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ggpubr包系列学习教程(二)

2018-08-27  本文已影响35人  Davey1220

使用gghistogram函数绘制直方图


# 加载ggpubr包

library(ggpubr)

基本用法:

Usage

gghistogram(data, x, y = "..count..", combine = FALSE, merge = FALSE,

            color = "black", fill = NA, palette = NULL, size = NULL,

            linetype = "solid", alpha = 0.5, bins = NULL, binwidth = NULL,

            title = NULL, xlab = NULL, ylab = NULL, facet.by = NULL,

            panel.labs = NULL, short.panel.labs = TRUE, 

            add = c("none", "mean", "median"), add.params = list(linetype = "dashed"), rug = FALSE,

            add_density = FALSE, label = NULL, font.label = list(size = 11, color = "black"), 

            label.select = NULL, repel = FALSE, label.rectangle = FALSE,

            ggtheme = theme_pubr(), ...)

常用参数:

Arguments

data  #所需数据框 a data frame.

x  #所需数据 variable to be drawn.

y  #设置为密度或count数,默认为count one of "..density.." or "..count..".

combine  #对于多类型数据是否分面 logical value. Default is FALSE. Used only when y is a vector containing multiple variables to plot. If TRUE, create a multi-panel plot by combining the plot of y variables.

merge  #对于对类型数据是否合并 logical or character value. Default is FALSE. Used only when y is a vector containing multiple variables to plot. If TRUE, merge multiple y variables in the same plotting area. Allowed values include also "asis" (TRUE) and "flip". If merge = "flip", then y variables are used as x tick labels and the x variable is used as grouping variable.

color, fill  #线条颜色与填充色 histogram line color and fill color.

palette  #自定义颜色画板 the color palette to be used for coloring or filling by groups. Allowed values include "grey" for grey color palettes; brewer palettes e.g. "RdBu", "Blues", ...; or custom color palette e.g. c("blue", "red"); and scientific journal palettes from ggsci R package, e.g.: "npg", "aaas", "lancet", "jco", "ucscgb", "uchicago", "simpsons" and "rickandmorty".

size  #大小 Numeric value (e.g.: size = 1). change the size of points and outlines.

linetype  #线条类型 line type. See show_line_types.

alpha  #透明度设置 numeric value specifying fill color transparency. Value should be in [0, 1], where 0 is full transparency and 1 is no transparency.

bins  #bin的个数 Number of bins. Defaults to 30.

binwidth  #bin的宽度 numeric value specifying bin width. use value between 0 and 1 when you have a strong dense dotplot. For example binwidth = 0.2.

title  #设置标题 plot main title.

xlab  #设置x轴标题 character vector specifying x axis labels. Use xlab = FALSE to hide xlab.

ylab  #设置y轴标题character vector specifying y axis labels. Use ylab = FALSE to hide ylab.

facet.by  #设置分组分面 character vector, of length 1 or 2, specifying grouping variables for faceting the plot into multiple panels. Should be in the data.

panel.labs  #设置分面各组的标题 a list of one or two character vectors to modify facet panel labels. For example, panel.labs = list(sex = c("Male", "Female")) specifies the labels for the "sex" variable. For two grouping variables, you can use for example panel.labs = list(sex = c("Male", "Female"), rx = c("Obs", "Lev", "Lev2") ).

short.panel.labs  #logical value. Default is TRUE. If TRUE, create short labels for panels by omitting variable names; in other words panels will be labelled only by variable grouping levels.

add  #添加均值或中位数线 allowed values are one of "mean" or "median" (for adding mean or median line, respectively).

add.params  #添加其他参数 parameters (color, size, linetype) for the argument 'add'; e.g.: add.params = list(color = "red").

rug  #是否添加边际线 logical value. If TRUE, add marginal rug.

add_density  #是否添加密度曲线 logical value. If TRUE, add density curves.

label  #设置列标签 the name of the column containing point labels. Can be also a character vector with length = nrow(data).

font.label  #设置标签字体 a list which can contain the combination of the following elements: the size (e.g.: 14), the style (e.g.: "plain", "bold", "italic", "bold.italic") and the color (e.g.: "red") of labels. For example font.label = list(size = 14, face = "bold", color ="red"). To specify only the size and the style, use font.label = list(size = 14, face = "plain").

repel  #是否避字体免重叠 a logical value, whether to use ggrepel to avoid overplotting text labels or not.

label.rectangle  #是否给标签添加方框 logical value. If TRUE, add rectangle underneath the text, making it easier to read.

ggtheme  #设置画图主题 function, ggplot2 theme name. Default value is theme_pubr(). Allowed values include ggplot2 official themes: theme_gray(), theme_bw(), theme_minimal(), theme_classic(), theme_void(), ....

