296 lines
13 KiB
R
296 lines
13 KiB
R
library(plyr)
|
|
library(dplyr)
|
|
library(ggdistribute)
|
|
library(ggplot2)
|
|
library(ggExtra)
|
|
library(scales)
|
|
library(gridExtra)
|
|
library(stringr);
|
|
library(DBI);
|
|
|
|
priceg = ".*"
|
|
mold = "XTG154"
|
|
colgrp = ".*"
|
|
branding = ".*"
|
|
outlier = 300
|
|
xfact = 4
|
|
yfact = 5
|
|
xtrans = "identity"
|
|
ytrans = "identity"
|
|
lprice = .01
|
|
uprice = 30.00
|
|
pqty = 2000
|
|
|
|
#prod_plot <- function(priceg, mold, colgrp, branding, outlier, xfact, yfact,xtrans, ytrans, lprice, uprice, pqty ) {
|
|
sql = paste("SELECT * FROM rlarp.rlang_plot('",mold,"','",priceg,"','",colgrp,"','",branding,"',",lprice,",",uprice,") x",sep="");
|
|
|
|
con <- dbConnect(RPostgres::Postgres(),dbname = 'ubm',
|
|
host = 'usmidlnx01',
|
|
port = 5030,
|
|
user = 'report',
|
|
password = 'report')
|
|
|
|
d <- dbGetQuery(con, sql)
|
|
|
|
dbDisconnect(con)
|
|
|
|
#-----each graph is composed of 2 pieces when doing the facet() pivot, these 2 pieces make up the plot defition-----
|
|
d$f7 <- substring(d$mold,1,7)
|
|
#d$dim1 <- trimws(paste(d$f7,d$v1ds));
|
|
#d$dim1 <- trimws(paste(d$f7,d$colgrp,d$brnd,d$package,d$suffix,d$kit));
|
|
d$dim1 <- trimws(paste(d$base_item,d$colgrp,d$brnd));
|
|
d$dim2 <- trimws(paste(d$chgrp));
|
|
d$plot <- trimws(paste(d$dim1,d$dim2));
|
|
d$sub <- trimws(paste("v1:",d$coltier,".",substring(d$brnd,1,1),".",d$package,".",d$suffix,".",d$kit));
|
|
#d$sub <- trimws(paste(d$oseas));
|
|
#d$sub <- trimws(paste(d$geo));
|
|
d$qty = d$qty/1000;
|
|
#-----need to include credits------
|
|
d$volmin = 0.0001;
|
|
d$season = factor(d$oseas);
|
|
#-----build widths for how many scenarios are present----------------------------------------------------------------
|
|
dim1 <- data.frame(unique(d$dim1));
|
|
var.dim1 = nrow(dim1);
|
|
dim2 <- data.frame(unique(d$dim2));
|
|
var.dim2 = nrow(dim2);
|
|
#-----------need to do an aggregate to consolidate to single customer point
|
|
d <- subset(d,chgrp != "X", promo != "Excess and Obsolete");
|
|
#-------------------------eliminate outliers-------------------------------------------------------------------------
|
|
dx <- boxplot.stats(d$price, coef = outlier);
|
|
ex <- data.frame(dx$out);
|
|
#ex; #list the excluded outlier prices
|
|
colnames(ex)[1] = "price";
|
|
outl <- inner_join(d,ex, by = "price");
|
|
outl;
|
|
d <- anti_join(d,ex, by = "price");
|
|
#---------switch to log axis if there are still outliers with a coefficient 3----------------------------------------
|
|
var.trans = "identity"
|
|
if (nrow(data.frame(boxplot.stats(d$price, coef = 3)$out)) >= 1){
|
|
var.trans = "log2"
|
|
};
|
|
|
|
|
|
glob <- ddply(d, .(), summarise,
|
|
Volume=round(sum(qty),0),
|
|
Sales=round(sum(sales),0),
|
|
WeightedAvg=round(sum(sales)/sum(qty),4),
