Visualization 1
library(ggplot2)
library(RColorBrewer)
data(diamonds)
diamonds$cut <- paste("Super Dee-Duper",as.character(diamonds$cut))
q <- qplot(cut,carat,data=diamonds,geom="boxplot")+theme_bw()
q + theme(axis.text.x = element_text(angle = 90, hjust = 1))+
theme(axis.text=element_text(size=16), axis.title=element_text(size=16))
### SOURCE: http://stackoverflow.com/questions/1330989/rotating-and-spacing-axis-labels-in-ggplot2
Visualization 2
stock <- "MSFT"
start.date <- "2006-01-12"
end.date <- Sys.Date()
quote <- paste("http://ichart.finance.yahoo.com/table.csv?s=",
stock, "&a=", substr(start.date,6,7),
"&b=", substr(start.date, 9, 10),
"&c=", substr(start.date, 1,4),
"&d=", substr(end.date,6,7),
"&e=", substr(end.date, 9, 10),
"&f=", substr(end.date, 1,4),
"&g=d&ignore=.csv", sep="")
stock.data <- read.csv(quote, as.is=TRUE)
stock.data <- transform(stock.data,
week = as.POSIXlt(Date)$yday %/% 7 + 1,
wday = as.POSIXlt(Date)$wday,
year = as.POSIXlt(Date)$year + 1900)
library(ggplot2)
ggplot(stock.data, aes(week, wday, fill = Adj.Close)) +theme_bw()+
geom_tile(colour = "white") + theme(axis.text=element_text(size=18), axis.title=element_text(size=18))+
scale_fill_gradientn(colours = c("#D61818","#FFAE63","#FFFFBD","#B5E384")) +
facet_wrap(~ year, ncol = 1)
#### SOURCE: http://stackoverflow.com/questions/2076370/most-underused-data-visualization
Visualization 3
library("reshape2")
library("ggplot2")
test_data <- data.frame(
var0 = 100 + c(0, cumsum(runif(49, -20, 20))),
var1 = 150 + c(0, cumsum(runif(49, -10, 10))),
date = seq.Date(as.Date("2002-01-01"), by="1 month", length.out=100))
test_data_long <- melt(test_data, id="date") # convert to long format
ggplot(data=test_data_long,
aes(x=date, y=value, colour=variable)) +theme_bw()+
geom_line(size=2)+ theme(axis.text=element_text(size=16), axis.title=element_text(size=18))
#### SOURCE: http://stackoverflow.com/questions/3777174/plotting-two-variables-as-lines-using-ggplot2-on-the-same-graph
Visualization 4
x<-rnorm(300)
y<-rt(300,df=10)
xy<-data.frame(x,y)
scatter <- qplot(x,y, data=xy) + theme_bw()+
scale_x_continuous(limits=c(min(x),max(x))) +
scale_y_continuous(limits=c(min(y),max(y))) +
geom_rug(col=rgb(.5,0,0,alpha=.2))
scatter
### SOURCE: http://stackoverflow.com/questions/8545035/scatterplot-with-marginal-histograms-in-ggplot2
Visualization 5
df <- data.frame(x=rep(1:10,2), y=c(1:10,11:20),
group=c(rep("a",10),rep("b",10)))
head(df)
## x y group
## 1 1 1 a
## 2 2 2 a
## 3 3 3 a
## 4 4 4 a
## 5 5 5 a
## 6 6 6 a
g <- ggplot(df, aes(x = x, y = y, group = group))+theme_bw()+
geom_line(size=2)+ theme(axis.text=element_text(size=16), axis.title=element_text(size=18))
g <- g + geom_line(aes(colour = group), size=1.2)
g <- g + geom_point(aes(colour = group), alpha = 0.8)
g
### SOURCE: http://stackoverflow.com/questions/11714951/remove-extra-legends-in-ggplot2
Visualization 6
## State BCmort year eastWest
## 1 BW 16.5 2010 west
## 2 BY 16.6 2010 west
## 3 BE 15.0 2010 east
## 4 BB 14.4 2010 east
## 5 HB 13.5 2010 west
## 6 HH 17.1 2010 west
ggplot(mort3, aes(x = year, y = BCmort, col = State, linetype = State)) +
geom_line(size=1.4)+
theme(axis.text=element_text(size=16), axis.title=element_text(size=16))+
scale_linetype_manual(values = c(rep("solid", 10), rep("dashed", 6))) +
scale_x_continuous(breaks=c(1998:2010))+
scale_color_manual(values = c(brewer.pal(10, "Set3"), brewer.pal(6, "Set3"))) +
theme_bw()
### SOURCE; http://stackoverflow.com/questions/11344561/controlling-line-color-and-line-type-in-ggplot-legend
Visualization 7
library(ggplot2)
library(plyr)
library(arm)
## Warning: package 'arm' was built under R version 3.2.3
## Loading required package: MASS
## Loading required package: Matrix
## Loading required package: lme4
##
## arm (Version 1.8-6, built: 2015-7-7)
##
## Working directory is C:/Users/s-das/Syncplicity Folders/Private/Rpubs1/FEB/4_ggplot2_so1
library(reshape2)
nba <- read.csv("http://datasets.flowingdata.com/ppg2008.csv")
head(nba)
## Name G MIN PTS FGM FGA FGP FTM FTA FTP X3PM X3PA
## 1 Dwyane Wade 79 38.6 30.2 10.8 22.0 0.491 7.5 9.8 0.765 1.1 3.5
## 2 LeBron James 81 37.7 28.4 9.7 19.9 0.489 7.3 9.4 0.780 1.6 4.7
## 3 Kobe Bryant 82 36.2 26.8 9.8 20.9 0.467 5.9 6.9 0.856 1.4 4.1
## 4 Dirk Nowitzki 81 37.7 25.9 9.6 20.0 0.479 6.0 6.7 0.890 0.8 2.1
## 5 Danny Granger 67 36.2 25.8 8.5 19.1 0.447 6.0 6.9 0.878 2.7 6.7
## 6 Kevin Durant 74 39.0 25.3 8.9 18.8 0.476 6.1 7.1 0.863 1.3 3.1
## X3PP ORB DRB TRB AST STL BLK TO PF
## 1 0.317 1.1 3.9 5.0 7.5 2.2 1.3 3.4 2.3
## 2 0.344 1.3 6.3 7.6 7.2 1.7 1.1 3.0 1.7
## 3 0.351 1.1 4.1 5.2 4.9 1.5 0.5 2.6 2.3
## 4 0.359 1.1 7.3 8.4 2.4 0.8 0.8 1.9 2.2
## 5 0.404 0.7 4.4 5.1 2.7 1.0 1.4 2.5 3.1
## 6 0.422 1.0 5.5 6.5 2.8 1.3 0.7 3.0 1.8
nba$Name <- with(nba, reorder(Name, PTS))
nba.m <- melt(nba)
## Using Name as id variables
nba.m <- ddply(nba.m, .(variable), transform,
rescale = rescale(value))
(p <- ggplot(nba.m, aes(variable, Name)) + geom_tile(aes(fill = rescale),
colour = "white") + scale_fill_gradient(low = "white",
high = "steelblue")+geom_text(aes(label=round(rescale,1))))
### SOURCE: http://stackoverflow.com/questions/3081066/what-techniques-exists-in-r-to-visualize-a-distance-matrix