如何最小化r中直方图上的间距

假设我有两种数据。一个在小范围内（从0到0.5），另一个在大范围内（从4到600）。第一个称为

v

，第二个称为

mx

data<-structure(list(v = c(0.0741993337844943, 0.0469609897824665, 
0.27686789382899, 0.0899877689865293, 0.0533351613571831, 0.0949535942113873, 
0.132267448969788, 0.140736814439988, 0.170258755089611, 0.0012874981224646, 
0.0167425549755457), mx = c(20.2159112302004, 15.2656614271742, 
14.4361762323113, 8.87425807502441, 4.04997522826475, 34.9314254746675, 
45.699439750261, 16.0238858355385, 79.4436180395085, 598.247400459265, 
5.16677793308584)), class = "data.frame", row.names = c(NA, -11L
))

例如，

v

图上没有介于0.0和0.1之间的值。我想给这个差距增加更多的值，比如0.01，0.02。。。对于另一个图，我想添加更多的值，比如0-10-20-30…200-210

简言之，我想最小化所有具有不同范围的图的所有间隙

data<-structure(list(v = c(0.0741993337844943, 0.0469609897824665, 0.27686789382899, 0.0899877689865293, 0.0533351613571831, 0.0949535942113873,  0.132267448969788, 0.140736814439988, 0.170258755089611, 0.0012874981224646, 0.0167425549755457),
                     mx = c(20.2159112302004, 15.2656614271742, 14.4361762323113, 8.87425807502441, 4.04997522826475, 34.9314254746675, 45.699439750261, 16.0238858355385, 79.4436180395085, 598.247400459265, 5.16677793308584)),
                class = "data.frame", row.names = c(NA, -11L))


library(ggplot2)    
ggplot(data, aes(x=data$v)) + geom_histogram(bins=10)
ggplot(data, aes(x=data$mx)) + geom_histogram(bins=10)

---

也许：

ggplot（data，aes（x=v））+geom_直方图（binwidth=0.01）

？不确定您想要实现什么：您的

数据在图表中根本不包含任何空白值-也许
geom_density（）
在视觉上更接近您想要实现的目标。您还可以添加
scale_x_log10（）
为了减小间隙，请注意这可能会使轴更难理解。
data<-structure(list(v = c(0.0741993337844943, 0.0469609897824665, 0.27686789382899, 0.0899877689865293, 0.0533351613571831, 0.0949535942113873,  0.132267448969788, 0.140736814439988, 0.170258755089611, 0.0012874981224646, 0.0167425549755457),
                     mx = c(20.2159112302004, 15.2656614271742, 14.4361762323113, 8.87425807502441, 4.04997522826475, 34.9314254746675, 45.699439750261, 16.0238858355385, 79.4436180395085, 598.247400459265, 5.16677793308584)),
                class = "data.frame", row.names = c(NA, -11L))


library(ggplot2)    
ggplot(data, aes(x=data$v)) + geom_histogram(bins=10)
ggplot(data, aes(x=data$mx)) + geom_histogram(bins=10)

ggplot(data, aes(x=data$v)) + geom_histogram(binwidth=0.01)

ggplot(data, aes(x=data$mx)) + geom_histogram(binwidth=10)