Stripchart with multiple groups Functions:geom_jitter(),stat_summary() Density plots Basic density plots Change density plot line types and colors Change density plot colors by groups Calculate the mean of each group : Change line colors
Facet with one discrete variable. Split by the levels of the group “supp” # Split in vertical directionp + facet_grid(rows = vars(supp))# Split in horizontal directionp + facet_grid(cols = vars(supp)) Facet with multiple variables. Split by the levels of two grouping variables: “dos...
group") ## Expand grid to ensure every combination has a defined value tmp <- expand.grid(x=unique(df$x), group=unique(df$group)) tmp <- merge(df, tmp, all.y=TRUE) df <- mutate(tmp, y=ifelse(is.na(y), 0, y)) ## Cast into a matrix shape and arrange by first column ...
#---ggpubr---## One limitation of ggExtra is that it can’t cope with multiple groups in the scatter plot and the marginal plots.# A solution is provided in the function ggscatterhist() [ggpubr]:library(ggpubr)# Grouped Scatter plot with marginal density plotsggscatterhist( iris, x...
Change the bar line and fill colors by group Contents: Key R functions Data preparation Loading required R package Basic barplots Change barplot colors by groups Barplot with multiple groups Conclusion Related Book GGPlot2 Essentials for Great Data Visualization in R ...
ggplot(df, aes(x = x, fill = group)) + geom_bar() stat = “identity” Settingstat = "identity"you can create a stacked bar plot for multiple variables. In this scenario you can pass other variable toaes, representing the value or count of that variable. ...
Multiple Variables library(reshape2) library(plotly) test_data <- data.frame( var0 = 100 + c(0, cumsum(runif(49, -20, 20))), var1 = 150 + c(0, cumsum(runif(49, -10, 10))), date = seq(as.Date("2002-01-01"), by="1 month", length.out=100) ) test_data_long <- mel...
# Scatter plot of x and y variables and color by groups scatterPlot <- ggplot(df2,aes(x, y, color=group)) + geom_point() + scale_color_manual(values = c('#999999','#E69F00')) + theme(legend.position=c(0,1), legend.justification=c(0,1)) # Marginal density plot of x (top...
As an example, I checked the averages by id for marker A and then used another line type for the ID with the highest average, ID=4, in all graphs. See below: data_long <- pivot_longer(data, cols = marker_all) summary<-data_long[data_long$name=="markerA",]%>%group_by(ID)%...
Same idea, but using 2 categorical variables for the faceting. Customized An advanced examples to make sure you know how to make your small multiple pretty. Strip features Customize the general layout with the strip option. Mixing charts