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...bel), x$x, x$y, : > invalid font type > In addition: There were 50 or more warnings (use warnings() to see the > first 50)" > > How can I install the font so that I can see the figures on the pdf files? > Some information that may be useful: > (1) If I use the English ggtitle, there is no problem at all. The pdf file > present the figures perfectly. > (2) If I use Chinese title, I can still see the figures p1 and p2 on > Studio, but I can't see it at the pdf file produced by ggsave. It gives an > error message > > > > rm(list=ls()) > l...

...ion: There were 50 or more warnings (use warnings() to > see the > first 50)" > > How can I install the font so that I can see the figures on the > pdf files? > Some information that may be useful: > (1) If I use the English ggtitle, there is no problem at all. > The pdf file > present the figures perfectly. > (2) If I use Chinese title, I can still see the figures p1 and p2 on > Studio, but I can't see it at the pdf file produced by ggsave. > It gives an >...

...aphics(L_text, as.graphicsAnnot(x$label), x$x, x$y, : invalid font type In addition: There were 50 or more warnings (use warnings() to see the first 50)" How can I install the font so that I can see the figures on the pdf files? Some information that may be useful: (1) If I use the English ggtitle, there is no problem at all. The pdf file present the figures perfectly. (2) If I use Chinese title, I can still see the figures p1 and p2 on Studio, but I can't see it at the pdf file produced by ggsave. It gives an error message rm(list=ls()) library(ggplot2) library(gridExtra) df1<-da...

...invalid font type >> In addition: There were 50 or more warnings (use warnings() to see the >> first 50)" >> >> How can I install the font so that I can see the figures on the pdf files? >> Some information that may be useful: >> (1) If I use the English ggtitle, there is no problem at all. The pdf file >> present the figures perfectly. >> (2) If I use Chinese title, I can still see the figures p1 and p2 on >> Studio, but I can't see it at the pdf file produced by ggsave. It gives an >> error message >> >> >>...

...e at all. I did see the Chinese title in the plot if I ask my RStudio to show the plot (if I type "p1"), but the pdf file shows the plots without the Chinese titles. library(ggplot2) library(gridExtra) df1<-data.frame(x=1:2, y=3:4, z=5:6) #p1<-ggplot(df1, aes(x=x, y=y))+geom_line()+ggtitle("test1") #p2<-ggplot(df1, aes(x=x, y=y))+geom_line()+ggtitle("test2") p1<-ggplot(df1, aes(x=x, y=y))+geom_line()+ggtitle("??") p2<-ggplot(df1, aes(x=x, y=y))+geom_line()+ggtitle("??") p1<-p1+theme(text = element_text(family = "Kaiti TC"...

...warnings (use warnings() to >> see the >> first 50)" >> >> How can I install the font so that I can see the figures on the >> pdf files? >> Some information that may be useful: >> (1) If I use the English ggtitle, there is no problem at all. >> The pdf file >> present the figures perfectly. >> (2) If I use Chinese title, I can still see the figures p1 and p2 >> on >> Studio, but I can't see it at the pdf file produced by ggsave. >>...

...n(x, y) viewport(layout.pos.row = x, layout.pos.col = y) tor<-ggplot(parasitos, aes(x=Arrenurus, y = torax, fill= Arrenurus)) + geom_boxplot(binwidth = 2) + scale_fill_manual(values = c("lightgreen", "lightblue"))+ ylab("Total parásitos")+ xlab("")+ ggtitle("Parásitos en el tórax") abd<- ggplot(parasitos, aes(x=Arrenurus, y = abdomen, fill= Arrenurus)) + geom_boxplot(binwidth = 2) + scale_fill_manual(values = c("lightgreen", "lightblue"))+ ylab("Total parásitos")+ xlab("")+ ggtitle("Pará...

...ene=X, intgroup="condition", returnData=TRUE) png(paste("img/", X, ".png", sep="")) ggplot(d, aes(x=condition, y=count, color=condition)) + geom_point(position=position_jitter(w=0.1,h=0)) + scale_y_log10(breaks=c(25,100,400)) + ggtitle(X) + theme(plot.title = element_text(hjust = 0.5)) dev.off() } 'd' is a dataframe count condition E11.5 F20HET BA40_quant 955.9788 E11.5 F20HET E11.5 F20HET BA45_quant 796.2863 E11.5 F20HET E11.5 F20HET BB84_quant 745.0340 E1...

...- qplot(carat, price, data=dsamp, colour=clarity, geom="path") tmp <- ggplot_gtable(ggplot_build(p1)) leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box") legend <- tmp$grobs[[leg]] grid.arrange(arrangeGrob(p1 + theme(legend.position="none") + ggtitle("Scatter Plot"), p2 + theme(legend.position="none") + ggtitle("Line Plot"), main ="this is a title", left = "This is my global Y-axis...

...eturnData=TRUE) >> png(paste("img/", X, ".png", sep="")) >> ggplot(d, aes(x=condition, y=count, color=condition)) + >> geom_point(position=position_jitter(w=0.1,h=0)) + >> scale_y_log10(breaks=c(25,100,400)) + >> ggtitle(X) + >> theme(plot.title = element_text(hjust = 0.5)) >> >> dev.off() >> } >> >> 'd' is a dataframe >> >> count condition >> E11.5 F20HET BA40_quant 955.9788 E11.5 F20HET >> E11.5...

