像这样绘制 correlation-matrix 情节的最佳方法是什么？
What´s the best way to do a correlation-matrix plot like this?
我使用 ggpairs 生成了这个图：
这是它的代码：
#load packages
library("ggplot2")
library("GGally")
library("plyr")
library("dplyr")
library("reshape2")
library("tidyr")
#generate example data
dat <- data.frame(replicate(6, sample(1:5, 100, replace=TRUE)))
dat[,1]<-as.numeric(dat[,1])
dat[,2]<-as.numeric(dat[,2])
dat[,3]<-as.numeric(dat[,3])
dat[,4]<-as.numeric(dat[,4])
dat[,5]<-as.numeric(dat[,5])
dat[,6]<-as.numeric(dat[,6])
#ggpairs-plot
main<-ggpairs(data=dat,
lower=list(continuous="smooth", params=c(colour="blue")),
diag=list(continuous="bar", params=c(colour="blue")),
upper=list(continuous="cor",params=c(size = 6)),
axisLabels='show',
title="correlation-matrix",
columnLabels = c("Item 1", "Item 2", "Item 3","Item 4", "Item 5", "Item 6")) + theme_bw() +
theme(legend.position = "none",
panel.grid.major = element_blank(),
axis.ticks = element_blank(),
panel.border = element_rect(linetype = "dashed", colour = "black", fill = NA))
main
然而，我的目标是，得到这样的情节：
这个情节是一个例子，我用以下三个ggplot-codes.
制作了它
我将其用于 geom_point 情节：
#------------------------
#lower / geom_point with jitter
#------------------------
#dataframe
df.point <- na.omit(data.frame(cbind(x=dat[,1], y=dat[,2])))
#plot
scatter <- ggplot(df.point,aes(x, y)) +
geom_jitter(position = position_jitter(width = .25, height= .25)) +
stat_smooth(method="lm", colour="black") +
theme_bw() +
scale_x_continuous(labels=NULL, breaks = NULL) +
scale_y_continuous(labels=NULL, breaks = NULL) +
xlab("") +ylab("")
scatter
这给出了以下情节：
我将其用于条形图：
#-------------------------
#diag. / BARCHART
#------------------------
bar.df<-as.data.frame(table(dat[,1],useNA="no"))
#Barplot
bar<-ggplot(bar.df) + geom_bar(aes(x=Var1,y=Freq),stat="identity") +
theme_bw() +
scale_x_discrete(labels=NULL, breaks = NULL) +
scale_y_continuous(labels=NULL, breaks = NULL, limits=c(0,max(bar.df$Freq*1.05))) +
xlab("") +ylab("")
bar
这给出了以下情节：
我将它用于 Correlation-Coefficients:
#----------------------
#upper / geom_tile and geom_text
#------------------------
#correlations
df<-na.omit(dat)
df <- as.data.frame((cor(df[1:ncol(df)])))
df <- data.frame(row=rownames(df),df)
rownames(df) <- NULL
#Tile to plot (as example)
test<-as.data.frame(cbind(1,1,df[2,2])) #F09_a x F09_b
colnames(test)<-c("x","y","var")
#Plot
tile<-ggplot(test,aes(x=x,y=y)) +
geom_tile(aes(fill=var)) +
geom_text(data=test,aes(x=1,y=1,label=round(var,2)),colour="White",size=10,show_guide=FALSE) +
theme_bw() +
scale_y_continuous(labels=NULL, breaks = NULL) +
scale_x_continuous(labels=NULL, breaks = NULL) +
xlab("") +ylab("") + theme(legend.position = "none")
tile
这给出了以下情节：
我的问题是：
获得我想要的情节的最佳方式是什么？我想从问卷中形象化 likert-items，在我看来，这是一种非常好的方法。
是否可以为此使用 ggpairs 而无需自己生成每个图，就像我对自定义 ggpairs-plot 所做的那样。或者还有其他方法吗？
我不知道这是不是最好的方法，它肯定不会更容易，但这会生成三个图列表：条形图、散点图和图块各一个。使用 gtable 函数，它创建一个 gtable 布局，将绘图添加到布局中，然后进行一些微调。
编辑： 将 t 和 p.values 添加到图块。
# Load packages
library(ggplot2)
library(plyr)
library(gtable)
library(grid)
# Generate example data
dat <- data.frame(replicate(10, sample(1:5, 200, replace = TRUE)))
dat = dat[, 1:6]
dat <- as.data.frame(llply(dat, as.numeric))
# Number of items, generate labels, and set size of text for correlations and item labels
n <- dim(dat)[2]
labels <- paste0("Item ", 1:n)
sizeItem = 16
sizeCor = 4
