科技猎用数据可视化之美逼死密集恐惧症
作者：真依然很拉风
事情起因是这样的：在某个搞技群里有人发了一个11维的蜜汁微笑矩阵用来逼死密集恐惧症——
11*11蜜汁微笑矩阵
于是有人用一个[擦汗]的表情表示无语……
可是仅仅一个表情，怎么能以对等的气势怼回去呢？于是——
emoji = '[擦汗]' for i in range(11): print(emoji*(i+1))
11维下三角擦汗
不过考虑到这种方法只能把表情按离散整数的序列来放置，还不能在任意的连续数值处放表情。考虑到R中的ggimage包可以用图片来代替散点，于是一个思路就是画散点（曲线）图，然后用表情来代换散点。
然后，升级版的逼死密集恐惧症图形就新鲜出炉了——
正弦式笑哭
library(ggplot2) library(ggimage) showtext::showtext.auto(enable = T) theme1 <- theme(panel.background = element_rect(fill = "black",color = "black"),plot.background = element_rect(fill="black",color = "black"),panel.grid = element_blank(),plot.title = element_text(hjust=0.5,family = "SimHei",size = 24,color = "#FEFEFE"), axis.text = element_blank(),axis.ticks = element_blank()) # 正弦曲线 x <- seq(from=0,to=2*pi,length.out = 80) y <- sin(x) df_sin <- data.frame(x = x,y=y) ggplot(df_sin,aes(x,y))+ geom_emoji(aes(image='1f602'))+ labs(x= "",y="",title="正弦式笑哭")+ theme1
正弦式笑哭
逻辑回归式笑哭
# sigmoid曲线 sigmoid <- function(x) return(1/(1+exp(-x))) x <- seq(from=-10,to=10,length.out = 100) y <- sigmoid(x) df_sigmoide <- data.frame(x = x,y=y) ggplot(df_sigmoide,aes(x,y))+ geom_emoji(aes(image='1f602'))+ labs(x= "",y="",title="逻辑回归式笑哭")+ theme1
逻辑回归式笑哭
正态分布式笑哭
# 正态密度曲线 x <- seq(-5,5,length.out = 100) y <- dnorm(x) df_norm <- data.frame(x = x,y=y) ggplot(df_norm,aes(x,y))+ geom_emoji(aes(image='1f602'))+ labs(x= "",y="",title="正态分布式笑哭")+ theme1
正态分布式笑哭
爱心式笑哭
# 心形曲线 t <- seq(0,2*pi,length.out = 100) x <- 16*(sin(t)^3) y <- 13*cos(t) - 5*cos(2*t) - 2*cos(3*t)-cos(4*t) df_heart <- data.frame(x=x,y=y) ggplot(df_heart,aes(x=x,y=y))+ geom_emoji(aes(image='1f602'))+ labs(x= "",y="",title="爱心式笑哭")+ theme1
爱心式笑哭
众星捧月式笑哭
# 弧形 x <- seq(-10,10,length.out=40) r <- 10 y <- -sqrt(r^2-x^2) df_cirle <- data.frame(x = c(x,0), y = c(y,5),z=2) df_cirle$z[nrow(df_cirle)] <- 16 ggplot()+ geom_emoji(data=df_cirle,mapping=aes(x=x,y=y,image='1f602',size=z))+ scale_y_continuous(limits = c(-10,12))+ scale_size_area(max_size = 0.3)+ labs(x= "",y="",title="众星捧月式笑哭")+ guides(size=F)+ theme1
众星捧月式笑哭
囧式笑器
x <- seq(-10,10,length.out = 100) y <- 2/(x^2-2) shift <- 3 x1 <- rep(seq(min(x)-shift,max(x)+shift,length.out = 150),2) y1 <- c(rep(min(y)-shift,150),rep(max(y)+shift,150)) x2 <- c(rep(min(x)-shift,150),rep(max(x)+shift,150)) y2 <- rep(seq(min(y)-shift,max(y)+shift,length.out = 150),2) df_orz <- data.frame(x=c(x,x1,x2),y=c(y,y1,y2)) ggplot(df_orz,aes(x=x,y=y))+ geom_emoji(aes(image='1f602'))+ labs(x= "",y="",title="囧式笑哭")+ theme1
囧式笑哭
金拱门式笑哭
# 金拱门 x <- seq(0,2*pi,length.out = 100) y <- abs(sin(x)) df_m <- data.frame(x=x,y=y) ggplot(df_m,aes(x=x,y=y))+ geom_emoji(aes(image='1f602'))+ labs(x= "",y="",title="金拱门式笑哭")+ theme1
金拱门式笑哭
四叶草式笑哭
# 四叶草 x <- seq(0,2*pi,length.out = 100) y <- cos(4*x) df_flower <- data.frame(x=x,y=y) ggplot(df_flower,aes(x,y))+ geom_line()+ geom_emoji(aes(image='1f602'))+ coord_polar()+ labs(x= "",y="",title="四叶草式笑哭")+ theme1
四叶草式笑哭
万花筒式笑哭
# 万花筒式笑哭
get_circle <- function(r){
t <- seq(-r,r,length.out = 50*sqrt(r))
x <- rep(t,2)
y <- c(sqrt(r^2-t^2),-sqrt(r^2-t^2))
df <- data.frame(x=x,y=y)
return(df)
}
df_circle <- data.frame(x=NULL,y=NULL)
layer <- 11
for(i in 1:layer){
df_circle <- rbind(df_circle,get_circle(i))
}
ggplot()+
geom_emoji(data = df_circle,aes(x,y,image='1f602'))+
scale_x_continuous(limits = c(-layer,layer))+
labs(x= "",y="",title="万花筒式笑哭")+
theme1
11阶万花筒式笑哭，是不是比矩阵不知道高到哪去了
无招胜有招式笑哭
# 无招胜有招式笑哭 x <- rnorm(10000,mean=0,sd=10) y <- rnorm(10000,mean = 0,sd=10) df_norm <- data.frame(x=x,y=y) ggplot(data = df_norm,mapping = aes(x,y,image='1f602'))+ geom_emoji()+ labs(x= "",y="",title="无招胜有招式笑哭")+ theme1
无招胜有招式笑哭
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