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library(ggplot2)
library(gcookbook)
library(plyr)
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summary(pg_mean)
str(pg_mean)
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ggplot(data = pg_mean, aes(x = group, y = weight)) + geom_bar(stat = "identity")
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str(BOD)
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ggplot(data = BOD, aes(x = Time, y = demand)) + geom_bar(stat = "identity")
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ggplot(data = BOD, aes(x = factor(Time), y = demand)) + geom_bar(stat = "identity")
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x <- factor(BOD$Time, ordered = TRUE)
str(x)
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ggplot(data = pg_mean, aes(x = group, y = weight)) + geom_bar(stat = "identity", fill = "lightblue", colour = "black")
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cabbage_exp
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ggplot(data = cabbage_exp, aes(x = Date, y = Weight, fill = Cultivar)) + geom_bar(stat = "identity", position = "dodge")
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ggplot(data = cabbage_exp, aes(x = Date, y = Weight, fill = Cultivar))+
geom_bar(stat = "identity", position = "dodge", colour = "black") + scale_fill_brewer(palette = "Pastel1")
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str(diamonds)
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ggplot(data = diamonds, aes(x = cut)) + geom_bar()
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ggplot(data = diamonds, aes(x = carat)) + geom_bar()
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upc <- subset(uspopchange, rank(Change) > 40)
upc
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rank(uspopchange$Change)
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ggplot(data = upc, aes(x = Abb, y = Change, fill = Region)) + geom_bar(stat = "identity")
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ggplot(data = upc, aes(x = reorder(Abb, Change), y = Change, fill = Region)) +
geom_bar(stat = "identity", colour = "black") +
scale_fill_manual(values = c("#669933", "#FFCC66")) +
xlab("State")
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csub <- subset(climate, Source == "Berkeley" & Year >= 1900)
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# str(csub)
tail(csub)
csub$pos <- csub$Anomaly10y >= 0
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ggplot(data = csub, aes(x = Year, y = Anomaly10y, fill = pos)) + geom_bar(stat = "identity", position = "identity")
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ggplot(data = csub, aes(x = Year, y = Anomaly10y, fill = pos)) +
geom_bar(stat = "identity", position = "identity", colour = "black", size = 0.25) +
scale_fill_manual(values = c("#669933", "#FFCC66"), guide = FALSE)
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summary(pg_mean)
str(pg_mean)
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ggplot(data = pg_mean, aes(x = group, y = weight)) + geom_bar(stat = "identity")
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ggplot(data = pg_mean, aes(x = group, y = weight)) + geom_bar(stat = "identity", width = 1)
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ggplot(data = pg_mean, aes(x = group, y = weight)) + geom_bar(stat = "identity", width = 0.5)
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ggplot(data = cabbage_exp, aes(x = Date, y = Weight, fill = Cultivar)) +
geom_bar(stat = "identity", width = 0.5, position = "dodge")
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ggplot(data = cabbage_exp, aes(x = Date, y = Weight, fill = Cultivar)) +
geom_bar(stat = "identity", width = 0.5, position = position_dodge(0.7))
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ggplot(data = cabbage_exp, aes(x = Date, y = Weight, fill = Cultivar)) +
geom_bar(stat = "identity")
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ggplot(data = cabbage_exp, aes(x = Date, y = Weight, fill = Cultivar)) +
geom_bar(stat = "identity") +
guides(fill = guide_legend(reverse = TRUE))
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ggplot(data = cabbage_exp, aes(x = Date, y = Weight, fill = Cultivar, order = desc(Cultivar))) +
geom_bar(stat = "identity")
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str(cabbage_exp$Cultivar)
cabbage_exp$Cultivar
cultivar = factor(c("c39", "c39","c39", "c52","c52","c52"), levels = c("c52", "c39"))
cultivar
str(cultivar)
identical(cabbage_exp$Cultivar, cultivar)
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ce <- ddply(cabbage_exp, "Date", transform, percentage_weight = Weight / sum(Weight) * 100)
ce
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ggplot(data = ce, aes(x = Date, y = percentage_weight, fill = Cultivar)) +
geom_bar(stat = "identity", colour = "black") +
guides(fill = guide_legend(reverse = FALSE)) +
scale_fill_brewer(palette = "Pastel1")
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ggplot(data = cabbage_exp, aes(x = Date, y = Weight, fill = Cultivar)) +
geom_bar(stat = "identity", position = "dodge", colour = "black") +
geom_text(aes(y = Weight - 0.1, label = Weight), position = position_dodge(0.9), color = "white")
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ce <- arrange(cabbage_exp, Date, desc(Cultivar))
ce <- ddply(ce, "Date", transform, label_y = cumsum(Weight))
ce
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ggplot(data = ce, aes(x = Date, y = Weight, fill = Cultivar, order=desc(Cultivar))) +
geom_bar(stat = "identity", colour = "black") +
geom_text(aes(y = label_y - 0.1, label = Weight), color = "white")