## List of scatterplots
scatter <- list()
for (i in 2:n) {
for (j in 1:(i-1)) {
# Data frame
df.point <- na.omit(data.frame(cbind(x = dat[ , j], y = dat[ , i])))
# Plot
p <- ggplot(df.point, aes(x, y)) +
geom_jitter(size = .7, position = position_jitter(width = .2, height= .2)) +
stat_smooth(method="lm", colour="black") +
theme_bw() + theme(panel.grid = element_blank())
name <- paste0("Item", j, i)
scatter[[name]] <- p
} }
## List of bar plots
bar <- list()
for(i in 1:n) {
# Data frame
bar.df <- as.data.frame(table(dat[ , i], useNA = "no"))
names(bar.df) <- c("x", "y")
# Plot
p <- ggplot(bar.df) +
geom_bar(aes(x = x, y = y), stat = "identity", width = 0.6) +
theme_bw() + theme(panel.grid = element_blank()) +
ylim(0, max(bar.df$y*1.05))
name <- paste0("Item", i)
bar[[name]] <- p
}
## List of tiles
tile <- list()
for (i in 1:(n-1)) {
for (j in (i+1):n) {
# Data frame
df.point <- na.omit(data.frame(cbind(x = dat[ , j], y = dat[ , i])))
x = df.point[, 1]
y = df.point[, 2]
correlation = cor.test(x, y)
cor <- data.frame(estimate = correlation$estimate,
statistic = correlation$statistic,
p.value = correlation$p.value)
cor$cor = paste0("r = ", sprintf("%.2f", cor$estimate), "\n",
"t = ", sprintf("%.2f", cor$statistic), "\n",
"p = ", sprintf("%.3f", cor$p.value))
# Plot
p <- ggplot(cor, aes(x = 1, y = 1)) +
geom_tile(fill = "steelblue") +
geom_text(aes(x = 1, y = 1, label = cor),
colour = "White", size = sizeCor, show_guide = FALSE) +
theme_bw() + theme(panel.grid = element_blank())
name <- paste0("Item", j, i)
tile[[name]] <- p
} }
# Convert the ggplots to grobs,
# and select only the plot panels
barGrob <- llply(bar, ggplotGrob)
barGrob <- llply(barGrob, gtable_filter, "panel")
scatterGrob <- llply(scatter, ggplotGrob)
scatterGrob <- llply(scatterGrob, gtable_filter, "panel")
tileGrob <- llply(tile, ggplotGrob)
tileGrob <- llply(tileGrob, gtable_filter, "panel")
## Set up the gtable layout
gt <- gtable(unit(rep(1, n), "null"), unit(rep(1, n), "null"))
## Add the plots to the layout
# Bar plots along the diagonal
for(i in 1:n) {
gt <- gtable_add_grob(gt, barGrob[[i]], t=i, l=i)
}
# Scatterplots in the lower half
k <- 1
for (i in 2:n) {
for (j in 1:(i-1)) {
gt <- gtable_add_grob(gt, scatterGrob[[k]], t=i, l=j)
k <- k+1
} }
# Tiles in the upper half
k <- 1
for (i in 1:(n-1)) {
for (j in (i+1):n) {
gt <- gtable_add_grob(gt, tileGrob[[k]], t=i, l=j)
k <- k+1
} }
# Add item labels
gt <- gtable_add_cols(gt, unit(1.5, "lines"), 0)
gt <- gtable_add_rows(gt, unit(1.5, "lines"), 2*n)
for(i in 1:n) {
textGrob <- textGrob(labels[i], gp = gpar(fontsize = sizeItem))
gt <- gtable_add_grob(gt, textGrob, t=n+1, l=i+1)
}
for(i in 1:n) {
textGrob <- textGrob(labels[i], rot = 90, gp = gpar(fontsize = sizeItem))
gt <- gtable_add_grob(gt, textGrob, t=i, l=1)
}
# Add small gap between the panels
for(i in n:1) gt <- gtable_add_cols(gt, unit(0.2, "lines"), i)
for(i in (n-1):1) gt <- gtable_add_rows(gt, unit(0.2, "lines"), i)
# Add chart title
gt <- gtable_add_rows(gt, unit(1.5, "lines"), 0)
textGrob <- textGrob("Korrelationsmatrix", gp = gpar(fontface = "bold", fontsize = 16))
gt <- gtable_add_grob(gt, textGrob, t=1, l=3, r=2*n+1)
# Add margins to the whole plot
for(i in c(2*n+1, 0)) {
gt <- gtable_add_cols(gt, unit(.75, "lines"), i)
gt <- gtable_add_rows(gt, unit(.75, "lines"), i)
