search for: ggbar

...investigaré. > > ft$hora <- strptime(ft$hora, format = "%H:%M", tz="GMT-2") > ft$Miles <- as.numeric(gsub("\\.", "", as.character(ft$Miles))) > ft$Share <- as.numeric(gsub("\\,", ".", as.character(ft$Share))) > > ggbar <- ggplot(ft, aes(x = hora, y = frec)) + > geom_area(fill= "gray") + > scale_x_datetime(date_breaks = "5 mins", date_labels = "%H:%M") + > theme(panel.background = element_rect(fill = "white")) + > scale_y_continuous(limits=c(0,1500)) +...

...a variable que use (Share o miles): >> >> >> >> *Error: Discrete value supplied to continuous scalegeom_path: Each group >> consists of only one observation. Do you need to adjust the groupaesthetic?* >> >> Modifique el código tal que así: >> >> ggbar<-ggplot(ft, aes(x=ft$hora, y=ft$frec)) + >> geom_bar(stat="identity", width = 0.8, fill="gray") + >> theme(panel.background = element_rect(fill = "white")) + >> scale_y_continuous(limits=c(0,1500)) >> ggline<-ggplot(ft, aes(x=ft$hora...

...entes > errores -dependiendo la la variable que use (Share o miles): > > > > *Error: Discrete value supplied to continuous scalegeom_path: Each group > consists of only one observation. Do you need to adjust the groupaesthetic?* > > Modifique el código tal que así: > > ggbar<-ggplot(ft, aes(x=ft$hora, y=ft$frec)) + > geom_bar(stat="identity", width = 0.8, fill="gray") + > theme(panel.background = element_rect(fill = "white")) + > scale_y_continuous(limits=c(0,1500)) > ggline<-ggplot(ft, aes(x=ft$hora, y=ft$Miles)) +...

Y bueno, algo más bonito sí que queda con ggplot... #--------------- datIn <- read.csv("pec.csv", header = TRUE, sep = ";", dec = ",") library(ggplot2) lab_x_idx <- c(1, round(nrow(datIn)/2, 0), nrow(datIn)) lab_x <- as.vector(datIn$hora[ lab_x_idx]) fre_gg <- ggplot( datIn, aes( x = 1:nrow(datIn), y = frec)) + geom_bar(stat =

ggplot provides a new system for drawing graphics in R, based on the Grammar of Graphics. It combines the advantages of both base and lattice graphics: conditioning and shared axes are handled automatically, and you can still build up a plot step by step from multiple data sources. It also implements a more sophisticated multidimensional conditioning system and a consistent interface to map data

ggplot provides a new system for drawing graphics in R, based on the Grammar of Graphics. It combines the advantages of both base and lattice graphics: conditioning and shared axes are handled automatically, and you can still build up a plot step by step from multiple data sources. It also implements a more sophisticated multidimensional conditioning system and a consistent interface to map data