...on=c(0,1), axis.title.x = element_text(face="bold", colour="black", size=16,vjust=0), axis.title.y = element_text(face="bold", colour="black", size=16,vjust=0.3), legend.text = element_text(size = 12, face = "bold" )) + ggtitle(GGTitle)+ geom_line() + geom_point(size=5) + geom_errorbar(width=0.1, aes(ymin=meanYvar-seYvar, ymax=meanYvar+seYvar)) PLot [[alternative HTML version deleted]]

...= "black", size = 0.5) + geom_errorbar(aes(ymin = mean - sdv , ymax = mean + sdv), width = 0.3, position = "dodge", color = "black", size=0.3) + theme_bw() + ylab(expression(paste("my measured stuff"))) + xlab("factor3") + ggtitle("") + labs(color = "factor1", shape = "factor1", group = "factor1", linetype = "factor1") p1 #Plot: levels C and D: # Summary (means etc) SummCD <- ddply(DataCD, .(factor3,factor1), summarize, mean = mean(var1,...

...t;condition", returnData=TRUE) > png(paste("img/", X, ".png", sep="")) > ggplot(d, aes(x=condition, y=count, color=condition)) + > geom_point(position=position_jitter(w=0.1,h=0)) + > scale_y_log10(breaks=c(25,100,400)) + > ggtitle(X) + > theme(plot.title = element_text(hjust = 0.5)) > > dev.off() > } > > 'd' is a dataframe > > count condition > E11.5 F20HET BA40_quant 955.9788 E11.5 F20HET > E11.5 F20HET BA45_quant 796.2863 E11.5...

...ity", width=0.7, # ANCHO BARRAS colour="grey", fill="darkred", # COLOR (borde relleno) position = "dodge")+ labs(x="MESES", y="IMPORTES EN USD",color="Tipo")+ # TITULOS EJES ggtitle("VALORES AL HABER POR MES EN USD (HISTÓRICOS")#TIT GRAFICO ########################################################################## Los Datasets que tengo, son Diario_S2 para 2020, Dia_S2_19 para 2019 y Dia_S2_18 para 2018. Es decir que tengo un Dataset para cada año. Solicito ay...

...13 FQC.10132112 0.0275 0.002088 0.0457 FQC.10201128 0.0169 0.000289 0.0170 FQC.10208432 0.0443 0.004081 0.0639 FQC.10218466 0.0116 0.000131 0.0115 ... and I am creating plot like this: s <- ggplot(SNP, mapping = aes(x = mean, y = var)) s <- s + geom_density_2d() + geom_point() + my.theme + ggtitle("SNPs") s I am getting plot in attach. My question is how do I: 1.interpret the inclusion versus exclusion within the ellipses-contours? 2. how do I extract from my data frame the points which are outside of ellipses? Thanks Ana -------------- next part -------------- A non-text att...

..."identity", color= "gray") + geom_line(aes(y=Estimada), stat = "identity", color="blue", size=1.5) + geom_point(aes(y=Estimada), shape=21, fill="blue", color="white")+ labs(y = expression(paste("Biomasa ", (g/cm^{2}))))+ ggtitle("Espeletia standleyana")+ theme_minimal()+ annotate(geom = 'text', x = 0, y = 750, hjust = 0, label = "Biomasa=220,774(IAF)+39,759(Aprom)-163,883")+ annotate(geom = 'text', x = 0, y = 700,...

Hola Lorena: Lo prometido es deuda. Dije que miraría si iba este asunto: ggplot(data = dLSaa, aes(x = factor(AA), y = AD, colour = factor(AA))) + geom_boxplot() + xlab( "AA" ) + ylab( "AD" ) + labs(colour = "Leyenda") + ggtitle(label = "Comparación de AD frente a AA") Y este es el resultado: [image: image.png] ¿Te sirve así?. Saludos. ------------ próxima parte ------------ Se ha borrado un adjunto en formato HTML... URL: <https://stat.ethz.ch/pi...

...from my data frame, > >> based on which parameter? > >> > >> So I am trying to connect outliers based on what the plot is showing: > >> s <- ggplot(SNP, mapping = aes(x = mean, y = var)) > >> s <- s + geom_density_2d() + geom_point() + my.theme + ggtitle("SNPs") > >> > >> versus what is in the data: > >> > >> > head(SNP) > >> mean var sd > >> FQC.10090295 0.0327 0.002678 0.0517 > >> FQC.10119363 0.0220 0.000978 0.0313 > >> FQC.10132112 0.02...

...0 1789 where get_density() is function from here: https://slowkow.com/notes/ggplot2-color-by-density/ and then do something like this: a=SNP[SNP$density>400,] and plot it again: p <- ggplot(a, mapping = aes(x = mean, y = var)) p <- p + geom_density_2d() + geom_point() + my.theme + ggtitle("SNPS_red") On Thu, Oct 8, 2020 at 3:52 PM Ana Marija <sokovic.anamarija at gmail.com> wrote: > > Hello, > > I have a data frame like this: > > > head(SNP) > mean var sd > FQC.10090295 0.0327 0.002678 0.0517 > FQC.10119363 0.02...

...ta3), t = rep(points, 3), std.beta = c(std.beta1, std.beta2, std.beta3) ) limits = aes(ymin = mean.beta - std.beta, ymax = mean.beta + std.beta); maintitle = paste("beta function (std = ", std, ")", sep = ""); p + geom_line() + geom_errorbar(limits, width = 0.05) + ggtitle(maintitle) + theme(legend.title=element_blank(), legend.justification=c(0,1), legend.position=c(0,1))+ scale_x_continuous(breaks=seq(0, 10, .1)) + scale_y_continuous(breaks=seq(0, 13, .1)) + ylab("Beta(t)") + scale_colour_hue(breaks=c("Wrong", "Correct", &qu...