}
# Draw it
grid.newpage()
grid.draw(gt)
我使用 ggpairs 生成了这个图：
这是它的代码：
#load packages
library("ggplot2")
library("GGally")
library("plyr")
library("dplyr")
library("reshape2")
library("tidyr")
#generate example data
dat <- data.frame(replicate(6, sample(1:5, 100, replace=TRUE)))
dat[,1]<-as.numeric(dat[,1])
dat[,2]<-as.numeric(dat[,2])
dat[,3]<-as.numeric(dat[,3])
dat[,4]<-as.numeric(dat[,4])
dat[,5]<-as.numeric(dat[,5])
dat[,6]<-as.numeric(dat[,6])
#ggpairs-plot
main<-ggpairs(data=dat,
lower=list(continuous="smooth", params=c(colour="blue")),
diag=list(continuous="bar", params=c(colour="blue")),
upper=list(continuous="cor",params=c(size = 6)),
axisLabels='show',
title="correlation-matrix",
columnLabels = c("Item 1", "Item 2", "Item 3","Item 4", "Item 5", "Item 6")) + theme_bw() +
theme(legend.position = "none",
panel.grid.major = element_blank(),
axis.ticks = element_blank(),
panel.border = element_rect(linetype = "dashed", colour = "black", fill = NA))
main
然而，我的目标是，得到这样的情节：
这个情节是一个例子，我用以下三个ggplot-codes.
制作了它我将其用于 geom_point 情节：
#------------------------
#lower / geom_point with jitter
#------------------------
#dataframe
df.point <- na.omit(data.frame(cbind(x=dat[,1], y=dat[,2])))
#plot
scatter <- ggplot(df.point,aes(x, y)) +
geom_jitter(position = position_jitter(width = .25, height= .25)) +
stat_smooth(method="lm", colour="black") +
theme_bw() +
scale_x_continuous(labels=NULL, breaks = NULL) +
scale_y_continuous(labels=NULL, breaks = NULL) +
xlab("") +ylab("")
scatter
这给出了以下情节：
我将其用于条形图：
#-------------------------
#diag. / BARCHART
#------------------------
bar.df<-as.data.frame(table(dat[,1],useNA="no"))
#Barplot
bar<-ggplot(bar.df) + geom_bar(aes(x=Var1,y=Freq),stat="identity") +
theme_bw() +
scale_x_discrete(labels=NULL, breaks = NULL) +
scale_y_continuous(labels=NULL, breaks = NULL, limits=c(0,max(bar.df$Freq*1.05))) +
xlab("") +ylab("")
bar
这给出了以下情节：
我将它用于 Correlation-Coefficients:
#----------------------
#upper / geom_tile and geom_text
#------------------------
#correlations
df<-na.omit(dat)
df <- as.data.frame((cor(df[1:ncol(df)])))
df <- data.frame(row=rownames(df),df)
rownames(df) <- NULL
#Tile to plot (as example)
test<-as.data.frame(cbind(1,1,df[2,2])) #F09_a x F09_b
colnames(test)<-c("x","y","var")
#Plot
tile<-ggplot(test,aes(x=x,y=y)) +
geom_tile(aes(fill=var)) +
geom_text(data=test,aes(x=1,y=1,label=round(var,2)),colour="White",size=10,show_guide=FALSE) +
theme_bw() +
scale_y_continuous(labels=NULL, breaks = NULL) +
scale_x_continuous(labels=NULL, breaks = NULL) +
xlab("") +ylab("") + theme(legend.position = "none")
tile
这给出了以下情节：
我的问题是： 获得我想要的情节的最佳方式是什么？我想从问卷中形象化 likert-items，在我看来，这是一种非常好的方法。 是否可以为此使用 ggpairs 而无需自己生成每个图，就像我对自定义 ggpairs-plot 所做的那样。或者还有其他方法吗？
我不知道这是不是最好的方法，它肯定不会更容易，但这会生成三个图列表：条形图、散点图和图块各一个。使用 gtable 函数，它创建一个 gtable 布局，将绘图添加到布局中，然后进行一些微调。
编辑： 将 t 和 p.values 添加到图块。
# Load packages
library(ggplot2)
library(plyr)
library(gtable)
library(grid)
# Generate example data
dat <- data.frame(replicate(10, sample(1:5, 200, replace = TRUE)))
dat = dat[, 1:6]
dat <- as.data.frame(llply(dat, as.numeric))
# Number of items, generate labels, and set size of text for correlations and item labels
n <- dim(dat)[2]
labels <- paste0("Item ", 1:n)
sizeItem = 16
sizeCor = 4
## List of scatterplots
scatter <- list()
