search for: theme_bw

...s 1, v2 to be as close as 0. Thanks very much. DF ID v1 v2 v3 1 0.8 0.1 0.7 2 0.85 0.3 0.6 3 0.9 0.21 0.7 4 0.95 0.22 0.8 5 0.9 0.3 0.7 6 0.8 0.4 0.76 7 0.9 0.3 0.77 ... fig1 = ggplot(data=DF, aes(x=v1,y=v2))+ geom_point()+ theme_bw()+ xlab('Variable 1')+ ylab('Variable 2') print(fig1) fig2 = ggplot(data=DF, aes(x=v1,y=v3)+ geom_point()+ theme_bw()+ xlab('Variable 1')+ ylab('Variable 3') print(fig2) [[alternative HTML version deleted]]

...et the colour aesthetic. The ID is numeric so ggplot applies a colour scale. If we cast ID to a factor we get the appropriate colouring. test_df <- data.frame(ID = 1:20, v1 = rnorm(20), v2 = rnorm(20), v3 = rnorm(20)) ggplot(data=test_df, aes(x=v1,y=v2, colour = as.factor(ID))) + geom_point()+ theme_bw()+ xlab('Variable 1')+ ylab('Variable 2') How to choose a number of samples from the dataset you can use the subset function to select by some variable: sub_test_df1 <- subset(test_df, ID < 5) ggplot(data=sub_test_df1, aes(x=v1,y=v2, colour = as.factor(ID))) + geom_point()...

Hi all; I am running the following ggplot codes. Runs well. However, I need to reflect the numeric values of the log10_P to the point size in the graph. Your help highly appreciated, Regards, Greg p <- ggplot(mydata, aes(x = X, y = log10_P)) + theme_bw() +theme(panel.border=element_blank()) + theme(legend.position="top", axis.text=element_text(size = 8)) (p1 <- p + geom_point(aes(color = Traits) [[alternative HTML version deleted]]

...s numeric so ggplot applies a colour scale. If we cast ID to a > factor we get the appropriate colouring. > > test_df <- data.frame(ID = 1:20, v1 = rnorm(20), v2 = rnorm(20), v3 = > rnorm(20)) > > ggplot(data=test_df, aes(x=v1,y=v2, colour = as.factor(ID))) + > geom_point()+ theme_bw()+ > xlab('Variable 1')+ ylab('Variable 2') > > How to choose a number of samples from the dataset you can use the subset > function to select by some variable: > sub_test_df1 <- subset(test_df, ID < 5) > > ggplot(data=sub_test_df1, aes(x=v1,y=v2, colour...

You could add size = log10_P to the aes() inside geom_point(). Untested code below. See also http://ggplot2.tidyverse.org/reference/geom_point.html ggplot(mydata, aes(x = X, y = log10_P)) + theme_bw() + theme(panel.border=element_blank(), legend.position="top", axis.text=element_text(size = 8)) + geom_point(aes(color = Traits, size = log10_P)) Jean On Fri, Jun 16, 2017 at 9:33 AM, greg holly <mak.hholly at gmail.com> wrote: > Hi all; > > I am running the follow...

...position = "dodge", width = 0.3, size=3) + geom_line(aes(linetype=factor1), color = "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 et...

...quot;SPINYTAIL","BIGELOW'S","SKATES (NS)","THORNY","SMOOTH","ABYSSAL","LITTLE","DEEPWATER","JENSEN'S","WHITE","SOFT")) + ylab("Abundance (fish/tow)") + coord_flip() + theme_bw() + opts(axis.title.x = theme_text(size = 10)) + opts(panel.grid.minor = theme_blank()) + opts(legend.position='none') ) (b<-ggplot(Final2, aes(x=spp, y=WPUE, fill=season)) + geom_bar(position=position_dodge()) + geom_errorbar(aes(ymin=WPUE-wpue.se, ymax=WPUE+wpue.se),...

...;blue") legend.labs <- c("Cluster1", "Cluster2", "Cluster3", "Cluster4") } ggsurvplot(cluster, data = inputfile, risk.table = F, palette = palette, ylim=c(0,1),ggtheme = theme_bw(),xlab="Relapse Free Suvival (Days)", main = "Survival curve",pval = TRUE,font.x = 16,font.y = 16, font.tickslab = 14,font.legend =c(14,"plain","black"), legend = "bottom", legend.title = "Tr...

...n trying to overlay two plots of the same points, one plotted with fills and the other plotted with edge outlines (here is my conceptual code): pfill <- ggplot(data=DF, aes(x=X, y=Y)) + geom_point(aes(colour=TRT),size=4) + scale_colour_grey(end=0.8) + theme_bw pedge <- ggplot(data=DF, aes(x=X, y=Y)) + geom_point(aes(colour=TRT),size=4) + scale_colour_grey(end=0.8) + scale_shape(solid=FALSE) + theme_bw However, I can't figure out the correct syntax, if this is even the right way to go about it...

...;,"green", "blue") legend.labs <- c("Cluster1", "Cluster2", "Cluster3", "Cluster4") } fig <-ggsurvplot(cluster, data = inputfile, risk.table = F, palette = palette, ylim=c(0,1),ggtheme = theme_bw(),xlab="Relapse Free Suvival (Days)", main = "Survival curve",pval = TRUE,font.x = 16,font.y = 16, font.tickslab = 14,font.legend =c(14,"plain","black"), legend = "bottom", legend.title = "T...

