search for: scale_color_manual

...df ggplot(df,aes(Year,Flow,group=Stat,colour=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&...

...but not for the lines. Attached the sample code and sample data. I tried to add "color" arguments to the "geom_smooth" and "geom_line" and doesn't work. I think the problem is I need to separate the color schemes for lines and points, but I can't use multiple scale_color_manual statement in one ggplot. Jun Shen ####sample data######### df1 <- structure(list(Y2 = c(0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L), X = c(27L, 8L, 33L, 53L, 100L, 52L, 9L, 60L, 50L, 10L, 3L, 30L, 50L, 15L, 90L, 48L, 110L, 75L, 72L, 150L, 47L, 30L),...

...olNum] head(trainset); str(df) svm_model<- svm(z ~ ., data = trainset, type = "C-classification", kernel = "linear", scale = FALSE) #! plot p = ggplot(data = trainset, aes(x=x, y=y, color=z)) + geom_point() + scale_color_manual(values = c("red", "blue")) # show decision boundaries w = t(svm_model$coefs) %*% svm_model$SV # %*% = matrix multiplication slope_1 = -w[1]/w[2] intercept_1 = svm_model$rho / w[2] p = p + geom_abline(slope = slope_1, intercept = intercept_1) ### here we go: can I use a shaded a...

also from this site: https://plotly.com/ggplot2/geom_ribbon/ I get the answer is geom_ribbon but I am still missing something ``` #! plot p = ggplot(data = trainset, aes(x=x, y=y, color=z)) + geom_point() + scale_color_manual(values = c("red", "blue")) # show support vectors df_sv = trainset[svm_model$index, ] p = p + geom_point(data = df_sv, aes(x=x, y=y), color="purple", size=4, alpha=0.5) # show hyperplane (decision boundaries are off set by 1/w[2]) w = t(svm_model$coe...

...background = element_blank())+ >> ????theme(axis.line = element_line(colour = "black"))+ >> ?? theme(axis.text=element_text(size=18))+ >> ?? theme(axis.title=element_text(size=20))+ >> ????ylab("Anteil BFF an LN [%]") +xlab("Jahr")+ >> ????scale_color_manual(values=c("red","dark green"), labels=c("?LN", >> "BIO"))+ >> ????scale_fill_manual(values=c("red","dark green"), labels= c("?LN", >> "BIO"))+ >> ????theme(legend.title = element_blank())+ >&gt...

...l<- svm(z ~ ., > data = trainset, > type = "C-classification", > kernel = "linear", > scale = FALSE) > > #! plot > p = ggplot(data = trainset, aes(x=x, y=y, color=z)) + > geom_point() + scale_color_manual(values = c("red", "blue")) # show > decision boundaries w = t(svm_model$coefs) %*% svm_model$SV # %*% = > matrix multiplication > slope_1 = -w[1]/w[2] > intercept_1 = svm_model$rho / w[2] > p = p + geom_abline(slope = slope_1, intercept = intercept_1) ### here we...

A stupid question but does anyone know how to express the actual colours used by the main Canadian political parties? I want to do a couple of ggplot2 plots and have lines or rectangles that accurately reflect the party colours. I can probably play around with RColorBrewer or something to figure it out but if some some already has got them it would save me some time especially with the NDP

...niendo el gradiente. He pensado, también, en crear una nueva variable, combinación de las dos, que me permitiera hacer eso mismo, pero no encuentro la forma. Gracias por vuestra ayuda, una vez más, Manuel ggplot(legend=FALSE)+ geom_point(data=NCDS,aes(x=lon,y=lat,color= PA),shape=15,size=1) + scale_color_manual(values=c("white","grey70"))+ geom_path(data=map_data('world'), aes(x=long, y=lat,group=group)) ggplot(legend=FALSE)+ geom_point(data=NCDS,aes(x=lon,y=lat,color= ExtTG7085),shape=15,size=1) + # PTP o FTP scale_colour_gradient2(low = "white",high="RED...

...entage, group=Enrolled_by, color=Enrolled_by, shape=Enrolled_by, fill=Enrolled_by)) + geom_line() + geom_point(size=3.5) + scale_y_continuous(breaks=seq(0, 100, 10), limits=c(0, 100), labels=paste(seq(0, 100, 10), "%", sep="")) + scale_color_manual(values=c("orange", "red"), breaks=c("PCT_ENR_FALL1", "PCT_ENR_FALL2"), labels=c("1st fall", "2nd fall")) + scale_fill_manual(values=c("orange", "red"), bre...

...group, i need to plot two, one type is solid, the other type is dotted. how to do it? I tried a color plot with the following code. what should i change "color" to? pb <- ggplot(data, aes(x = a, y = b, color = char, linetype = factor(sex))) p0 <- pb + scale_color_manual(values = c("#00FFFF", "#FFFF00", "#00FF00")) + scale_linetype_manual(breaks=c("0","1"), values=c(1,2), labels = c("male", "female")) + geom_smooth(method = "lm", se = FALSE, # Don't add shaded con...

...area between lines in ggplot2 > > > > also from this site: https://plotly.com/ggplot2/geom_ribbon/ > > I get the answer is geom_ribbon but I am still missing something ``` #! plot > > p > > = ggplot(data = trainset, aes(x=x, y=y, color=z)) + > > geom_point() + scale_color_manual(values = c("red", "blue")) # show > > support vectors df_sv = trainset[svm_model$index, ] p = p + > > geom_point(data = df_sv, aes(x=x, y=y), > > color="purple", size=4, alpha=0.5) # show hyperplane > > (decision > > bou...

