ggplot2

问题 I am trying to understand how ggplot2 handles the aesthetics for color. The two ggplot commands shown below display different colors.The second command displays a lighter color, and in addition prints a legend. I appreciate if anyone can throw some light on this concept. data(iris) #1st command ggplot(iris) + geom_point(aes(Sepal.Length,Sepal.Width), color = "red") #2nd command ggplot(iris) + geom_point(aes(Sepal.Length,Sepal.Width, color = "red")) 回答1: aes() maps between variables in the

问题 I am trying to understand how ggplot2 handles the aesthetics for color. The two ggplot commands shown below display different colors.The second command displays a lighter color, and in addition prints a legend. I appreciate if anyone can throw some light on this concept. data(iris) #1st command ggplot(iris) + geom_point(aes(Sepal.Length,Sepal.Width), color = "red") #2nd command ggplot(iris) + geom_point(aes(Sepal.Length,Sepal.Width, color = "red")) 回答1: aes() maps between variables in the

问题 I'm trying to create a boxplot which shows only the significant p values, within the groups for each bar in a box plot. For example here it would compare I1 and SI2 for the "fair", "good", "very good" etc I've tried using the following code to achieve the above plot library(ggplot2) library(dplyr) data("diamonds") labeldat <- diamonds %>% group_by(cut, clarity) %>% dplyr::summarise(labels = paste(n(), n_distinct(color), sep = "\n")) Comparisons = list(c("I1","SI2"),c("I1","SI1"),c("I1","VS2")

问题 I have some data which looks like: # A tibble: 50 x 11 V1 V2 V3 V4 V5 V6 V7 V8 GRP ID OUTCOME <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <int> <dbl> 1 0.667 0.539 0.373 -0.774 0.197 -0.0816 -0.0835 0.189 1 166 1 2 -0.436 -0.592 -0.686 -0.364 -0.0200 -0.0360 0.0285 -0.147 1 61 1 3 -0.631 -0.573 -0.705 -0.287 -0.0507 0.0474 0.0182 -0.0702 1 54 1 4 0.418 0.731 0.500 0.262 -0.0979 0.0353 0.0450 0.0156 1 240 0 5 1.03 0.281 -0.0649 -0.670 0.223 0.138 0.0336 0.162 1 179 1 6 -0.200 0.312 0

问题 My dataframe df look like this Year Frequency 1 1975 86 2 1976 52 3 1977 53 4 1978 54 5 1979 301 6 1980 161 You can use this to reproduce the data.frame yourself: ydf <- structure(list(Year = c(1975, 1976, 1977, 1978, 1979, 1980), Frequency = c(86, 52, 53, 54, 301, 161)), row.names = c(NA, -6L), class = "data.frame") And I plotted this graph with ggplot(ydf, aes(x = Year, y = Frequency, fill=Frequency)) + geom_bar(stat = "identity") + geom_text(aes(label = Frequency), nudge_y=1, check_overlap

问题 I'm trying to make a world map with a custom legend on the right side. The legend should be with the prepared text on the left and the generated numbers on the right. I tried but to no avail. I need help My code is as follows: library(dplyr) library(ggplot2) library(ggrepel) library(rworldmap) world_map_without_antarctica <- getMap()[-which(getMap()$ADMIN=='Antarctica'),] #get data from web world_map_without_antarctica_t <- fortify(world_map_without_antarctica) Data <- data.frame( "lon"=c(17

问题 I am producing a list of boxplots from a list of data frames as so: Bps<-lapply(dflist, function(x){ gg<-ggplot(x, aes(x= x, y= y, fill= x))+ geom_boxplot(position = "dodge")+ ggtitle(names(x)) }) The list of dataframes can be generated by: df1<-data.frame(x=seq(1:50), y=rep("Blank", "Non_blank",25)) df2<-data.frame(x=seq(1:40), y=rep("Blank", "Non_blank",20)) df3<-data.frame(x=seq(1:30), y=rep("Blank", "Non_blank",15)) dflist<-list(df1,df2,df3 I need to paste the names of the original

问题 I got the following dataframe describing the age structure in different german districts: I would like to plot one line per row with ggplot in R. An easy solution via matplot in R is: matplot(t(df61[,-c(1,2)], type="l")) which yields: But how is it working with ggplot. I understood, that I have to transform the dataframe into a flat form: library("reshape2") df61_long <- melt(df61[,-2], id.vars = "NAME") Which gives me: I thought that the solution via ggplot should be something like: ggplot

问题 I got the following dataframe describing the age structure in different german districts: I would like to plot one line per row with ggplot in R. An easy solution via matplot in R is: matplot(t(df61[,-c(1,2)], type="l")) which yields: But how is it working with ggplot. I understood, that I have to transform the dataframe into a flat form: library("reshape2") df61_long <- melt(df61[,-2], id.vars = "NAME") Which gives me: I thought that the solution via ggplot should be something like: ggplot

问题 I would like to plot a nice, 'approaching the limit'-looking normal pdf in ggplot. I found that to get a very symmetric and clean looking plot, I had to crank up the number of samples to a rather large number; one million creates a great visualization. However, this is pretty slow, especially if I hope to work with Shiny at some point. df <- data.frame(c(rnorm(1000000))) ggplot(df, aes(df[1])) + geom_density() Surely there is a better way to display something close to the ideal normal