...legend.labs <- c("Cluster1", "Cluster2", "Cluster3", "Cluster4") > } > > ggsurvplot(cluster, data = inputfile, risk.table = F, > palette = palette, > ylim=c(0,1),ggtheme = theme_bw(),xlab="Relapse Free Suvival (Days)", > main = "Survival curve",pval = TRUE,font.x = 16,font.y = 16, > font.tickslab = 14,font.legend =c(14,"plain","black"), > legend = "bottom", > leg...

...lour=Stat))+ coord_cartesian(ylim = c(0, 10)) + geom_line()+ geom_point() ## this works ## BUT: ## code 2 col.2<-cb8[4:5] ggplot(df,aes(Year,Flow,group=Stat,colour=Stat))+ coord_cartesian(ylim = c(0, 10)) + geom_line()+ geom_point()+ scale_color_manual(values =cb8[4:5])+ theme_bw() ## this gives error message Error: Continuous value supplied to discrete scale ## However this example using code from the net does work so I don't understand why my ## second code doesn't work. ## code 3 df.1 <- data.frame(store=c('A', 'A', 'A', 'B',...

...heme for race but dont know how, can someone show me. Thanks in advance Code and input file below: library(ggplot2) library(gridExtra) d<-read.table("results", header=TRUE, fill=TRUE) plot2<-qplot(X,Y,data=d,color=race,facets=TYPE~., xlab="X", ylab="Y") + theme_bw() grid.arrange(plot2,ncol=1) dev.off() cat? results <snip> X?????? Y?????? ID????? race??? TYPE 0.0350? 0.0200??? 1??? X??? NA 0.0280? 0.0251??? 2??? X??? NA 0.0258? 0.0175????3??? Y??? NA </snip>

...ue") > legend.labs <- c("Cluster1", "Cluster2", "Cluster3", "Cluster4") > } > > > fig <-ggsurvplot(cluster, data = inputfile, risk.table = F, > palette = palette, > ylim=c(0,1),ggtheme = theme_bw(),xlab="Relapse Free Suvival > (Days)", > main = "Survival curve",pval = TRUE,font.x = 16,font.y = 16, > font.tickslab = 14,font.legend =c(14,"plain","black"), > legend = "bottom", >...

...lour for 0-10, next shade for 10-30, next for 30-70 etc. Due to some magic done on the data, one uses intervals 0,50,100,150 and the other 0,20,40 etc. - not important but I would be interested to know why. My plots are created by; ggplot(DiffMod,aes(binL,binR,fill=HProbCount)) + geom_tile() + theme_bw() + scale_fill_gradient(low="white",high="red") ggplot(DiffMod,aes(binL,binR,fill= HCount)) + geom_tile() + theme_bw() + scale_fill_gradient(low="white",high="red") I can get the intervals right in the legend using; ggplot(DiffMod,aes(binL,binR,fill=HPr...

...15)) + scale_colour_discrete(name ="Group", breaks=c("ace", "ctrlAM","met"), labels=c("acetone", "untreated","methoprene"))+ theme_bw() + # maek background theme black and white opts(legend.justification=c(1,0),# legend justification needs to be in the (options) legend.position=c(1,0), panel.grid.major...

...quot;,"green", "blue") legend.labs <- c("Cluster1", "Cluster2", "Cluster3", "Cluster4") } fig <-ggsurvplot(cluster, data = inputfile, risk.table = F, palette = palette, ylim=c(0,1),ggtheme = theme_bw(),xlab="Relapse Free Suvival (Days)", main = "Survival curve",pval = TRUE,font.x = 16,font.y = 16, font.tickslab = 14,font.legend =c(14,"plain","black"), legend = "bottom", legend.title = "Tr...

...D) p1 <- ggplot(barley,aes(fill=year,y=yield,x=variety)) p2 <- p1 + geom_bar(position="dodge",stat="identity") dodge <- position_dodge(width=0.9) p3 <- p2 + geom_errorbar(limits,position=dodge,width=0.5,size=0.7) p4 <- p3 + facet_wrap(~site,ncol=2) p5 <- p4+theme_bw(base_size=16) p5 last_plot() + opts(panel.grid.minor=theme_blank()) # deletes the minor grid lines ## Now i would like to increase the width of all remaining lines (bottom, left, top, right border of all panels and stripes) in the plot, as a certain minimum lines width is required by many jo...

...er.95ci and upper.95ci. Presently I am doing the following: qplot(x=as.factor(sch),y=lower.95ci) + geom_point(aes(x=as.factor(sch),y=upper.95ci),colour="black") + geom_point(aes(x=as.factor(sch), y=est),colour="red") + ylab("Value-Added") + xlab("School") + theme_bw() Which creates this graph ---> http://dl.dropbox.com/u/1501309/value_added_test.pdf That's fine except that it doesn't connect the points vertically. Does anyone know how I could make the 'black' points connect to the 'red' point, i.e. show confidence bands? Thanks,...

...{ cluster2<- survfit(Surv(RFS_days, OV_Had_a_Recurrence_CODE) ~ clusters, data = inputfile) ggsurvplot(cluster2, data = inputfile, risk.table = F, palette = c("red", "black"), ylim=c(0,1), ggtheme = theme_bw(), xlab="Relapse Free Suvival (Days)", main = "Survival curve", pval = TRUE, font.x = 16, font.y = 16, font.tickslab = 14, font.legend =c(14,"plain","black"),...