facet-wrap

问题 I am using fdc of hydroTSM package . I have three data.frame and i would like to construct Flow duration curves (FDC) of the data.frame using facet_wrap functionality of ggplot to have the plots in three rows and one column . the following will produce FDC curves for DF1 . library(tidyverse) library(hydroTSM) library(gridExtra) DF1 = data.frame(Ob = runif(1000,0,500), A = runif(1000,0,700), B = runif(1000,2,800)) DF2 = data.frame(Ob = runif(1000,0,500), A = runif(1000,0,700), B = runif(1000,2

问题 I am using fdc of hydroTSM package . I have three data.frame and i would like to construct Flow duration curves (FDC) of the data.frame using facet_wrap functionality of ggplot to have the plots in three rows and one column . the following will produce FDC curves for DF1 . library(tidyverse) library(hydroTSM) library(gridExtra) DF1 = data.frame(Ob = runif(1000,0,500), A = runif(1000,0,700), B = runif(1000,2,800)) DF2 = data.frame(Ob = runif(1000,0,500), A = runif(1000,0,700), B = runif(1000,2

问题 I am trying to wrap numerous plots together, as they are closely related (showing density using 1 continuous and 1 categorical variable, broken down by day of the week, where each day is a different plot). In R, I can either use grid.arrange() from gridExtra or facet_wrap to wrap visualizations together to return to the user as 1 variable and image containing all plots. It looks like this: How do I do this in Python? 回答1: Yes, this can be done using matplotlib subplots. See this example. The

问题 My tbl_df: > str(p2p_dt_SKILL_A) Classes ‘tbl_dt’, ‘tbl’, ‘data.table’ and 'data.frame': 693 obs. of 35 variables: $ Patch : Factor w/ 7 levels "BVG1","BVG11",..: 1 2 3 4 5 6 7 1 2 3 ... $ Skill : Factor w/ 15 levels "A","BROADBAND",..: 1 1 1 1 1 1 1 1 1 1 ... $ Date : Date, format: "2015-12-04" "2015-12-04" "2015-12-04" "2015-12-04" ... $ SOD_FWIH_A : num 1.09 1.14 1.09 1.1 1.09 1.07 1.09 1.07 1.12 1.07 ... $ Prod_MWF : num 5.06 5.06 5.44 5.34 4.22 4.72 4.89 4.68 4.68 5.22 ... $ Prod_MA :

问题 I am trying to use facet_wrap to make a polygon map in ggplot2. I have two factor levels (soybean, Maize) in my variable "crop" However, I am getting three plots: soybean, maize and one with NA values. In addition NA values are not displayed in the first two facets- here is my code to make the map: ggplot(study_area.map, aes(x=long, y=lat, group=group)) + geom_polygon(aes(fill=brazil_loss_new2)) + geom_path(colour="black") + facet_wrap(~crop, ncol=2, drop=T) + scale_fill_brewer(na.value="grey

问题 I am trying to use facet_wrap to make a polygon map in ggplot2. I have two factor levels (soybean, Maize) in my variable "crop" However, I am getting three plots: soybean, maize and one with NA values. In addition NA values are not displayed in the first two facets- here is my code to make the map: ggplot(study_area.map, aes(x=long, y=lat, group=group)) + geom_polygon(aes(fill=brazil_loss_new2)) + geom_path(colour="black") + facet_wrap(~crop, ncol=2, drop=T) + scale_fill_brewer(na.value="grey

问题 I am using facet-wrap to show two variables ( a and b ) for four cities. I could group the plots based on the cities but can not show the legend for the variables (i.e., a and b ) using scale_color_discrete. ggplot() + geom_line(data=df, aes(x=year, y = a, group=city), colour="red",linetype = "longdash",show_guide = TRUE) + geom_line(data=df, aes(x=year, y = b, group=city), colour="blue", show_guide = TRUE) + scale_color_discrete(name="Scenarios",labels=c("a" ,"b")) + guides(color=guide

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 am trying to combine percentage histogram with facet_wrap , but the percentages are not calculated based on group but all data. I would like each histogram to show distribution in a group, not relative to all population. I know it is possible to do several plots and combine them with multiplot . library(ggplot2) library(scales) library(dplyr) set.seed(1) df <- data.frame(age = runif(900, min = 10, max = 100), group = rep(c("a", "b", "c", "d", "e", "f", "g", "h", "i"), 100)) tmp <- df %>%