Visual 2 - Histogram

# Basic Histogram

good.choices <- c(.43, .47, .47, .48, .50, .52, .53, .53, .54, .54, .54, .54, .55, .55, .55, .56, .56, .57, .57, .57, .57, .58, .58, .58, .59, .59, .60, .62, .63, .63, .64, .64, .66, .66, .67, .67, .68, .70, .70)
par(cex.main = 1.5, mar = c(5, 6, 4, 5) + 0.1, mgp = c(3.5, 1, 0), cex.lab = 1.5 , font.lab = 2, cex.axis = 1.3, bty = "n", las=1)
hist(good.choices, main = "", xlab = "", ylab = " ", ylim = c(0, 13), xlim = c(.30, .80), axes = FALSE, col = "grey")
axis(1, seq(.30, .80, by = .1))
axis(2, seq(.00, 12, by = 2))
rug(jitter(good.choices))
mtext("Prop. Choices from Good Decks", side = 1, line = 2.5, cex = 1.5, font = 2)
mtext("Number of Studies", side = 2, line = 3, cex = 1.5, font = 2, las = 0)


# Include a density estimator

lines(density(good.choices), lwd = 2)

# Include Numbers on Top

yhigh <- 8
h <- hist(good.choices, freq = FALSE, main = "", xlab = "", ylab = " ", ylim = c(0, yhigh), xlim = c(0.3, 0.8), axes = FALSE, col = "grey")
l_ply(seq_along(h$density), function(x) text(h$mids[x], h$density[x] + 0.32, round(h$density[x], 2), cex = 1.2))
axis(1, seq(0.3, 0.8, by = 0.1))
axis(2, labels = FALSE, lwd.ticks = 0)
rug(jitter(good.choices))
mtext("Prop. Choices from Good Decks", side = 1, line = 2.5, cex = 1.5, font = 2)
mtext("Density of Studies", side = 2, line = 1, cex = 1.5, font = 2, las = 0)

## Select most recent 16 week data;

colsToSum <- names(data)[-1]
thisyear <- data[, lapply(.SD, sum, na.rm=TRUE), .SDcols=colsToSum]

## Column sum

data2=data.table(style=colnames(thisyear), cnt=unlist(thisyear))[order(cnt)]
data2$rowid=1:nrow(data2)
data2$style=str_replace_all(data2$style, "_", " ")
data2$style=factor(data2$style, levels=data2$style)
data2$scalecnt=round(100*data2$cnt/max(data2$cnt))


ggplot(data2, aes(y=scalecnt, x=style)) +
geom_bar(stat="identity", fill="blue") +
coord_flip() +
ggtitle("Total Search Index from 4/10/2016 to 7/24/2016 ") +
ylab("Search Volume Index") +
xlab("Style") +
theme(plot.title = element_text(face = "bold", size = 10)) +
theme(axis.text.x = element_text(face = "bold", size = 10)) +
theme(axis.text.y = element_text(face = "bold", size = 10)) +
theme(axis.title.x = element_text(face = "bold", size = 10)) +
theme(axis.title.y = element_text(face = "bold", size = 10, angle=90))

colsToSum <- names(data)[-1]
thisyear <- data[, lapply(.SD, sum, na.rm=TRUE), .SDcols=colsToSum]
## Column sum
data2=data.table(style=colnames(thisyear), cnt=unlist(thisyear))[order(cnt)]
data2$rowid=1:nrow(data2)
data2$style=str_replace_all(data2$style, "_", " ")
data2$style=factor(data2$style, levels=data2$style)
data2$scalecnt=round(100*data2$cnt/max(data2$cnt))

ggplot(data2, aes(y=scalecnt, x=style)) +
  geom_bar(stat="identity", fill="blue") +
  coord_flip() +
  ggtitle("Total Search Index from 4/10/2016 to 7/24/2016 ") +
  ylab("Search Volume Index") +
  xlab("Style") +
  theme(plot.title = element_text(face = "bold", size = 10)) +
  theme(axis.text.x = element_text(face = "bold", size = 10)) +
  theme(axis.text.y = element_text(face = "bold", size = 10)) +
  theme(axis.title.x = element_text(face = "bold", size = 10)) +
  theme(axis.title.y = element_text(face = "bold", size = 10, angle=90))