from eipdb_sandbox.ling_sls_brnd_demog a
where a.gma_nbr in (2,5)
and a.trn_sls_dte between '2016-11-14' AND '2016-12-16'
group by 1
order by 1;")
dat1$perc <- dat1$sld_qty/sum(dat1$sld_qty)
p1 <- ggplot(dat1, aes(x = factor(1), y =sld_qty, fill = channel)) +
geom_bar(width = 1, stat = "identity") +
scale_fill_manual(values = c("red", "blue")) +
coord_polar(theta="y", start = pi / 3) +
##labs(title = "Kohl's Sold Items by Channel") +
geom_text_repel(aes(label=scales::percent(perc)), size=4.5) + ylab("") + xlab("") +
theme_void()
dat2 <-dbGetQuery(conn,"select new_ind, sum(a.sld_qty)
from eipdb_sandbox.ling_sls_brnd_demog a
where a.gma_nbr in (2,5)
and a.trn_sls_dte between '2016-11-14' AND '2016-12-16'
group by 1
order by 1;")
dat2$new_ind <- factor(dat2$new_ind)
dat2$perc <- dat2$sld_qty/sum(dat2$sld_qty)
p2 <- ggplot(dat2, aes(x = "", y =sld_qty, fill = new_ind)) +
geom_bar(width = 1, stat = "identity") +
scale_fill_manual(values = c("darkgreen", "orangered", "red")) +
coord_polar("y", start = pi / 3) +
##labs(title = "Kohl's Sold Items by New/Existed Customer") +
geom_text_repel(aes(label=scales::percent(perc)), size=4.5) + ylab("") + xlab("") +
theme_void()
dat3 <-dbGetQuery(conn,"select sku_stat_desc, sum(a.sld_qty)
from eipdb_sandbox.ling_sls_brnd_demog a
where a.gma_nbr in (2,5)
and a.trn_sls_dte between '2016-11-14' AND '2016-12-16'
group by 1
order by 1;")
dat3$perc <- dat3$sld_qty/sum(dat3$sld_qty)
dat3 <- dat3[order(dat3$sld_qty),]
p3 <- ggplot(dat3, aes(x = "", y =sld_qty, fill = sku_stat_desc)) +
geom_bar(width = 1, stat = "identity") +
scale_fill_brewer(palette = "Spectral") +
coord_polar("y", start = pi / 3) +
##labs(title = "Kohl's Sold Items by SKU Status") +
geom_text_repel(aes(label=scales::percent(perc)), size=4.5) + ylab("") + xlab("") +
theme_void()
grid.arrange(p1,p2,p3, nrow=3, ncol=1)
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