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01-fulton-EDA.R
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# Base de datos -----
dbT <- readxl::read_excel("BD.xlsx",
sheet = "BDT")
# Recodificacion ----
require(data.table)
df <- data.table(dbT,
stringsAsFactors = T)
df$ID <- as.character(df$ID)
# EDA (Exploratory Data Analysis)
### Peso y Medidas (Crudas y log)
# Ajuste visualizacion ----
op <- par(mfcol= c (2,2),
mar = c(4,4,2,2))
# BP-Cumulativos
boxplot(df[,10:16],
col = "lightgray",
ylab = "",
xlab = "Medidas",
main = "",
horizontal = T,
cex.axis = 0.8,
cex.lab = 0.8)
# BP-log-Cum
boxplot(df[,10:16],
col = "lightgray",
ylab = "",
xlab = "log Medidas",
main = "",
horizontal = T,
log = "x",
cex.axis = 0.8,
cex.lab = 0.8)
# CP-Cumulativo
dotchart(df$Peso[!is.na(df$Peso)],
bg = "black",
pt.cex = 1.5,
labels = df$ID[!is.na(df$ID)],
lcolor = "gray",
cex = 0.6,
xlab = "Peso (kg)",
ylab = "")
# CP-log-Cum
dotchart(log(df$Peso[!is.na(df$Peso)]),
bg = "black",
pt.cex = 1.5,
labels = df$ID[!is.na(df$ID)],
lcolor = "gray",
cex = 0.6,
xlab = "log Peso (kg)",
ylab = "")
# Crudas por sexo ----
require(data.table)
H <- df[Sexo == "H"]
M <- df[Sexo == "M"]
# BP-Hembras
boxplot(H[,10:16],
col = "lightgray",
ylab = "",
xlab = "Hembras",
main = "",
horizontal = T,
cex.axis = 0.8,
cex.lab = 0.8)
# BP-Machos
boxplot(M[,10:16],
col = "lightgray",
ylab = "",
xlab = "Machos",
main = "",
horizontal = T,
cex.axis = 0.8,
cex.lab = 0.8)
# CP-Hembras
dotchart(H$Peso[!is.na(H$Peso)],
bg = "black",
pt.cex = 1.5,
labels = H$ID,
lcolor = "gray",
cex = 0.7,
xlab = "Peso (kg)",
ylab = "")
# CP-Machos
dotchart(M$Peso[!is.na(M$Peso)],
bg = "black",
pt.cex = 1.5,
labels = M$ID[!is.na(M$ID)],
lcolor = "gray",
cex = 0.7,
xlab = "Peso (kg)",
ylab = "")
# Log por sexo ----
# BP-logHembras
boxplot(H[,10:16],
col = "lightgray",
ylab = "",
xlab = "log Hembras",
main = "",
horizontal = T,
log = "x",
cex.axis = 0.8,
cex.lab = 0.8)
# BP-logMachos
boxplot(M[,10:16],
col = "lightgray",
ylab = "",
xlab = "log Machos",
main = "",
horizontal = T,
log = "x",
cex.axis = 0.8,
cex.lab = 0.8)
# CP-logHembras
dotchart(log(H$Peso[!is.na(H$Peso)]),
bg = "black",
pt.cex = 1.5,
labels = H$ID[!is.na(H$ID)],
lcolor = "gray",
cex = 0.7,
xlab = "log Peso (kg)",
ylab = "")
# CP-logMachos
dotchart(log(M$Peso[!is.na(M$Peso)]),
bg = "black",
pt.cex = 1.5,
labels = M$ID[!is.na(M$ID)],
lcolor = "gray",
cex = 0.7,
xlab = "log Peso (kg)",
ylab = "")
# Resetear ajustes de visualizacion ----
par(op)
### Multi-panel Cleveland dot plot----
# Variables con logaritmos base 10 (log10) ----
require(dplyr)
# Cumulativo
K <- df %>%
mutate(logW =log10(Peso),
logLTC =log10(LTC),
logCCu =log10(CCu),
logCPCH =log10(CPCH),
logCCL =log10(CCL),
logLHC =log10(LHC),
logLT =log10(LT))
# Hembras
KH <- H %>%
mutate(logW =log10(Peso),
logLTC =log10(LTC),
logCCu =log10(CCu),
logCPCH =log10(CPCH),
logCCL =log10(CCL),
logLHC =log10(LHC),
logLT =log10(LT))
# Machos
KM <- M %>%
mutate(logW =log10(Peso),
logLTC =log10(LTC),
logCCu =log10(CCu),
logCPCH =log10(CPCH),
logCCL =log10(CCL),
logLHC =log10(LHC),
logLT =log10(LT))
# Cleveland dot plot ----
require(lattice)
# Variables crudas ----
Z <- cbind(df$LTC,
df$CCu,
df$CPCH,
df$CCL,
df$LHC,
df$LT)
# Colnames
colnames(Z) <- c("Longitud de Cráneo", "Circunferencia de Cuello", "Circunferencia de Pecho","Circunferencia de Cola", "Longitud Hocico - Cloaca", "Longitud Total")
# Dotplot
dotplot(as.matrix(Z),
groups = FALSE,
strip =
strip.custom(bg = 'grey',
par.strip.text = list(cex = 0.8)),
scales = list(x = list(relation = "sliced"),
y = list(relation = "sliced"),
draw = F),
col = 1, cex = 0.8, pch = 19,
xlab = "Medidas en cm",
ylab = "")
# Variables log ----
Y <- cbind(K$logW,
K$logCCu,
K$logCPCH,
K$logCCL,
K$logLHC,
K$logLT)
# Colnames log
colnames(Y) <- c("Log Cráneo", "Log Cuello", "Log Pecho","Log Cola", "Log Hocico - Cloaca", "Log Longitud Total")
# Dotplot log
dotplot(as.matrix(Y),
groups = FALSE,
strip =
strip.custom(bg = 'grey',
par.strip.text = list(cex = 0.8)),
scales = list(x = list(relation = "sliced"),
y = list(relation = "sliced"),
draw = F),
col = 1, cex = 0.8, pch = 19,
xlab = "Log Medidas Sin distinción de sexo",
ylab = "")
# Variables log por sexo ----
# Machos
Mc <- cbind(KM$logW,
KM$logCCu,
KM$logCPCH,
KM$logCCL,
KM$logLHC,
KM$logLT)
# Colnames log
colnames(Mc) <- c("Log Cráneo", "Log Cuello", "Log Pecho","Log Cola", "Log Hocico - Cloaca", "Log Longitud Total")
# Dotplot log
dotplot(as.matrix(Mc),
groups = FALSE,
strip =
strip.custom(bg = 'grey',
par.strip.text = list(cex = 0.8)),
scales = list(x = list(relation = "sliced"),
y = list(relation = "sliced"),
draw = F),
col = 1, cex = 0.8, pch = 19,
xlab = "Log Medidas Machos",
ylab = "")
# Hembras
Hc <- cbind(KH$logW,
KH$logCCu,
KH$logCPCH,
KH$logCCL,
KH$logLHC,
KH$logLT)
# Colnames log
colnames(Hc) <- c("Log Cráneo", "Log Cuello", "Log Pecho","Log Cola", "Log Hocico - Cloaca", "Log Longitud Total")
# Dotplot log
dotplot(as.matrix(Hc),
groups = FALSE,
strip =
strip.custom(bg = 'grey',
par.strip.text = list(cex = 0.8)),
scales = list(x = list(relation = "sliced"),
y = list(relation = "sliced"),
draw = F),
col = 1, cex = 0.8, pch = 19,
xlab = "Log Medidas Hembras",
ylab = "")