长期以来画图最折磨人的莫过于颜色的选择，一张图往往在颜色选择上都要耗费我不少的时间，正好自己最近有大型配色需求索性将R中的颜色代码一并整理分享给大家，希望对各位小伙伴有所帮助
viridis 连续型调色板
这个配色我常用于热图的绘制
install.packages("viridis")
viridis使用案例
scale_fill_viridis(option="magma")中写入调色板名称即可
library(viridis)
unemp <- read.csv("http://datasets.flowingdata.com/unemployment09.csv",
header = FALSE, stringsAsFactors = FALSE)
names(unemp) <- c("id", "state_fips", "county_fips", "name", "year",
"?", "?", "?", "rate")
unemp$county <- tolower(gsub(" County, [A-Z]{2}", "", unemp$name))
unemp$county <- gsub("^(.*) parish, ..$","\\1", unemp$county)
unemp$state <- gsub("^.*([A-Z]{2}).*$", "\\1", unemp$name)
county_df <- map_data("county", projection = "albers", parameters = c(39, 45))
names(county_df) <- c("long", "lat", "group", "order", "state_name", "county")
county_df$state <- state.abb[match(county_df$state_name, tolower(state.name))]
county_df$state_name <- NULL
state_df <- map_data("state", projection = "albers", parameters = c(39, 45))
choropleth <- merge(county_df, unemp, by = c("state", "county"))
choropleth <- choropleth[order(choropleth$order), ]
ggplot(choropleth, aes(long, lat, group = group)) +
geom_polygon(aes(fill = rate), colour = alpha("white", 1 / 2), size = 0.2) +
geom_polygon(data = state_df, colour = "white", fill = NA) +
coord_fixed() +
theme_minimal() +
ggtitle("US unemployment rate by county") +
theme(axis.line = element_blank(), axis.text = element_blank(),
axis.ticks = element_blank(), axis.title = element_blank()) +
scale_fill_viridis(option="magma")
image
以下介绍的2种调色板多用于离散型数据，有了这麽多的颜色代码再也不用担心颜色不够用了，哈哈
wesanderson
devtools::install_github("karthik/wesanderson")
# CRAN version
install.packages("wesanderson")
image
wesanderson使用案例
只需要更换色条wes_palette("Zissou1")内名称即可
library(wesanderson)
library("ggplot2")
ggplot(mtcars, aes(factor(cyl), fill=factor(vs))) + geom_bar() +
scale_fill_manual(values = wes_palette("Zissou1"))
image
wesanderson 16进制颜色代码清单
wes_palettes <- list(
BottleRocket1 = c("#A42820", "#5F5647", "#9B110E", "#3F5151", "#4E2A1E", "#550307", "#0C1707"),
BottleRocket2 = c("#FAD510", "#CB2314", "#273046", "#354823", "#1E1E1E"),
Rushmore1 = c("#E1BD6D", "#EABE94", "#0B775E", "#35274A" ,"#F2300F"),
Rushmore = c("#E1BD6D", "#EABE94", "#0B775E", "#35274A" ,"#F2300F"),
Royal1 = c("#899DA4", "#C93312", "#FAEFD1", "#DC863B"),
Royal2 = c("#9A8822", "#F5CDB4", "#F8AFA8", "#FDDDA0", "#74A089"),
Zissou1 = c("#3B9AB2", "#78B7C5", "#EBCC2A", "#E1AF00", "#F21A00"),
Darjeeling1 = c("#FF0000", "#00A08A", "#F2AD00", "#F98400", "#5BBCD6"),
Darjeeling2 = c("#ECCBAE", "#046C9A", "#D69C4E", "#ABDDDE", "#000000"),
Chevalier1 = c("#446455", "#FDD262", "#D3DDDC", "#C7B19C"),
FantasticFox1 = c("#DD8D29", "#E2D200", "#46ACC8", "#E58601", "#B40F20"),
Moonrise1 = c("#F3DF6C", "#CEAB07", "#D5D5D3", "#24281A"),
Moonrise2 = c("#798E87", "#C27D38", "#CCC591", "#29211F"),
Moonrise3 = c("#85D4E3", "#F4B5BD", "#9C964A", "#CDC08C", "#FAD77B"),
Cavalcanti1 = c("#D8B70A", "#02401B", "#A2A475", "#81A88D", "#972D15"),
GrandBudapest1 = c("#F1BB7B", "#FD6467", "#5B1A18", "#D67236"),
GrandBudapest2 = c("#E6A0C4", "#C6CDF7", "#D8A499", "#7294D4"),
IsleofDogs1 = c("#9986A5", "#79402E", "#CCBA72", "#0F0D0E", "#D9D0D3", "#8D8680"),
IsleofDogs2 = c("#EAD3BF", "#AA9486", "#B6854D", "#39312F", "#1C1718"))
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