SCM Exploratorio

Importar Datasets

library(readr)
transporte <- read_delim("https://themys.sid.uncu.edu.ar/rpalma/R-cran/SCM_Perform/transporte.csv", 
    delim = ";", escape_double = FALSE, col_types = cols(H5 = col_factor(levels = c("Anmat", 
        "Expired", "Waiver", "Devolucion"))), 
    locale = locale(decimal_mark = ",", grouping_mark = "."), 
    trim_ws = TRUE)

## New names:
## • `` -> `...1`

Análisis de datos categóricos

plot(transporte$H5,transporte$H4,main = "Inversión en TIC por tipo de carga",ylab="Porcentaje del presupuesto anual ejecutado",xlab="Logística Inversa de Carga")

Datos sumario

plot(transporte$H5)

summary(transporte)

##       ...1             id              H1               H2       
##  Min.   :  1.0   Min.   :100.0   Min.   : 1.008   Min.   :201.0  
##  1st Qu.:148.2   1st Qu.:279.2   1st Qu.: 4.607   1st Qu.:346.2  
##  Median :295.5   Median :447.0   Median : 7.948   Median :491.0  
##  Mean   :295.5   Mean   :449.1   Mean   : 7.983   Mean   :482.5  
##  3rd Qu.:442.8   3rd Qu.:620.8   3rd Qu.:11.374   3rd Qu.:619.0  
##  Max.   :590.0   Max.   :790.0   Max.   :14.995   Max.   :747.0  
##        H3               H4                  H5     
##  Min.   : 20.00   Min.   :0.4204   Anmat     :145  
##  1st Qu.: 54.25   1st Qu.:0.4818   Expired   :138  
##  Median : 86.00   Median :0.5458   Waiver    :156  
##  Mean   : 85.92   Mean   :0.5467   Devolucion:151  
##  3rd Qu.:118.75   3rd Qu.:0.6097                   
##  Max.   :150.00   Max.   :0.6798

Afectación de mano de obra (u Horas Hombre) a las Operaciones

hist(transporte$H1, breaks = 50, main= "H1 % Personas afectadas a Operaciones", xlab="Personas por Equipo", ylab="Frecuencia" )

hist(transporte$H1, breaks = 2, main= "H1 % Personas afectadas a Operaciones", xlab="Personas por Equipo", ylab="Frecuencia" )

Varianza en el tamaño de equipos

boxplot(transporte$H1)

mean(transporte$H1)

## [1] 7.983239

sd(transporte$H1)

## [1] 4.037328

A

library(ggplot2) 

#create data frame
df <- data.frame(result = transporte$H5,
                 reclamo = transporte$H5,
                 costo = transporte$H1)
                 viajes = transporte$H2

#create bar chart of teams
ggplot(df, aes(x=reclamo)) +
  geom_bar()

#create boxplots of points, grouped by team
ggplot(df, aes(x=reclamo, y=costo)) +
  geom_boxplot(fill='steelblue')

#create table of counts
counts <- table(df$result, df$costo)

mosaicplot(counts, xlab='SCM Performance', ylab='Reclamo',
           main='Costos por Viaje Reclamo mes Enero', col='steelblue')