Niv_Inv_Analysis: Create plots about inventory level.

In PaulLulo/AzzortiPackage: Create diagrams and tables about services, inventory, and the best combination of sales predictions.

Usage

Niv_Inv_Analysis(df_base,lugar,linea,momento)

Arguments

df_base

The data must be constituted as follows:

• 1) CODI_CAMP: Sales campaign (ej. 201718..201909)

• 2) NOMB_LINE: Line of the SKU (ej. "JO JOYERIA")

• 3) CODI_VENT: Sales code SKU (ej. 123456)

• 4) DESCRIPCION: Name of the SKU.

• 5) REAL: Real Demand SKU.

• 7) Q_RG3: Traditional forecast for the SKU.

• 8) Q_MKT: Marketing area estimate.

• 9...) Comparative Models (ej. "Q_20", "Q_30")

• #) Must be the "Besty Model" (Q_BESTY)

lugar	Three letters summarizing the name of the place (ej. "PER")
linea	Three letters summarizing the name of the line (ej. "ROE")
momento	Six letters summarizing the names of the current moment and prediction moment (ej. "ADVNAC")

Examples

#Headers
DF_TOTAL <- data.frame(CODI_CAMP = "",
                      NOMB_LINE = "",
                      CODI_VENT = "",
                      DESCRIPCION = "",
                      REAL = "",
                      Q_RG3 = "",
                      Q_MKT = "",
                      Q_30 = "",
                      Q_50 = "",
                      Q_70 = ""
)

DF_TOTAL<- DF_TOTAL[-c(1:nrow(DF_TOTAL)),]
campanas<- c(201901, 201902, 201903, 201904)

acumula<- DF_TOTAL

for(i in 1: length(campanas)) {
  #i=1
  acumula <- data.frame(CODI_CAMP = campanas[i],
                        NOMB_LINE = "RE ROPA EXTERIOR",
                        CODI_VENT = ceiling(runif(100,100000,999999)),
                        DESCRIPCION = paste0("P",c(1:100)),
                        REAL = 1000+(1:100)*10,
                        Q_RG3 = abs(1000+(1:100)*10 + rnorm(100,300,800)),
                        Q_MKT = abs(1000+(1:100)*10 + rnorm(100,100,700)),
                        Q_30 = abs(1000+(1:100)*10 + rnorm(100,400,700)),
                        Q_50 = abs(1000+(1:100)*10 + rnorm(100,450,900)),
                        Q_70 = abs(1000+(1:100)*10 + rnorm(100,700,900))
  )


  DF_TOTAL<- rbind(DF_TOTAL,acumula)
}

#
DF_TOTAL<-gen_q_besty(DF_TOTAL)
#
NIVEL_INVENTARIO<- Niv_Inv_Analysis(DF_TOTAL,lugar= "PER", linea= "ROE", momento="ADVNAC")

PaulLulo/AzzortiPackage documentation built on March 28, 2020, 12:55 a.m.