...Subject: Re: [R] How to shade area between lines in ggplot2 > > also from this site: https://plotly.com/ggplot2/geom_ribbon/ > I get the answer is geom_ribbon but I am still missing something ``` #! plot > p > = ggplot(data = trainset, aes(x=x, y=y, color=z)) + > geom_point() + scale_color_manual(values = c("red", "blue")) # show > support vectors df_sv = trainset[svm_model$index, ] p = p + > geom_point(data = df_sv, aes(x=x, y=y), > color="purple", size=4, alpha=0.5) # show hyperplane > (decision > boundaries are off set by 1...

...width=1) + > theme(panel.background = element_blank())+ > theme(axis.line = element_line(colour = "black"))+ > theme(axis.text=element_text(size=18))+ > theme(axis.title=element_text(size=20))+ > ylab("Anteil BFF an LN [%]") +xlab("Jahr")+ > scale_color_manual(values=c("red","dark green"), labels=c("?LN", > "BIO"))+ > scale_fill_manual(values=c("red","dark green"), labels= c("?LN", > "BIO"))+ > theme(legend.title = element_blank())+ > theme(legend.text=ele...

..., formula = y ~ x + I(x^2),linewidth=1) + theme(panel.background = element_blank())+ theme(axis.line = element_line(colour = "black"))+ theme(axis.text=element_text(size=18))+ theme(axis.title=element_text(size=20))+ ylab("Anteil BFF an LN [%]") +xlab("Jahr")+ scale_color_manual(values=c("red","dark green"), labels=c("?LN", "BIO"))+ scale_fill_manual(values=c("red","dark green"), labels= c("?LN", "BIO"))+ theme(legend.title = element_blank())+ theme(legend.text=element_text(size=20))+ sca...

..."identity", notch=TRUE ) + theme(panel.background = element_blank())+ theme(axis.line = element_line(colour = "black"))+ theme(axis.text=element_text(size=18))+ theme(axis.title=element_text(size=20))+ ylab("Anteil BFF an LN [%]") +xlab("Jahr")+ scale_color_manual(values=c("red","darkgreen"), labels=c("?LN", "BIO"))+ scale_fill_manual(values=c("red","darkgreen"), labels= c("?LN", "BIO"))+ theme(legend.title = element_blank())+ theme(legend.text=element_text(size=20)) p1<...

...ines in ggplot2 > > > > > > also from this site: https://plotly.com/ggplot2/geom_ribbon/ > > > I get the answer is geom_ribbon but I am still missing something ``` > > > #! plot p = ggplot(data = trainset, aes(x=x, y=y, color=z)) + > > > geom_point() + scale_color_manual(values = c("red", "blue")) # > > > show support vectors df_sv = trainset[svm_model$index, ] p = p + > > > geom_point(data = df_sv, aes(x=x, y=y), > > > color="purple", size=4, alpha=0.5) # show > > > hyperplane (de...

...are given in the plot do not match with the values specified in the codes given below. Your helps highly appreciated. Greg library(ggplot2) p <- ggplot(a,aes(x=NO_BMI_FI_beta ,y=FI_beta ,color= Super.Pathway))+ theme_bw() +theme(panel.border=element_blank()) + geom_point(size=3) p2<-p+scale_color_manual(name="Super.Pathway", labels=c("Amino Acid", "Cofactors and Vitamins", "Carbohydrate", "Energy", "Lipid", "Peptide", "Nucleotide"), values=c("Amino Acid"="red", "Cofactors and Vitamins"=...

...und = element_blank())+ > > theme(axis.line = element_line(colour = "black"))+ > > theme(axis.text=element_text(size=18))+ > > theme(axis.title=element_text(size=20))+ > > ylab("Anteil BFF an LN [%]") +xlab("Jahr")+ > > scale_color_manual(values=c("red","darkgreen"), labels=c("?LN", "BIO"))+ > > scale_fill_manual(values=c("red","darkgreen"), labels= c("?LN", "BIO"))+ > > theme(legend.title = element_blank())+ > > theme(legen...

...or gradient, I would like make the values between A and B a set color, between B and C another color, and so on. That's where I'm having an issue, because the values are all continuous data, and it seems like the only thing which will let me get anything close to what I would like (such as scale_color_manual) requires a discrete dataset. I've reached an impasse with this and could really use some advice. Thanks everyone! A -- Adrienne Wootten Graduate Research Assistant State Climate Office of North Carolina Department of Marine, Earth and Atmospheric Sciences North Carolina State University --...

...dentity", notch=TRUE ) + theme(panel.background = element_blank())+ theme(axis.line = element_line(colour = "black"))+ theme(axis.text=element_text(size=18))+ theme(axis.title=element_text(size=20))+ ylab("Anteil BFF an LN [%]") +xlab("Jahr")+ scale_color_manual(values=c("red","darkgreen"), labels=c("?LN", "BIO"))+ scale_fill_manual(values=c("red","darkgreen"), labels= c("?LN", "BIO"))+ theme(legend.title = element_blank())+ theme(legend.text=element_text(size=20)) p1...