英文:
Plot multiple variable on y axis in R using ggplot
问题
我是新手使用R，但有一些Matlab的经验。我正在尝试在一个图表上制作三种不同区域测量值的比较图，按动物模型的基因型进行分面。我想要按基因型（Control和Cre-）来绘制Glom.Area、Glom.Tuft和Mesangial.Area。
我的代码如下：
# 设置环境library(tidyverse)library(ggbeeswarm)library(readxl)# 工作目录setwd("C:/Users/k_nic/OneDrive/Desktop")# 读取CSV文件t1 <- read.csv("sample.csv", header = TRUE)# 绘制一个变量的图表ggplot(t1, aes(x = Genotype, y = Glom.Area))
数据集：
Genotype Sex Glom.Area Glom.Tuft Mesangial.Area1 Control M 6617.669 3804.877 1917.3102 Control M 7986.696 5377.977 2761.9493 Control M 8617.410 4443.345 2335.2444 Control M 7785.355 4307.021 2381.5125 Control M 9159.720 5568.449 3163.2326 Control M 8484.327 5314.041 3238.8617 Control M 10315.521 6105.294 3429.9068 Control M 5517.161 3090.970 1878.2889 Cre- M 6075.166 3438.421 2147.75810 Cre- M 8947.698 5809.953 3744.11711 Cre- M 6677.471 4315.344 2113.50212 Cre- M 7616.932 4293.291 2763.79113 Cre- M 8191.464 4778.529 2159.00714 Cre- M 8549.339 6043.961 2922.29515 Cre- M 11057.196 6546.740 3771.89116 Cre- M 5911.768 3382.556 1754.674
我希望它看起来类似于以下图表：
非常感谢任何帮助！
英文:
I am new to R but have some experience with matlab. I am trying to make comparison plots between three different area measurements on one graph faceted by genotype of animal model. I would like to plot Glom.Area, Glom.Tuft, and Mesangial.Area faceted by genotype (control v Cre -).
My code so far:
# Setuplibrary(tidyverse)library(ggbeeswarm)library(readxl)# work spacesetwd("C:/Users/k_nic/OneDrive/Desktop")# Read in csv filet1 <- read.csv("sample.csv", header = TRUE)# plot for one varibleggplot(t1, aes(x = Genotype, y= Glom.Area))
Dataset:
Genotype Sex Glom.Area Glom.Tuft Mesangial.Area1 Control M 6617.669 3804.877 1917.3102 Control M 7986.696 5377.977 2761.9493 Control M 8617.410 4443.345 2335.2444 Control M 7785.355 4307.021 2381.5125 Control M 9159.720 5568.449 3163.2326 Control M 8484.327 5314.041 3238.8617 Control M 10315.521 6105.294 3429.9068 Control M 5517.161 3090.970 1878.2889 Cre- M 6075.166 3438.421 2147.75810 Cre- M 8947.698 5809.953 3744.11711 Cre- M 6677.471 4315.344 2113.50212 Cre- M 7616.932 4293.291 2763.79113 Cre- M 8191.464 4778.529 2159.00714 Cre- M 8549.339 6043.961 2922.29515 Cre- M 11057.196 6546.740 3771.89116 Cre- M 5911.768 3382.556 1754.674
This is what I would like it to look something like:
Any help is greatly appreciated!
答案1
得分: 0
在这种方法中，我们将三个测量转化为长格式的数据。我们将测量名称映射到 x 轴，相应的数值映射到 y 轴。将基因型映射到填充美观度会产生一对列。``` rlibrary(tidyverse)df %>%pivot_longer(c(Glom.Area, Glom.Tuft, Mesangial.Area)) %>%ggplot(aes(name, value, fill = Genotype)) +geom_col(position = position_dodge())
创建于2023年06月15日，使用 reprex v2.0.2
<details><summary>英文:</summary>In this approach, we pivot the three measurements into long-form data. We map the measurement names to the x-axis and their respective values along the y. Mapping the Genotypes to the fill aesthetic yields the pairs of columns.``` rlibrary(tidyverse)df %>%pivot_longer(c(Glom.Area, Glom.Tuft, Mesangial.Area)) %>%ggplot(aes(name, value, fill = Genotype)) +geom_col(position = position_dodge())
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<sup>Created on 2023-06-15 with reprex v2.0.2</sup>
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