用数据可视化之美逼死密集恐惧症

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