...  #设置其他参数 other arguments to be passed to geom_histogram and ggpar.

使用示例

Examples

# Create some data format

set.seed(1234)

wdata = data.frame(

  sex = factor(rep(c("F", "M"), each=200)),

  weight = c(rnorm(200, 55), rnorm(200, 58)))

head(wdata, 4)

##  sex  weight

## 1  F 53.79293

## 2  F 55.27743

## 3  F 56.08444

## 4  F 52.65430

# Basic density plot

# Add mean line and marginal rug 添加均值线和边际线

p1 <- gghistogram(wdata, x = "weight", fill = "lightgray",

            add ="mean", rug = TRUE)

p1


p1

# Change outline colors by groups ("sex") 设置分组颜色

# Use custom color palette

p2 <- gghistogram(wdata, x = "weight",

            add ="mean", rug = TRUE,

            color ="sex", palette = c("#00AFBB", "#E7B800"))

p2

p2

# Change outline and fill colors by groups ("sex")

# Use custom color palette

p3 <- gghistogram(wdata, x = "weight",

            add ="mean", rug = TRUE,

            color ="sex", fill = "sex",

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

p3

p3

# Combine histogram and density plots 添加密度曲线

p4 <- gghistogram(wdata, x = "weight",

            add ="mean", rug = TRUE,

            fill ="sex", palette = c("#00AFBB", "#E7B800"),

            add_density =TRUE)

p4

p4

p5 <- gghistogram(wdata, x = "weight", y = "..density..",

                  add ="mean", rug = TRUE,

                  fill ="sex", palette = c("#00AFBB", "#E7B800"),

                  add_density =TRUE)

p5

p5

# 设置分组分面和分面的标题

p6 <- gghistogram(wdata, x = "weight", facet.by = "sex",

                  add ="mean", rug = TRUE,

                  fill ="sex", palette = c("#00AFBB", "#E7B800"),

                  add_density =TRUE)

p6

p6

p7 <- gghistogram(wdata, x = "weight", facet.by = "sex", panel.labs = list(sex = c("Female", "Mmale")),

                  add ="mean", rug = TRUE,

                  fill ="sex", palette = c("#00AFBB", "#E7B800"),

                  add_density =TRUE)

p7

p7

sessionInfo()

## R version 3.5.1 (2018-07-02)

## Platform: x86_64-apple-darwin15.6.0 (64-bit)

## Running under: OS X El Capitan 10.11.3

## 

## Matrix products: default

## BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib

## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

## 

## locale:

## [1] zh_CN.UTF-8/zh_CN.UTF-8/zh_CN.UTF-8/C/zh_CN.UTF-8/zh_CN.UTF-8

## 

## attached base packages:

## [1] stats    graphics  grDevices utils    datasets  methods  base     

## 

## other attached packages:

## [1] ggpubr_0.1.7.999 magrittr_1.5    ggplot2_3.0.0   

## 

## loaded via a namespace (and not attached):

##  [1] Rcpp_0.12.18    rstudioapi_0.7  bindr_0.1.1      knitr_1.20     

##  [5] tidyselect_0.2.4 munsell_0.5.0    colorspace_1.3-2 R6_2.2.2       

##  [9] rlang_0.2.2      stringr_1.3.1    plyr_1.8.4      dplyr_0.7.6     

## [13] tools_3.5.1      grid_3.5.1      gtable_0.2.0    withr_2.1.2     

## [17] htmltools_0.3.6  assertthat_0.2.0 yaml_2.2.0      lazyeval_0.2.1 

## [21] rprojroot_1.3-2  digest_0.6.16    tibble_1.4.2    crayon_1.3.4   

## [25] bindrcpp_0.2.2  purrr_0.2.5      glue_1.3.0      evaluate_0.11   

## [29] rmarkdown_1.10  labeling_0.3    stringi_1.2.4    compiler_3.5.1 

## [33] pillar_1.3.0    scales_1.0.0    backports_1.1.2  pkgconfig_2.0.2

参考来源:https://www.rdocumentation.org/packages/ggpubr/versions/0.1.4/topics/gghistogram

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