19. 峰峦图绘制
清除当前环境中的变量
rm(list=ls())
设置工作目录
setwd("C:/Users/Dell/Desktop/R_Plots/19ridge/")
使用ggridges包绘制峰峦图
library(ggridges)
library(ggplot2)
##
## Attaching package: 'ggplot2'
## The following object is masked from 'package:ggridges':
##
## scale_discrete_manual
# 查看示例数据
head(iris)
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
# 使用geom_density_ridgesh函数绘制峰峦图
ggplot(iris, aes(x=Sepal.Length, y=Species, fill=Species)) +
geom_density_ridges()
image.png
# 设置分面
ggplot(iris, aes(x = Sepal.Length, y = Species)) +
geom_density_ridges(scale = 1) +
facet_wrap(~Species)
image.png
# 添加jitter散点
ggplot(iris, aes(x=Sepal.Length, y=Species)) +
geom_density_ridges(jittered_points = TRUE) +
theme_ridges()
image.png
# 更改散点的位置
ggplot(iris, aes(x=Sepal.Length, y=Species, fill=Species)) +
geom_density_ridges(
jittered_points = TRUE,
position = "raincloud",
alpha = 0.8, scale = 0.5
)
image.png
# 设置散点的大小和颜色
ggplot(iris, aes(x = Sepal.Length, y = Species, fill = Species)) +
geom_density_ridges(
aes(point_shape = Species, point_fill = Species, point_size = Petal.Length),
alpha = .2, point_alpha = 1, jittered_points = TRUE
) +
scale_point_color_hue(l = 40) +
scale_point_size_continuous(range = c(0.5, 4)) +
scale_discrete_manual(aesthetics = "point_shape", values = c(21, 22, 23))
image.png
library(viridis)
## Loading required package: viridisLite
head(lincoln_weather)
## # A tibble: 6 x 24
## CST `Max Temperatur~ `Mean Temperatu~ `Min Temperatur~ `Max Dew Point ~
## <chr> <int> <int> <int> <int>
## 1 2016~ 37 24 11 19
## 2 2016~ 41 23 5 22
## 3 2016~ 37 23 8 23
## 4 2016~ 30 17 4 24
## 5 2016~ 38 29 19 29
## 6 2016~ 34 33 32 33
## # ... with 19 more variables: `Mean Dew Point [F]` <int>, `Min Dewpoint
## # [F]` <int>, `Max Humidity` <int>, `Mean Humidity` <int>, `Min
## # Humidity` <int>, `Max Sea Level Pressure [In]` <dbl>, `Mean Sea Level
## # Pressure [In]` <dbl>, `Min Sea Level Pressure [In]` <dbl>, `Max
## # Visibility [Miles]` <int>, `Mean Visibility [Miles]` <int>, `Min
## # Visibility [Miles]` <int>, `Max Wind Speed [MPH]` <int>, `Mean Wind
## # Speed[MPH]` <int>, `Max Gust Speed [MPH]` <int>, `Precipitation
## # [In]` <chr>, CloudCover <int>, Events <chr>, `WindDir
## # [Degrees]` <int>, Month <fct>
ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = `Month`, fill = ..x..)) +
geom_density_ridges_gradient(scale = 3, rel_min_height = 0.01, gradient_lwd = 1.) +
scale_x_continuous(expand = c(0.01, 0)) +
scale_y_discrete(expand = c(0.01, 0)) +
scale_fill_viridis(name = "Temp. [F]", option = "C") +
labs(
title = 'Temperatures in Lincoln NE',
subtitle = 'Mean temperatures (Fahrenheit) by month for 2016\nData: Original CSV from the Weather Underground'
) +
theme_ridges(font_size = 13, grid = TRUE) + theme(axis.title.y = element_blank())
image.png
sessionInfo()
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 18363)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936
## [2] LC_CTYPE=Chinese (Simplified)_China.936
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C
## [5] LC_TIME=Chinese (Simplified)_China.936
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] viridis_0.5.1 viridisLite_0.3.0 ggplot2_3.2.0 ggridges_0.5.1
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.5 pillar_1.4.2 compiler_3.6.0 plyr_1.8.4
## [5] tools_3.6.0 digest_0.6.20 evaluate_0.14 tibble_2.1.3
## [9] gtable_0.3.0 pkgconfig_2.0.2 rlang_0.4.7 cli_1.1.0
## [13] yaml_2.2.0 xfun_0.8 gridExtra_2.3 withr_2.1.2
## [17] dplyr_0.8.3 stringr_1.4.0 knitr_1.23 vctrs_0.3.2
## [21] grid_3.6.0 tidyselect_0.2.5 glue_1.3.1 R6_2.4.0
## [25] fansi_0.4.0 rmarkdown_1.13 purrr_0.3.2 magrittr_1.5
## [29] scales_1.0.0 htmltools_0.3.6 assertthat_0.2.1 colorspace_1.4-1
## [33] labeling_0.3 utf8_1.1.4 stringi_1.4.3 lazyeval_0.2.2
## [37] munsell_0.5.0 crayon_1.3.4
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