根据列绘制具有不同颜色的 data.frame [英] Plotting data.frame with different colour according to a column

问题描述

我有一个这样的数据框:

I have a data frame like this:

> video
id          oldid      year month day   lon    lat    colour
01208513    Continent    1885   1   1   -30.7   -32.65  #FFFFFF
04960001    05890280     1885   1   1   122.72  26.17   #FDFEFF
05520001    CornFMort    1885   1   1   -22.84  48.34   #FBFDFF
06058       06058        1885   1   1   -61.5   36.5    #F9FCFF
06251       06251        1885   1   1   -113.5  -2.5    #F7FBFF
06323        06323       1885   1   1   174.5   -26.5   #F5FAFF
06466       06466        1885   1   1   -115.5  -40.5   #F3F9FF
106323       106323      1885   1   1   177.5   -26.5   #F1F8FF

我根据其 id 为每个数据分配了一种颜色

where I have assigned a colour to every data according to its id

z <- unique(video$id)
range01 <- function(x)(x-min(x))/diff(range(x))
rainbow(7)
cRamp <- function(x){
  cols <- colorRamp(colours())(range01(x))
  apply(cols, 1, function(xt)rgb(xt[1], xt[2], xt[3], maxColorValue=255))
} 
video$col <- as.factor(cRamp(match(video$id,z)))

实际上我想做的是绘制每天 lon 和 lat 的值，用颜色区分不同的 id，但到目前为止还没有似乎工作.是否存在与 video$colour 类相关的任何问题，或者我应该以不同的方式分配颜色?

What I would like to do in fact is to plot the value of lon and lat for every day with the colours distinguishing the different ids but so far it does not seem to work. Can be there any issues related to the class of video$colour or should I assign the colour in a different way?

要绘制我将数据框划分为年/月/日文件:

To plot I dividing the data frame in year/month/day files:

YRMODYlist <- list()
YRMODYlist <- split(video, data.frame(video$yr, video$mo, video$dy))

然后绘图

for (i in 1:length(YRMODYlist)){
    colnames(YRMODYlist[[i]]) <-c("id","oldid","yr","mo","dy","lon","lat","col")
    plot(YRMODYlist[[i]]$lon, YRMODYlist[[i]]$lat, ylim=c(-90,90),xlim=c(-180,180),col = YRMODYlist[[i]]$col)
}

推荐答案

看着你的数据，我怀疑这是某种面向地理的数据集(因为使用了 lon 和 lat 变量，通常用于识别地理位置)以及分布在世界各地的位置.

Looking at your data, I suspect that this some kind of geographically oriented dataset (because of the use of the lon and lat variables, which are usually used for identifiing geographic locations) with locations scattered around the world.

假设我是对的，你可能会按如下方式解决这个问题:

Assuming that I'm right, you might tackle this problem as follows:

# reading the data
video <- read.table(header=TRUE, comment.char="",
text="id          oldid      year  month  day   lon    lat    colour
01208513    Continent    1885   1   1   -30.7   -32.65  #FFFFFF
04960001    05890280     1885   1   1   122.72  26.17   #FDFEFF
05520001    CornFMort    1885   1   1   -22.84  48.34   #FBFDFF
06058       06058        1885   1   1   -61.5   36.5    #F9FCFF
06251       06251        1885   1   1   -113.5  -2.5    #F7FBFF
06323        06323       1885   1   1   174.5   -26.5   #F5FAFF
06466       06466        1885   1   1   -115.5  -40.5   #F3F9FF
106323       106323      1885   1   1   177.5   -26.5   #F1F8FF")

# getting the required packages
library(ggmap)
library(ggplot2)

# splitting the dataframe into a list of dataframes by id
video$id <- as.factor(video$id)
idlist <- split(video, video$id)

# creating a map for each location with the corresponding points plotted on it
for (i in 1:length(idlist)){
  x <- get_map(location = c(lon=mean(idlist[[i]]$lon), lat=mean(idlist[[i]]$lat)), zoom=3, maptype="satellite", scale=2)
  p <- ggmap(x) + geom_point(data=idlist[[i]], aes(x=lon, y=lat, fill=as.factor(id)), size = 4, shape = 21, show_guide=FALSE)
  print(p)
}

这将产生一系列像这样的图:

this will produce a series of plots like this:

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