facet

问题 I have a spatialtemporal dataset with various indicators for a set of location that I wish to map overtime. Here is my facet_wrap + loop #basemap basemap <- ggplot() + geom_sf(data= country_adm2) + coord_sf() + theme_void() print(basemap) #joining dataframe to polygons df_poly <- left_join(country_adm2, df, by= "County") ##joins the data by County. #loop & facet_wrap plots ## This goes over the dataset (df_poly) to plot the the three variables, and facet_wrap over ~Date to see time variation

问题 I have a spatialtemporal dataset with various indicators for a set of location that I wish to map overtime. Here is my facet_wrap + loop #basemap basemap <- ggplot() + geom_sf(data= country_adm2) + coord_sf() + theme_void() print(basemap) #joining dataframe to polygons df_poly <- left_join(country_adm2, df, by= "County") ##joins the data by County. #loop & facet_wrap plots ## This goes over the dataset (df_poly) to plot the the three variables, and facet_wrap over ~Date to see time variation

问题 I have a spatialtemporal dataset with various indicators for a set of location that I wish to map overtime. Here is my facet_wrap + loop #basemap basemap <- ggplot() + geom_sf(data= country_adm2) + coord_sf() + theme_void() print(basemap) #joining dataframe to polygons df_poly <- left_join(country_adm2, df, by= "County") ##joins the data by County. #loop & facet_wrap plots ## This goes over the dataset (df_poly) to plot the the three variables, and facet_wrap over ~Date to see time variation

问题 I am trying to ggplot D2 on the same figure as of D1 . I, however, do not have data for the Variable X in D2 data.frame . How i can plot D2 on its respective facets of D1 plot ? these plots represent data for 2011 and 2014 so i would like to have legends for the line to differentiate which line represent which year data. library(tidyverse) set.seed(1500) D1 <- data.frame(Day = 1:8, A = runif(8, 2,16), S = runif(8, 3,14), X = runif(8, 5,10), Z = runif(8, 1,12), Year = rep("2011",8)) D2 <- data

问题 I have the following data and a faceted plot generated from it. # Data generation dataPlot <- mtcars %>% select(mpg, wt, carb) %>% group_by(carb) %>% mutate(N = n()) %>% data.frame() # Original Faceted plot g1 <- ggplot(dataPlot, aes(mpg, wt)) + geom_point() + facet_wrap(~carb) + ggtitle("Original plot") I would like to extract the following plot from the above plot. For comparison, I am generating it from the data itself. # Refined plot with minimum 4 points g2 <- ggplot(dataPlot %>% filter

问题 I have boxplots in multiple facets and I would like to perform a Kruskal-Wallis test on each facet, and place the result on top-left of each respective facet. To exemplify this, I am using the iris dataset, to which I added an additional variable named "treatment". MWE: library(reshape2) library(ggplot2) data(iris) iris$treatment <- rep(c("A","B"), length(iris$Species)/2) mydf <- melt(iris, measure.vars=names(iris)[1:4]) mydf$treatment <- as.factor(mydf$treatment) mydf$variable <- factor(mydf

问题 I have a dataset like the below and am trying to get an ordered faceted stacked barplot. I have looked at some answers on SO particularly this one to come up with my plot but am not sure why this does not work on one particular bar of my stacked barplot structure(list(reg = c("J", "J", "J", "J", "J", "J", "J", "J", "KA", "KA", "KA", "KA", "KA", "KA", "KA", "KA", "KA", "KA", "RI", "RI", "RI", "RI", "SU", "SU", "SU", "SU", "SU", "SU", "SA", "SA", "SA", "SA", "SA", "SA", "SA", "SA", "SA", "SA",

问题 I have a dataset like the below and am trying to get an ordered faceted stacked barplot. I have looked at some answers on SO particularly this one to come up with my plot but am not sure why this does not work on one particular bar of my stacked barplot structure(list(reg = c("J", "J", "J", "J", "J", "J", "J", "J", "KA", "KA", "KA", "KA", "KA", "KA", "KA", "KA", "KA", "KA", "RI", "RI", "RI", "RI", "SU", "SU", "SU", "SU", "SU", "SU", "SA", "SA", "SA", "SA", "SA", "SA", "SA", "SA", "SA", "SA",

问题 I'm working in a jupyter notebook trying to display a sort of adjacency-matrix-like data set in a grouped layout like this one using Altair's Chart.facet() method. This guy's answer gets me halfway there, but when I try to facet with rows and resolve the y scale as 'independent', the chart comes up as a tiny box containing no elements. df = (pd.util.testing.makeDataFrame() .reset_index(drop=True) # drop string index .reset_index() # add an index column .melt(id_vars=['index'], var_name=

问题 There are plenty of explanations, including this good one, of how to label box plots with sample size. All of them seem to use max(x) or median(x) to position the sample size. I'm wondering if there is a way to easily position the labels at the top or bottom of the plot, especially when using the scale = "free_y" command in facet where the max and minimum value for the axis is picked automatically for each facet by ggplot. The reason is that I am creating multiple facets where the