ggproto

问题 When plotting a bar chart, I often add labels to bars to signify the y-value for each bar. However, I run into trouble when the bar becomes too low, making the label unreadable or simply ugly. Example library(ggplot2) df_blood <- data.frame(blood_type = c("O-", "O+", "A-", "A+", "B-", "B+", "AB-", "AB+"), frequency = c(0.13, 0.35, 0.08, 0.3, 0.02, 0.08, 0.01, 0.02)) ggplot(df_blood, aes(x = blood_type, y = frequency, fill = blood_type)) + geom_bar(stat = "identity") + geom_text(aes(label =

问题 When plotting a bar chart, I often add labels to bars to signify the y-value for each bar. However, I run into trouble when the bar becomes too low, making the label unreadable or simply ugly. Example library(ggplot2) df_blood <- data.frame(blood_type = c("O-", "O+", "A-", "A+", "B-", "B+", "AB-", "AB+"), frequency = c(0.13, 0.35, 0.08, 0.3, 0.02, 0.08, 0.01, 0.02)) ggplot(df_blood, aes(x = blood_type, y = frequency, fill = blood_type)) + geom_bar(stat = "identity") + geom_text(aes(label =

问题 When plotting a bar chart, I often add labels to bars to signify the y-value for each bar. However, I run into trouble when the bar becomes too low, making the label unreadable or simply ugly. Example library(ggplot2) df_blood <- data.frame(blood_type = c("O-", "O+", "A-", "A+", "B-", "B+", "AB-", "AB+"), frequency = c(0.13, 0.35, 0.08, 0.3, 0.02, 0.08, 0.01, 0.02)) ggplot(df_blood, aes(x = blood_type, y = frequency, fill = blood_type)) + geom_bar(stat = "identity") + geom_text(aes(label =

问题 When plotting a bar chart, I often add labels to bars to signify the y-value for each bar. However, I run into trouble when the bar becomes too low, making the label unreadable or simply ugly. Example library(ggplot2) df_blood <- data.frame(blood_type = c("O-", "O+", "A-", "A+", "B-", "B+", "AB-", "AB+"), frequency = c(0.13, 0.35, 0.08, 0.3, 0.02, 0.08, 0.01, 0.02)) ggplot(df_blood, aes(x = blood_type, y = frequency, fill = blood_type)) + geom_bar(stat = "identity") + geom_text(aes(label =

问题 I've found the dplyr %>% operator helpful with simple ggplot2 transformations (without resorting to ggproto , which is required for ggplot2 extensions), e.g. library(ggplot2) library(scales) library(dplyr) gg.histo.pct.by.group <- function(g, ...) { g + geom_histogram(aes(y=unlist(lapply(unique(..group..), function(grp) ..count..[..group..==grp] / sum(..count..[..group..==grp])))), ...) + scale_y_continuous(labels = percent) + ylab("% of total count by group") } data = diamonds %>% select

问题 I've found the dplyr %>% operator helpful with simple ggplot2 transformations (without resorting to ggproto , which is required for ggplot2 extensions), e.g. library(ggplot2) library(scales) library(dplyr) gg.histo.pct.by.group <- function(g, ...) { g + geom_histogram(aes(y=unlist(lapply(unique(..group..), function(grp) ..count..[..group..==grp] / sum(..count..[..group..==grp])))), ...) + scale_y_continuous(labels = percent) + ylab("% of total count by group") } data = diamonds %>% select

问题 I know that in ggplot2 one can add the convex hull to a scatterplot by group as in library(ggplot2) library(plyr) data(iris) df<-iris find_hull <- function(df) df[chull(df$Sepal.Length, df$Sepal.Width), ] hulls <- ddply(df, "Species", find_hull) plot <- ggplot(data = df, aes(x = Sepal.Length, y = Sepal.Width, colour=Species, fill = Species)) + geom_point() + geom_polygon(data = hulls, alpha = 0.5) + labs(x = "Sepal.Length", y = "Sepal.Width") plot I was wondering though how one could

问题 I've been working on a radar plot recently and found a great bit of code on from Erwan Le Pennec. I've made a few edits, however there are some parts I couldn't work out how to remove the outermost circle as it doesn't define a value. Currently the code is plotting the major grid lines. I've tried to trick it into removing both axis and only plotting the minor increments however either has worked. Cheers! Here is my code: coord_radar <- function (theta = "x", start = 0, direction = 1) { theta

问题 Reproducible code: x = sample(1:12,100,replace=TRUE) y = rnorm(100) z = sample(c('Sample A','Sample B'),100,replace=TRUE) d = data.frame(x,y,z) ggplot(data=d, aes(factor(x),y)) + geom_boxplot() + stat_summary(fun.y=mean, geom="line", aes(group=1), color ='red') + stat_summary(fun.y=mean, geom="point", color='red') + xlab('Months') + ylab('Metric') + facet_wrap(~z) I want to add a table at the end of this chart that displays the summary statistics- mean, median, quartiles and number of records

问题 I have x=rnorm(100) y=rnorm(100) plot(x,y) abline(h=0); abline(v=0) From point (0,0) and going outwards I would like to draw a contour/circle/ellipse/freehand convex hull that encloses any given percentage of points. Is there any function or package that can automate this? I have tried the following so far but I can only get a circle with some extrapolation and approximation. I have tried this so far: #calculate radius r<- sqrt(x^2+y^2) df<-data.frame(radius=seq(0,3,0.1), percentage=NA) #get