R-ggplot2 package Examples
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This document provides various examples of using the ggplot2 package in R for data visualization, including creating dot plots, box plots, and histograms with different datasets such as student data and diamonds. It includes code snippets for visualizing data based on specific attributes, applying faceting, and modifying themes. References to additional resources and materials on ggplot2 are also included.
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morph <- read.csv("Morph_for_Sato.csv")
names(morph) <- tolower(names(morph)) # make columns names lowercase
morph <- subset(morph, islandid == "Flor_Chrl") # take only one island morph <-
morph[,c("taxonorig", "sex", "wingl", "beakh", "ubeakl")] # only keep these
names(morph)[1] <- "taxon" morph <- data.frame(na.omit(morph)) # remove all rows
morph$taxon <- factor(morph$taxon) # remove extra remaining factor levels
morph$sex <- factor(morph$sex) # remove extra remaining factor levels
row.names(morph)
ggplot(morph, aes(taxon, wingl)) + geom_boxplot() + coord_flip()
Ref: http://seananderson.ca/ggplot2-FISH554/](https://image.slidesharecdn.com/ggplot2examples-161020200648/85/R-ggplot2-package-Examples-14-320.jpg)
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library("dplyr")
> morph_quant <-
morph %>%
+ group_by(taxon) %>%
+ summarise(
+ l = quantile(wingl, 0.25)[[1]],
+ m = median(wingl),
+ u = quantile(wingl, 0.75)[[1]]) %>%
+ # re-order factor levels by median for plotting:
+ mutate(taxon = reorder(taxon, m, function(x) x))
>ggplot(morph_quant, aes(x = taxon, y = m, ymin = l, ymax = u)) +
geom_pointrange() + coord_flip() + ylab("Wing length") + xlab("")
Ref: http://seananderson.ca/ggplot2-FISH554/](https://image.slidesharecdn.com/ggplot2examples-161020200648/85/R-ggplot2-package-Examples-16-320.jpg)
R-ggplot2 package Examples
- 1. Prepared by Volkan OBAN ggplot2 Examples: 1- students = read.csv("student.csv") library(ggplot2) ggplot(students, aes(x = Height)) + geom_dotplot()
- 2. 2- ggplot(students, aes(x = Sex, y = Height)) + geom_boxplot() + coord_flip()
- 4. 4- ggplot(students,aes(x =Sleep)) +geom_dotplot(dotsize=0.4) + facet_grid(Level ~.)
- 5. 5- ggplot(students, aes(x = Major, y = MilesHome)) + geom_boxplot() + coord_fip()
- 6. qplot 6- qplot(color, price / carat, data = diamonds, geom = "jitter")
- 7. 7- qplot(color, price / carat, data = diamonds, geom = "boxplot")
- 8. 8- qplot(carat, data = diamonds, geom = "histogram", fill = color)
- 9. 9- >library(nlme) > data(Oxboys) > p <- ggplot(Oxboys, aes(age, height, group = Subject)) + + geom_line() > p > p + geom_smooth(aes(group = Subject), method="lm", se = F)
- 10. 10- depth_dist<- ggplot(diamonds,aes(depth)) +xlim(58,68) depth_dist+ geom_histogram(aes(y= ..density..),binwidth= 0.1) + facet_grid(cut~ .) depth_dist+ geom_histogram(aes(fill =cut), binwidth= 0.1, position= "fill") depth_dist+geom_freqpoly(aes(y=..density..,colour= cut), binwidth= 0.1) Reference: http://www.stat.wisc.edu/~larget/stat302/chap2.pdf Reference book: ggplot2 Elegant Graphics for Data Analysis; Wickham, Hadley
- 11. 11- > library("ggplot2") > library("ggthemes") > ggplot(diamonds, aes(x = clarity, fill = cut)) + geom_bar() + scale_fill_ptol() +theme_minimal()
- 12. 12- > dtemp <- data.frame(months = factor(rep(substr(month.name,1,3), 4), l evels = substr(month.name,1,3)), city = rep(c("Tokyo", "New York", "Berlin", "London"), each = 12), temp = c(7.0, 6.9, 9.5, 14.5, 18.2, 21.5, 25.2, 26.5, 23.3, 18.3, 13.9, 9.6 , -0.2, 0.8, 5.7, 11.3, 17.0, 22.0, 24.8, 24.1, 20.1, 14.1, 8.6, 2.5, -0.9, 0.6, 3.5, 8.4, 13.5, 17.0, 18.6, 17.9, 14.3, 9.0, 3.9, 1.0, 3.9, 4.2, 5.7, 8.5, 11.9, 15.2, 17.0, 16.6, 14.2, 10.3, 6.6, 4.8)) > ggplot(dtemp, aes(x = months, y = temp, group = city, color = city)) + geom_line() + geom_point(size = 1.1) + ggtitle("Monthly Average Temperature") + theme_hc() + scale_colour_hc() > ggplot(dtemp, aes(x = months, y = temp, group = city, color = city)) + geom_line() + geom_point(size = 1.1) + ggtitle("Monthly Average Temperature") + theme_hc(bgcolor = "darkunica") + scale_fill_hc("darkunica") Ref: https://cran.r-project.org/web/packages/ggthemes/vignettes/ggthemes.html
- 13. 13- > ppc <- ggplot(data = diamonds, aes(x = color, y = price/carat)) > ppc + geom_boxplot(aes(fill = color)) Ref:https://www3.nd.edu/~steve/computing_with_data/11_geom_examples/ggplot_examples.html
- 14. 14- morph <- read.csv("Morph_for_Sato.csv") names(morph) <- tolower(names(morph)) # make columns names lowercase morph <- subset(morph, islandid == "Flor_Chrl") # take only one island morph <- morph[,c("taxonorig", "sex", "wingl", "beakh", "ubeakl")] # only keep these names(morph)[1] <- "taxon" morph <- data.frame(na.omit(morph)) # remove all rows morph$taxon <- factor(morph$taxon) # remove extra remaining factor levels morph$sex <- factor(morph$sex) # remove extra remaining factor levels row.names(morph) ggplot(morph, aes(taxon, wingl)) + geom_boxplot() + coord_flip() Ref: http://seananderson.ca/ggplot2-FISH554/
- 15. 15- ggplot(morph, aes(sex, wingl)) + geom_violin() + facet_wrap(~taxon)
- 16. 16. library("dplyr") > morph_quant <- morph %>% + group_by(taxon) %>% + summarise( + l = quantile(wingl, 0.25)[[1]], + m = median(wingl), + u = quantile(wingl, 0.75)[[1]]) %>% + # re-order factor levels by median for plotting: + mutate(taxon = reorder(taxon, m, function(x) x)) >ggplot(morph_quant, aes(x = taxon, y = m, ymin = l, ymax = u)) + geom_pointrange() + coord_flip() + ylab("Wing length") + xlab("") Ref: http://seananderson.ca/ggplot2-FISH554/
- 17. 17- >library(ggplot2) > plot2 <- qplot(color, price/carat, data = diamonds, geom = "boxplot", col our = color) > plot2
- 18. 18- > library(GGally) > library(ggplot2) >data(tips, package = "reshape") > pm <- ggpairs(tips, mapping = aes(color = sex), columns = c("total_bill", "time", "tip")) > pm Ref: http://ggobi.github.io/ggally/docs.html#columns_and_mapping