|
|
Mean=round(mean(price),4),
|
|
StdDev=round(sd(price),4),
|
|
Target=round(mean(target_price),4),
|
|
AnyMax=round(max(c(price,target_price)),4),
|
|
AnyMin=round(min(c(price,target_price)),4),
|
|
PriceMin = round(min(price),4),
|
|
PriceMax = round(max(price),4),
|
|
VolumeMin = round(min(pmax(qty,volmin)),4),
|
|
VolumeMax = round(max(qty),1),
|
|
VolumeSD=round(sd(pmax(qty,volmin)),4)
|
|
);
|
|
#targets <- ddply(d, .(dim1, dim2, plot,mold,chan,colgrp, brnd), summarise,
|
|
targets <- ddply(d, .(dim2, v1ds, dim1, plot,mold,chan,colgrp, brnd), summarise,
|
|
Volume=round(sum(qty),0),
|
|
Sales=round(sum(sales),0),
|
|
WeightedAvg=round(sum(sales)/sum(qty*1000),4),
|
|
Mean=round(mean(price),4),
|
|
StdDev=round(sd(price),4),
|
|
Target=round(mean(target_price),4),
|
|
HexCol = min(hex)
|
|
);
|
|
seas <- ddply(d, .(dim1, dim2, plot, oseas), summarise,
|
|
Volume=round(sum(qty),0),
|
|
Sales=round(sum(sales),0),
|
|
WeightedAvg=round(sum(sales)/sum(qty*1000),4),
|
|
Mean=round(mean(price),4),
|
|
StdDev=round(sd(price),4),
|
|
Target=round(mean(target_price),4)
|
|
);
|
|
#-----------------blank dataframe in case there is no data for a scenario-----------------
|
|
blank <- glob
|
|
blank$customer = 'NO DATA'
|
|
blank$oseas = 2020
|
|
blank$season = '2020'
|
|
blank$qty = blank$VolumeSD
|
|
blank$price = blank$Mean
|
|
#blank;
|
|
|
|
yr1 <- subset(seas, oseas == 2020);
|
|
yr2 <- subset(seas, oseas == 2021);
|
|
dir_t <- subset(targets, chan == "DIR");
|
|
drp_t <- subset(targets, chan == "DRP");
|
|
whs_t <- subset(targets, chan == "WHS");
|
|
|
|
anno <- data.frame(unique(d[c("plot","dim2","dim1","mold","colgrp","brnd")]));
|
|
anno <- data.frame(anno,qty=c(Inf),price=c(Inf),hjustvar = c(1),vjustvar = c(1));
|
|
|
|
anno <- merge(x = anno, y = yr1[ , c("plot","Mean","WeightedAvg", "StdDev","Volume")], by = "plot", all.x=TRUE);
|
|
names(anno)[names(anno)=="Mean"] <- "yr1_mn";
|
|
names(anno)[names(anno)=="WeightedAvg"] <- "yr1_wa";
|
|
names(anno)[names(anno)=="StdDev"] <- "yr1_sd";
|
|
names(anno)[names(anno)=="Volume"] <- "yr1_vo";
|
|
|
|
anno <- merge(x = anno, y = yr2[ , c("plot","Mean","WeightedAvg", "StdDev","Volume")], by = "plot", all.x=TRUE);
|
|
names(anno)[names(anno)=="Mean"] <- "yr2_mn";
|
|
names(anno)[names(anno)=="WeightedAvg"] <- "yr2_wa";
|
|
names(anno)[names(anno)=="StdDev"] <- "yr2_sd";
|
|
names(anno)[names(anno)=="Volume"] <- "yr2_vo";
|
|
|
|
anno <- merge(x = anno, y = dir_t[ , c("plot","Target")], by = "plot", all.x=TRUE);
|
|
names(anno)[names(anno)=="Target"] <- "t_dir";
|
|
|
|
anno <- merge(x = anno, y = drp_t[ , c("plot","Target")], by = "plot", all.x=TRUE);
|
|
names(anno)[names(anno)=="Target"] <- "t_drp";
|
|
|
|
anno <- merge(x = anno, y = whs_t[ , c("plot","Target")], by = "plot", all.x=TRUE);
|
|
