使用ggline函数绘制线图
加载所需R包
library(ggpubr)
基本用法：
Usage
ggline(data, x, y, group = 1, combine = FALSE, merge = FALSE,
color = "black", palette = NULL, linetype = "solid",
plot_type = c("b", "l", "p"), size = 0.5, shape = 19,
point.size = size, point.color = color, title = NULL, xlab = NULL,
ylab = NULL, facet.by = NULL, panel.labs = NULL,
short.panel.labs = TRUE, select = NULL, remove = NULL, order = NULL,
add = "none", add.params = list(), error.plot = "errorbar",
label = NULL, font.label = list(size = 11, color = "black"),
label.select = NULL, repel = FALSE, label.rectangle = FALSE,
show.line.label = FALSE, ggtheme = theme_pubr(), ...)
常用参数：
Arguments
data #a data frame
x, y #x and y variables for drawing.
group #分组变量 grouping variable to connect points by line. Allowed values are 1 (for one line, one group) or a character vector specifying the name of the grouping variable (case of multiple lines).
combine #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 #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 #line colors.
palette #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".
linetype #line type.
plot_type #绘图类型 plot type. Allowed values are one of "b" for both line and point; "l" for line only; and "p" for point only. Default is "b".
size #Numeric value (e.g.: size = 1). change the size of points and outlines.
shape #point shapes.
point.size #point size.
point.color #point color.
title #plot main title.
xlab #character vector specifying x axis labels. Use xlab = FALSE to hide xlab.
ylab #character vector specifying y axis labels. Use ylab = FALSE to hide ylab.
facet.by #character vector, of length 1 or 2, specifying grouping variables for faceting the plot into multiple panels. Should be in the data.
panel.labs #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.
select #character vector specifying which items to display.
remove #character vector specifying which items to remove from the plot.
order #character vector specifying the order of items.
add #character vector for adding another plot element (e.g.: dot plot or error bars). Allowed values are one or the combination of: "none", "dotplot", "jitter", "boxplot", "point", "mean", "mean_se", "mean_sd", "mean_ci", "mean_range", "median", "median_iqr", "median_mad", "median_range"; see ?desc_statby for more details.
add.params #parameters (color, shape, size, fill, linetype) for the argument 'add'; e.g.: add.params = list(color = "red").
error.plot #添加误差棒 plot type used to visualize error. Allowed values are one of c("pointrange", "linerange", "crossbar", "errorbar", "upper_errorbar", "lower_errorbar", "upper_pointrange", "lower_pointrange", "upper_linerange", "lower_linerange"). Default value is "pointrange" or "errorbar". Used only when add != "none" and add contains one "mean_*" or "med_*" where "*" = sd, se, ....
label #the name of the column containing point labels. Can be also a character vector with length = nrow(data).
font.label #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 #a logical value, whether to use ggrepel to avoid overplotting text labels or not.
label.rectangle #logical value. If TRUE, add rectangle underneath the text, making it easier to read.
show.line.label #logical value. If TRUE, shows line labels.
ggtheme #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()
... #other arguments to be passed to geom_dotplot.
使用示例
# 构建数据框
df <- data.frame(dose=c("D0.5", "D1", "D2"),
len=c(4.2, 10, 29.5))
head(df)
## dose len
## 1 D0.5 4.2
## 2 D1 10.0
## 3 D2 29.5
# Basic plot
p1 <- ggline(df, x = "dose", y = "len")
p1
p1
# Plot with multiple groups
# Create some data
df2 <- data.frame(supp=rep(c("VC", "OJ"), each=3),
dose=rep(c("D0.5", "D1", "D2"),2),
len=c(6.8, 15, 33, 4.2, 10, 29.5))
print(df2)
## supp dose len
## 1 VC D0.5 6.8
## 2 VC D1 15.0
## 3 VC D2 33.0
## 4 OJ D0.5 4.2
## 5 OJ D1 10.0
## 6 OJ D2 29.5
# Plot "len" by "dose" and
# Change line types and point shapes by a second groups: "supp"
p2 <- ggline(df2, "dose", "len",
linetype = "supp", shape = "supp")
p2
p2
# Change colors
# Change color by group: "supp"
# Use custom color palette
p3 <- ggline(df2, "dose", "len",
linetype = "supp", shape = "supp",
color = "supp", palette = c("#00AFBB", "#E7B800"))
p3
p3
# Add points and errors
# Data: ToothGrowth data set we'll be used.
df3 <- ToothGrowth
head(df3, 10)
## len supp dose
## 1 4.2 VC 0.5
## 2 11.5 VC 0.5
## 3 7.3 VC 0.5
## 4 5.8 VC 0.5
## 5 6.4 VC 0.5
## 6 10.0 VC 0.5
## 7 11.2 VC 0.5
## 8 11.2 VC 0.5
## 9 5.2 VC 0.5
## 10 7.0 VC 0.5
# It can be seen that for each group we have
# different values
p4 <- ggline(df3, x = "dose", y = "len")
p4
p4
# Visualize the mean of each group
p5 <- ggline(df3, x = "dose", y = "len",
add = "mean")
p5
p5
# Add error bars: mean_se
# (other values include: mean_sd, mean_ci, median_iqr, ....)
p6 <- ggline(df3, x = "dose", y = "len", add = "mean_se")
p6
p6
# Change error.plot to "pointrange"
p7 <- ggline(df3, x = "dose", y = "len",
add = "mean_se", error.plot = "pointrange")
p7
p7
# Add jitter points and errors (mean_se)
p8 <- ggline(df3, x = "dose", y = "len",
add = c("mean_se", "jitter"))
p8
p8
# Add dot and errors (mean_se)
p9 <- ggline(df3, x = "dose", y = "len",
add = c("mean_se", "dotplot"), color = "steelblue")
p9
p9
# Add violin and errors (mean_se)
p10 <- ggline(df3, x = "dose", y = "len",
add = c("mean_se", "violin"), color = "steelblue")
p10
p10
# Multiple groups with error bars
p11 <- ggline(df3, x = "dose", y = "len", color = "supp",
add = "mean_se", palette = c("#00AFBB", "#E7B800"))
p11
p11
# Add jitter
p12 <- ggline(df3, x = "dose", y = "len", color = "supp",
add = c("mean_se", "jitter"), palette = c("#00AFBB", "#E7B800"))
p12
p12
# Add dot plot
p13 <- ggline(df3, x = "dose", y = "len", color = "supp",
add = c("mean_se", "dotplot"), palette = c("#00AFBB", "#E7B800"))
p13
p13
参考来源：
https://www.rdocumentation.org/packages/ggpubr/versions/0.1.4/topics/ggline
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