for (i in 2:n) {
for (j in 1:(i-1)) {
# Data frame
df.point <- na.omit(data.frame(cbind(x = dat[ , j], y = dat[ , i])))
# Plot
p <- ggplot(df.point, aes(x, y)) +
geom_jitter(size = .7, position = position_jitter(width = .2, height= .2)) +
stat_smooth(method="lm", colour="black") +
theme_bw() + theme(panel.grid = element_blank())
name <- paste0("Item", j, i)
scatter[[name]] <- p
} }
## List of bar plots
bar <- list()
for(i in 1:n) {
# Data frame
bar.df <- as.data.frame(table(dat[ , i], useNA = "no"))
names(bar.df) <- c("x", "y")
# Plot
p <- ggplot(bar.df) +
geom_bar(aes(x = x, y = y), stat = "identity", width = 0.6) +
theme_bw() + theme(panel.grid = element_blank()) +
ylim(0, max(bar.df$y*1.05))
name <- paste0("Item", i)
bar[[name]] <- p
}
## List of tiles
tile <- list()
for (i in 1:(n-1)) {
for (j in (i+1):n) {
# Data frame
df.point <- na.omit(data.frame(cbind(x = dat[ , j], y = dat[ , i])))
x = df.point[, 1]
y = df.point[, 2]
correlation = cor.test(x, y)
cor <- data.frame(estimate = correlation$estimate,
statistic = correlation$statistic,
p.value = correlation$p.value)
cor$cor = paste0("r = ", sprintf("%.2f", cor$estimate), "\n",
"t = ", sprintf("%.2f", cor$statistic), "\n",
"p = ", sprintf("%.3f", cor$p.value))
# Plot
p <- ggplot(cor, aes(x = 1, y = 1)) +
geom_tile(fill = "steelblue") +
geom_text(aes(x = 1, y = 1, label = cor),
colour = "White", size = sizeCor, show_guide = FALSE) +
theme_bw() + theme(panel.grid = element_blank())
name <- paste0("Item", j, i)
tile[[name]] <- p
} }
# Convert the ggplots to grobs,
# and select only the plot panels
barGrob <- llply(bar, ggplotGrob)
barGrob <- llply(barGrob, gtable_filter, "panel")
scatterGrob <- llply(scatter, ggplotGrob)
scatterGrob <- llply(scatterGrob, gtable_filter, "panel")
tileGrob <- llply(tile, ggplotGrob)
tileGrob <- llply(tileGrob, gtable_filter, "panel")
## Set up the gtable layout
gt <- gtable(unit(rep(1, n), "null"), unit(rep(1, n), "null"))
## Add the plots to the layout
# Bar plots along the diagonal
for(i in 1:n) {
gt <- gtable_add_grob(gt, barGrob[[i]], t=i, l=i)
}
# Scatterplots in the lower half
k <- 1
for (i in 2:n) {
for (j in 1:(i-1)) {
gt <- gtable_add_grob(gt, scatterGrob[[k]], t=i, l=j)
k <- k+1
} }
# Tiles in the upper half
k <- 1
for (i in 1:(n-1)) {
for (j in (i+1):n) {
gt <- gtable_add_grob(gt, tileGrob[[k]], t=i, l=j)
k <- k+1
} }
# Add item labels
gt <- gtable_add_cols(gt, unit(1.5, "lines"), 0)
gt <- gtable_add_rows(gt, unit(1.5, "lines"), 2*n)
for(i in 1:n) {
textGrob <- textGrob(labels[i], gp = gpar(fontsize = sizeItem))
gt <- gtable_add_grob(gt, textGrob, t=n+1, l=i+1)
}
for(i in 1:n) {
textGrob <- textGrob(labels[i], rot = 90, gp = gpar(fontsize = sizeItem))
gt <- gtable_add_grob(gt, textGrob, t=i, l=1)
}
# Add small gap between the panels
for(i in n:1) gt <- gtable_add_cols(gt, unit(0.2, "lines"), i)
for(i in (n-1):1) gt <- gtable_add_rows(gt, unit(0.2, "lines"), i)
# Add chart title
gt <- gtable_add_rows(gt, unit(1.5, "lines"), 0)
textGrob <- textGrob("Korrelationsmatrix", gp = gpar(fontface = "bold", fontsize = 16))
gt <- gtable_add_grob(gt, textGrob, t=1, l=3, r=2*n+1)
# Add margins to the whole plot
for(i in c(2*n+1, 0)) {
gt <- gtable_add_cols(gt, unit(.75, "lines"), i)
gt <- gtable_add_rows(gt, unit(.75, "lines"), i)
}
# Draw it
grid.newpage()
grid.draw(gt)