如何改变条形图上的颜色？

Question

I have bars that are all pink and want to know how to change them from light to dark of a color like from red to blue, white to red, etc.

    barplot(d1[1:25,]$freq, las = 2, names.arg = 
    stri_trans_totitle(d1[1:25,]$word),
    col = "pink", main ="Most Frequent Words \n in The Three Musketeers",
    ylab = "Word frequencies", ylim=c(0,2000)) 

Answer 1

Overview

For each height value supplied in barplot() , create a corresponding color. In this case, I create a color palette that progresses from a gray to a dark blue color.

Reproducible Example

Color Picker helps me translate general colors into hexadecimal color values .

# create data frame
df <- data.frame(
  id = 1:5
  , Coolness_Level = 1:5
  , Coolness_Color = NA
  , stringsAsFactors = FALSE
)

# view data
df
# id Coolness_Level Coolness_Color
# 1  1              1             NA
# 2  2              2             NA
# 3  3              3             NA
# 4  4              4             NA
# 5  5              5             NA


# I want colors to progress
# from gray to dark blue
color.function <- colorRampPalette( c( "#CCCCCC" , "#104E8B" ) )

# decide how many groups I want, in this case 5
# so the end product will have 5 bars
color.ramp <- color.function( n = nrow( x = df ) )

# view colors
color.ramp
# [1] "#CCCCCC" "#9DACBB" "#6E8DAB" "#3F6D9B" "#104E8B"

# assign every row in df
# a color
# based on their $Coolness_Level
df$Coolness_Color <-
  as.character(
    x = cut(
      x = rank( x = df$Coolness_Level )  # used to assign order in the event of ties
      , breaks = nrow( x = df )  # same as the 'n' supplied in color.function()
      , labels = color.ramp  # label the groups with the color in color.ramp
    )
  )

# view the data
df
# id Coolness_Level Coolness_Color
# 1  1              1        #CCCCCC
# 2  2              2        #9DACBB
# 3  3              3        #6E8DAB
# 4  4              4        #3F6D9B
# 5  5              5        #104E8B

# make barplot
# and save as PNG
png( filename = "my_cool_barplot.png"
     , units = "px"
     , height = 1600
     , width = 1600
     , res = 300
     )
barplot( height = df$Coolness_Level
         , names.arg = df$id
         , las = 1
         , col = df$Coolness_Color
         , border = NA  # eliminates borders around the bars
         , main = "Is Coolness Correlated with Higher ID #s?"
         , ylab = "Coolness Level"
         , xlab = "ID #"
         )
# shut down plotting device
dev.off()

# end of script #

Answer 2

As per ?barplot :

col   a vector of colors for the bars or bar components. By default, grey is used if height is a vector, and a gamma-corrected grey palette if height is a matrix.

You need to add the colours you want as a vector to the col parameter. If you specify fewer colours than bars, the colours will be recycled from the start.

First generate some data.

# Load packages
library(dplyr, warn.conflicts = FALSE, quietly = TRUE, )

# Generate some miles per gallon per number of cylinders data using the mtcars
foo <- mtcars %>% 
       group_by(cyl) %>% 
       summarise(mpg = mean(mpg))

Plot with rainbow colours

with(foo, barplot(mpg, 
                  names.arg = cyl, 
                  xlab = "Number of cylinders", 
                  ylab = "Mean miles per gallon", 
                  col = rainbow(3)))

Plot with greyscale

with(foo, barplot(mpg, 
                  names.arg = cyl, 
                  xlab = "Number of cylinders", 
                  ylab = "Mean miles per gallon", 
                  col = grey.colors(3)))

Make your own colour ramp and then plot

pal <- colorRampPalette(colors = c("lightblue", "blue"))(3)

with(foo, barplot(mpg, 
                  names.arg = cyl, 
                  xlab = "Number of cylinders", 
                  ylab = "Mean miles per gallon", 
                  col = pal))

Plot with a user-specified palette

with(foo, barplot(mpg, 
          names.arg = cyl,
          xlab = "Number of cylinders", 
          ylab = "Mean miles per gallon", 
          col = c("#E69F00", "#56B4E9", "#009E73")))