ggplot2

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 would like to conditionally alter the color/face/etc of a continuous tick mark label using logic instead of hard coding. For example: library(tidyverse) library(viridis) xx=rpois(1000,lambda = 40) y=density(xx,n=3600,from=0) ggplot(data.frame(x = y$x, y = y$y), aes(x, y)) + geom_line() + geom_segment(aes(xend = x, yend = 0, colour = y)) + scale_color_viridis() + labs(y='Density',x='Count',colour='Density')+ geom_vline(xintercept=40,color='red') + scale_x_continuous(breaks=c(0,40,seq(25,100

问题 I am using R studio in Ubuntu, with standard updated R and ggplot2 I try to create a histogram in ggplot, and to separate the data by groups. I need the plot's y axis to say the frequency of each bin in the subgroup that was split by the facet grid. for example if i have two entries in the data a group 1 1 2 2 I need to use facet_grid to split by group, and then to show that a has one bar for 1 that is 100% percent of the examples in group 1 and vice versa. I found out that the way to do it,

问题 I would like to conditionally alter the color/face/etc of a continuous tick mark label using logic instead of hard coding. For example: library(tidyverse) library(viridis) xx=rpois(1000,lambda = 40) y=density(xx,n=3600,from=0) ggplot(data.frame(x = y$x, y = y$y), aes(x, y)) + geom_line() + geom_segment(aes(xend = x, yend = 0, colour = y)) + scale_color_viridis() + labs(y='Density',x='Count',colour='Density')+ geom_vline(xintercept=40,color='red') + scale_x_continuous(breaks=c(0,40,seq(25,100

问题 I would like to conditionally alter the color/face/etc of a continuous tick mark label using logic instead of hard coding. For example: library(tidyverse) library(viridis) xx=rpois(1000,lambda = 40) y=density(xx,n=3600,from=0) ggplot(data.frame(x = y$x, y = y$y), aes(x, y)) + geom_line() + geom_segment(aes(xend = x, yend = 0, colour = y)) + scale_color_viridis() + labs(y='Density',x='Count',colour='Density')+ geom_vline(xintercept=40,color='red') + scale_x_continuous(breaks=c(0,40,seq(25,100

问题 I would like to conditionally alter the color/face/etc of a continuous tick mark label using logic instead of hard coding. For example: library(tidyverse) library(viridis) xx=rpois(1000,lambda = 40) y=density(xx,n=3600,from=0) ggplot(data.frame(x = y$x, y = y$y), aes(x, y)) + geom_line() + geom_segment(aes(xend = x, yend = 0, colour = y)) + scale_color_viridis() + labs(y='Density',x='Count',colour='Density')+ geom_vline(xintercept=40,color='red') + scale_x_continuous(breaks=c(0,40,seq(25,100

问题 I am using R studio in Ubuntu, with standard updated R and ggplot2 I try to create a histogram in ggplot, and to separate the data by groups. I need the plot's y axis to say the frequency of each bin in the subgroup that was split by the facet grid. for example if i have two entries in the data a group 1 1 2 2 I need to use facet_grid to split by group, and then to show that a has one bar for 1 that is 100% percent of the examples in group 1 and vice versa. I found out that the way to do it,