### second plot: 2 colors, jagged lines ggplot(dat) + geom_line(aes(x = t, y = y)) + theme_bw() + theme(panel.grid = element_blank()) # ggsave("tmp/line1b.eps", device = "eps", # width = 6, height = 6) 在显示zoomed-in线的屏幕截图中,我们观察到第一个图中的线是平滑...
今天我介绍的这个R包,patternplot包可以很完美的解决这个应用,我想相信这回cover大部分人的需求,因为我们在R语言中做出这种线条区分的图形实在是太少了。 patternplot 包 安装R包,这个包依赖ggplot,还是很可以的,但是就是使用方法不是很ggplot,如果作者能够将这种方式继续进行改造,相信引用会很高的。目前这个包已经上...
Autoplot and fortify 读这个知识点参考卡片,可以检验你ggplot2语法的记忆程度。 sthda网站的ggplot核心图表示例 链接:http://www.sthda.com/english/wiki/ggplot2-essentials 书籍本身提供售卖,价格是17欧元,不过内容都是电子化了,大家直接网页浏览,就是免费的哈!
patternplot包,提供了丰度的图形可视化填充选项,但是目前我尽然没忽悠看到一篇推文来介绍和学习这个R包的。 大家都知道,柱状图我们在中文中常见填充的除了颜色,还有形状,用不同的线填充,区分不同分组,因为中文期刊彩色版面费贵一些,所以很多...
Plot one or several time series A time series is the visual representation of time-dependent data, this is, its a chart that represents the evolution of a variable through time. Generally, the pair of points are connected with lines and the decision of showing the points or not depends on...
问题是,当你在baseNULL对象(与ggplot不同,后者将返回一个plot对象)。 您可以直接在ggplot中绘制绘图(有几种方法可以这样做,但我已经做了一个简单的示例bolow)并用ggplotly转换它: p <- ggplot()+ geom_line(aes(x = r_fit$unique.death.times, y = t(pred[1,])), col = "red") + ...
Dumbbell Plot 哑铃图 1. Visualize relative positions (like growth and decline) between two points in time. 2. Compare distance between two categories.比较两类间距离 Y 变量应该是 a factor and the levels of the factor variable should be in the same order as it should appear in the plot. 1...
Lines over grouped bars It is possible to add lines over grouped bars. In this example, there are actually four lines (one for each entry forhline), but it looks like two, because they are drawn on top of each other. I don’t think it’s possible to avoid this, but it doesn’t...
(p1 <- p0 + labs(tag = "p1") + theme(plot.background = element_blank(), panel.background = element_blank(), panel.grid = element_blank(), legend.position = "none", axis.line = element_line(color = "black", linewidth = 0.4), axis.ticks.length = unit(-0.25 , "lines"), axi...
plot_f<- gene_expression%>% filter(gene=="CCR7")%>% ggplot(aes(x = group, y = expression, fill = group)) + geom_violin(trim = FALSE) + geom_boxplot(width=0.15)+ scale_fill_manual(values = c("G1" = "#66c2a5", "G2" = "#fc8d62", "G3" = "#8da0cb", "G4" = "...