我想在图的y轴上自定义间隙(断裂)。我尝试了两种选择。
option1: ylim(0.0,0.6)
option2: scale_y_continuous(breaks=seq(0.0, 0.6, 0.1))
option1的问题在于它每0.2中断一次,直到y轴的极限为0.6。option2的问题在于,由于它扩大了图的0.1段,因此它给出了图之间的巨大差异的幻觉。
我想要的是y轴每隔0.1断裂一次,或者将其自定义为任意断裂,同时显示y轴的最大限制(在本例中为0.0到0.6,但每隔0.1断裂)。
xVal = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15)
a = c(0.18340368127959822, 0.17496531617798133, 0.16772886654445848, 0.15934821062512169, 0.15390913489444036, 0.14578798884106348, 0.14524174121702108, 0.13958093302847951, 0.1365009715515553, 0.13337340345559975, 0.12995175856952607, 0.12583603207983862, 0.12180656145228715, 0.11824179486798418, 0.11524630600365712)
b = c(0.13544353787855531, 0.11345498050033079, 0.11449834060237293, 0.10479213576778054, 0.09677430524414686, 0.091990671548439179, 0.089965934807318487, 0.088711600335474206, 0.088923403079789909, 0.087989321310275717, 0.085424600757017272, 0.08251334730889931, 0.080178280060313953, 0.077717041621392688, 0.076638743116633837)
c = c(0.087351324973658093, 0.12113308515702567, 0.11422800742900453, 0.11264309199970789, 0.11390287790920843, 0.10774426268894192, 0.10587704437111881, 0.10474954948318291, 0.10568277685778472, 0.10201545270338952, 0.09939827283775747, 0.098062403381144761, 0.094110034623398231, 0.091211408116407641, 0.089369778116029489)
library(ggplot2)
library(reshape2)
df = data.frame(xVal, a, b, c)
df.melt = melt(df, id="xVal")
问题1:
ggplot(data=df.melt, aes(x=xVal, y=value, colour=variable)) +
geom_point() +
geom_line() +
xlab("xVal") + ylab("YValues") + xlim(1,16) +
ylim(0.0,0.6)
问题2:
ggplot(data=df.melt, aes(x=xVal, y=value, colour=variable)) +
geom_point() +
geom_line() +
xlab("xVal") + ylab("YValues") + xlim(1,16) +
scale_y_continuous(breaks=seq(0.0, 0.6, 0.1))
如何自定义y轴,以便根据我指定的值断开。
见下文。您需要同时设置休息时间和限制。否则,您可能不喜欢选择的休息时间,否则它可能会放大数据并且不显示某些休息时间。
library(ggplot2)
library(reshape2)
xVal = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15)
a = c(0.18340368127959822, 0.17496531617798133, 0.16772886654445848, 0.15934821062512169, 0.15390913489444036, 0.14578798884106348, 0.14524174121702108, 0.13958093302847951, 0.1365009715515553, 0.13337340345559975, 0.12995175856952607, 0.12583603207983862, 0.12180656145228715, 0.11824179486798418, 0.11524630600365712)
b = c(0.13544353787855531, 0.11345498050033079, 0.11449834060237293, 0.10479213576778054, 0.09677430524414686, 0.091990671548439179, 0.089965934807318487, 0.088711600335474206, 0.088923403079789909, 0.087989321310275717, 0.085424600757017272, 0.08251334730889931, 0.080178280060313953, 0.077717041621392688, 0.076638743116633837)
c = c(0.087351324973658093, 0.12113308515702567, 0.11422800742900453, 0.11264309199970789, 0.11390287790920843, 0.10774426268894192, 0.10587704437111881, 0.10474954948318291, 0.10568277685778472, 0.10201545270338952, 0.09939827283775747, 0.098062403381144761, 0.094110034623398231, 0.091211408116407641, 0.089369778116029489)
df = data.frame(xVal, a, b, c)
df.melt = melt(df, id="xVal")
ggplot(data=df.melt,
aes(x=xVal, y=value, colour=variable)) + geom_point() +
geom_line() + xlab("xVal") + ylab("YValues") + xlim(1,16) + scale_y_continuous(breaks=seq(0.0, 0.6, 0.1), limits=c(0, 0.6))
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