R语言如何让数据更论文化

大家在给文章作图的时候是不是会感到很痛苦，不知道该怎么调色，也对图形样式的选择感到迷茫。今天给大家介绍一个具有强大功能的绘图R包ggpubr。它整合了目前基本流行的图形样式，包括箱线图、气泡图、柱状图、散点图、密度图、环状图、火山图甚至可以为你安排布局设计表格。

安装ggpubr很简单，但是需要注意的是要重新安装我们自带的rlang包，不然很多功能无法实现。

接下来我们介绍下它的具体绘图的函数：

1. ggtexttable 绘制表格。其中主要的参数是theme = ttheme(type)，其type的值包括c("default","blank", "classic", "minimal", "light","lBlack", "lBlue", "lRed", "lGreen","lViolet", "lCyan", "lOrange", "lBlackWhite","lBlueWhite", "lRedWhite", "lGreenWhite","lVioletWhite", "lCyanWhite", "lOrangeWhite","mBlack", "mBlue", "mRed", "mGreen","mViolet", "mCyan", "mOrange","mBlackWhite", "mBlueWhite", "mRedWhite","mGreenWhite", "mVioletWhite", "mCyanWhite","mOrangeWhite" ).以上的表格类型如果感兴趣可以自行去试试那个更好看。

我们举两个实例：

# data

df <- head(iris)

# Default table

# Remove row namesusing rows = NULL

ggtexttable(df, rows= NULL)

# Medium blue(mBlue) theme

ggtexttable(df, rows= NULL, theme = ttheme("mBlue"))

2. ggviolin绘制小提琴图，具体的参数如下：

其中：

orientation负责图形的方向。主要值c("vertical","horizontal", "reverse")。

draw_quantiles 分位数的设置。主要值：0.5，0.27，0.75.

add 添加元素。其值包括："none","dotplot", "jitter", "boxplot","point", "mean", "mean_se", "mean_sd","mean_ci", "mean_range", "median","median_iqr", "median_mad", "median_range"。

fill填充小提琴图。可以是各种颜色。

示例如下：

# Load data

data("ToothGrowth")

df <- ToothGrowth

# Basic plot

# +++++++++++++++++++++++++++

ggviolin(df, x ="dose", y = "len")

ggviolin(df, "dose", "len", add = "jitter",

   draw_quantiles = 0.5)

ggviolin(df,"dose", "len", fill = "dose",

palette = c("#00AFBB","#E7B800", "#FC4E07"),

add = "boxplot", add.params =list(fill = "white"))

ggviolin(df,"dose", "len", color = "supp",

palette = c("#00AFBB","#E7B800"), add = "boxplot")#子集的绘制

3. ggballoonplot气泡图的绘制。

其中主要的参数设置：

# Define color palette

my_cols <- c("#0D0887FF", "#6A00A8FF", "#B12A90FF",

"#E16462FF", "#FCA636FF", "#F0F921FF")

# Standard contingency table

#:::::::::::::::::::::::::::::::::::::::::::::::::::::::::

# Read a contingency table: housetasks

# Repartition of 13 housetasks in the couple

data <- read.delim(

  system.file("demo-data/housetasks.txt", package = "ggpubr"),

  row.names = 1

  )

data

# Basic ballon plot

ggballoonplot(data)

ggballoonplot(data, color = "#0073C2FF", fill = "#0073C2FF")

ggballoonplot(data, fill = "value",  shape = 23)+

  gradient_fill(c("blue", "white", "red"))

ggballoonplot(data, fill = "value", color = "lightgray",

              size = 10, show.label = TRUE)+

  gradient_fill(c("blue", "white", "red"))

data(HairEyeColor)

data= as.data.frame(HairEyeColor)

ggballoonplot(data,x= "Hair", y = "Eye", size = "Freq",ggtheme =theme_gray()) %>%facet("Sex")#其中facet主要分组的依据

4. ggpaired 配对的散点图绘制。

#::::::::::::::::::::::::::::::::::::::::::

before <-c(200.1, 190.9, 192.7, 213, 241.4, 196.9, 172.2, 185.5, 205.2, 193.7)

after <-c(392.9, 393.2, 345.1, 393, 434, 427.9, 422, 383.9, 392.3, 352.2)

d <- data.frame(before = before, after = after)

ggpaired(d, cond1 = "before", cond2 = "after",

    fill = "condition", palette = "jco")

ggpaired(d, cond1 ="before", cond2 = "after",

fill = "condition", palette ="npg", line.color = "gray", line.size = 0.4)

以上是这个包的主要绘图函数，其他的我们实现的途径很多，我就不一一进行演示了。