names(anno)[names(anno)=="Target"] <- "t_whs";
|
|
|
|
csv <- anno;
|
|
csv <- subset(csv, select = c(mold, dim2, colgrp, brnd, yr1_mn, yr2_mn, yr1_wa, yr2_wa, t_dir, t_drp, t_whs));
|
|
csv$t_dir_rev = csv$t_dir;
|
|
csv$t_drp_rev = csv$t_drp;
|
|
csv$t_whs_rev = csv$t_whs;
|
|
names(csv)[names(csv)=="dim2"] <- "chgrp";
|
|
csv;
|
|
#write.csv(csv, file = paste("//home/ptrowbridge/pt_share/",file_name,"_TRG.csv",sep=""), row.names = FALSE);
|
|
|
|
p=ggplot(d, aes(x=qty, y=price, color=v1ds)) +
|
|
#scale_color_manual(values=c("#F44336", "#E91E63", "#9C27B0","#673ab7","#3f51b5","#2196f3","#03a9f4","#00bcd4","#009688","#4caf50","#8bc34a","#8bc34a","#ffeb3b","#ffc107")) +
|
|
geom_point(size=2) +
|
|
geom_text(data = anno,
|
|
aes(
|
|
x=qty,y=price,
|
|
color = NULL,
|
|
hjust=hjustvar,vjust=vjustvar,
|
|
label=paste(
|
|
" mean | wavg | stdd | vol \n",
|
|
"-------|--------|--------|---------\n",
|
|
"PY(black): ",
|
|
#----------mean-------------------------------
|
|
str_pad(
|
|
format(round(yr1_mn, 4), nsmall = 4),
|
|
width = 6,
|
|
side = "both",
|
|
pad = " "),
|
|
"|",
|
|
#----------weighted average-------------------
|
|
str_pad(
|
|
format(round(yr1_wa, 4), nsmall = 4),
|
|
width = 6,
|
|
side = "both",
|
|
pad = " "
|
|
),
|
|
#----------standard deviation-----------------
|
|
"|",
|
|
str_pad(
|
|
format(round(yr1_sd, 4), nsmall = 4),
|
|
width = 6,
|
|
side = "both",
|
|
pad = " "),
|
|
"|",
|
|
#----------volume-----------------------------
|
|
str_pad(
|
|
format(round(yr1_vo/1000, 4), nsmall = 4,width = 7),
|
|
width = 6,
|
|
side = "both",
|
|
pad = " "),
|
|
"\n",
|
|
"CY(green): ",
|
|
#----------mean-------------------------------
|
|
str_pad(
|
|
format(round(yr2_mn, 4), nsmall = 4),
|
|
width = 6,
|
|
side = "both",
|
|
pad = " "),
|
|
"|",
|
|
#----------weighted average-------------------
|
|
str_pad(
|
|
format(round(yr2_wa, 4), nsmall = 4),
|
|
width = 6,
|
|
side = "both",
|
|
pad = " "
|
|
),
|
|
#----------standard deviation-----------------
|
|
"|",
|
|
str_pad(
|
|
format(round(yr2_sd, 4), nsmall = 4),
|
|
width = 6,
|
|
side = "both",
|
|
pad = " "),
|
|
"|",
|
|
#----------volume-----------------------------
|
|
str_pad(
|
|
format(round(yr2_vo/1000, 4), nsmall = 4,width = 7),
|
|
width = 6,
|
|
side = "both",
|
|
pad = " "),
|
|
"\n",
|
|
#format(round(yr2_mn, 4), nsmall = 4),"|",format(round(yr2_wa, 4), nsmall = 4),"|",format(round(yr2_sd, 4), nsmall = 4),"|",format(round(yr2_vo/1000, 4), nsmall = 4,width = 7),"\n",
|
|
" \n",
|
|
" dir (b) | drp (y) | whs (r) \n",
|
|
"-----------|-----------|-----------\n",
|
|
"Targets: ",
|
|
str_pad(
|
|
format(round(t_dir, 4), nsmall = 4),
|
|
width = 9,
|
|
side ="both",
|
|
pad=" "),
|
|
"|",
|
|
str_pad(
|
|
format(round(t_drp, 4), nsmall = 4),
|
|
width = 9,
|
|
side = "both",
|
|
pad = " "),
|
|
