab = "Promedio",
xlab = "Tipo de emergencia ambiental",
col = c("Blue","yellow","Red","Pink","green"),
names.arg = c("Derrame","Explosion","Fuga","Incendio",
"Otro"))
text(g1, datos_1$Cluster.1+0.4, labels = datos_1$Cluster.1)
#Medias del cluster 2
g2 = barplot(datos_1$Cluster.2, ylim = c(0,2), main = "Cluster 2" ,ylab = "Promedio",
xlab = "Tipo de emergencia ambiental",
col = c("Blue","yellow","Red","Pink","green"),
names.arg = c("Derrame","Explosion","Fuga","Incendio",
"Otro"))
text(g2, datos_1$Cluster.2+0.1, labels = datos_1$Cluster.2)
#Medias del cluster 3
g3 = barplot(datos_1$Cluster.3, ylim = c(0,12), main = "Cluster 3" ,ylab = "Promedio",
xlab = "Tipo de emergencia ambiental",
col = c("Blue","yellow","Red","Pink","green"),
names.arg = c("Derrame","Explosion","Fuga","Incendio",
"Otro"))
text(g3, datos_1$Cluster.3+0.4, labels = datos_1$Cluster.3)
Proyecto completo “EMERGENCIAS AMBIENTALES ASOCIADAS A SUSTANCIAS QUÍMICAS EN MÉXICO 2017”