"|",
|
|
str_pad(
|
|
format(round(coalesce(t_whs,0), 4), nsmall = 4),
|
|
width = 10,
|
|
side = "both",
|
|
pad = " ")
|
|
)
|
|
),
|
|
family="Courier",
|
|
size = 3,
|
|
#use check_overlap to avoid doubling up the price info print, it will print over top of itself based on the color=sub count of uniques
|
|
check_overlap=TRUE
|
|
) +
|
|
geom_text(aes(label=customer),size=3, vjust = 2, hjust = 0, check_overlap=TRUE) +
|
|
facet_grid(dim2~dim1) +
|
|
#facet_grid(chgrp~plot) +
|
|
#facet_wrap(plot) +
|
|
geom_hline(data=yr1, aes(yintercept=Mean),linetype="dashed", size=.5, colour="black") +
|
|
#geom_hline(data=yr1, aes(yintercept=Mean - StdDev),linetype="dashed", size=.5, colour="black") +
|
|
#geom_hline(data=yr1, aes(yintercept=Mean - StdDev * 2),linetype="dashed", size=.5, colour="black") +
|
|
geom_hline(data=yr1, aes(yintercept=WeightedAvg),linetype="solid", size=.5, colour="black") +
|
|
geom_vline(aes(xintercept = pqty/1000) ,linetype = "dashed",size = .5, colour = "orange") +
|
|
#geom_vline(aes(xintercept = pqty/1000*8) ,linetype = "dashed",size = .5, colour = "grey") +
|
|
geom_vline(aes(xintercept = pqty/1000*8) ,linetype = "dashed",size = .5, colour = "grey") +
|
|
#geom_hline(data=yr2, aes(yintercept=Mean),linetype="dashed", size=.5, colour="green") +
|
|
#geom_hline(data=yr2, aes(yintercept=Mean - StdDev),linetype="dashed", size=.5, colour="green") +
|
|
#geom_hline(data=yr2, aes(yintercept=Mean - StdDev * 2),linetype="dashed", size=.5, colour="green") +
|
|
#geom_hline(data=yr2, aes(yintercept=WeightedAvg),linetype="solid", size=.5, colour="green") +
|
|
geom_hline(data=drp_t, aes(yintercept=Target, color=v1ds),linetype="solid", size=.5) +
|
|
geom_hline(data=dir_t, aes(yintercept=Target, color=v1ds),linetype="solid", size=.5) +
|
|
geom_hline(data=whs_t, aes(yintercept=Target, color=v1ds),linetype="solid", size=.5) +
|
|
#scale_y_continuous(breaks=seq(0, 10, round(glob$StdDev * .5,2))) +
|
|
scale_y_continuous(
|
|
#breaks=seq(glob$PriceMin, glob$PriceMax, round(glob$StdDev * .5,4)),
|
|
breaks = pretty_breaks(n=20),
|
|
limits = c(glob$AnyMin, glob$AnyMax), trans = ytrans
|
|
) +
|
|
scale_x_continuous(
|
|
#breaks=seq(glob$VolumeMin, glob$VolumeMax, round(glob$VolumeSD * 1.0,4)),
|
|
#breaks = pretty_breaks(n=10),
|
|
limits = c(glob$VolumeMin, glob$VolumeMax*1.1), trans = xtrans
|
|
) +
|
|
#scale_x_continuous(trans='log2') +
|
|
#scale_x_continuous(breaks=seq(0,1000,round(glob$VolumeSD * 1,2)), trans = 'log2') +
|
|
#geom_label(colour = "white", fontface = "bold") +
|
|
#geom_text(aes(label=ds$ship_group),position = position_dodge(width=.9), size=2) +
|
|
theme(legend.position="none");
|
|
cp_pvt = p + theme_bw();
|
|
#targets;
|
|
options(
|
|
repr.plot.width=var.dim1*xfact,
|
|
repr.plot.height=var.dim2*yfact
|
|
);
|
|
cp_pvt;
|
|
#};
|