Plot With Conditional Colors Based on Values in R

Plot with conditional colors based on values in R

The argument col will set the colours, you could use this in conjunction with an ifelse statement. See ?plot for more details.

# using base plot
plot(x,y,xlab="PC1",ylab="PC2", col = ifelse(x < 0,'red','green'), pch = 19 )

To do the same thing in ggplot2.

#using ggplot2
library(ggplot2)
ggplot(np_graph) + geom_point(aes(x = C1, y = C2, colour = C1 >0)) +
  scale_colour_manual(name = 'PC1 > 0', values = setNames(c('red','green'),c(T, F))) +
  xlab('PC1') + ylab('PC2')

Plot with conditional colors based on values in hist

You could determine the colors according to the mid-point of each bin.

Sample <- rnorm(2500, 1000, 20)
h <- hist(Sample, plot = FALSE)
hist(Sample, col = ifelse(h$mids < 980, 'red', 'green'))

R - How to conditionally color the values of a data.frame and make a plot

Simply add col.data=ifelse(tabRet<0,'red','black'), after col.rownames="Darkblue", to your code

Plot a line chart with conditional colors depending on values

Use segments instead of lines.

The segments function will only add to an existing plot. To create a blank plot with the correct axes and limits, first use plot with type="n" to draw "nothing".

x0 <- seq(1, 10, 0.1)
colour <- ifelse(sin(seq(from=1, to=10,by=0.1))>0.5,"red","blue")

plot(x0, sin(x0), type="n")
segments(x0=x0, y0=sin(x0), x1=x0+0.1, y1=sin(x0+0.1), col=colour)

See ?segments for more detail.

Plot conditional colors based on rows

Hi this way works for me using ifelse, let me know what you think:

outlier <- sample(1:100, 50)
data <- data.frame(x = 1:100, y = rnorm(n = 100))
plot(
  data[ ,1], data[ ,2]
  ,col = ifelse(row.names(data) %in% outlier, "red", "blue")
  ,type = "h"
)

Color data points in R when a condition is met

Add a column in the dataframe and use it in color :

library(ggplot2)

df$col = ifelse(df$pvalue < 0.05,'red', 'black')

ggplot(data=df)+
  geom_jitter(aes(x=as.factor(Phenotype), y=Genic_enrichment, color = col)) +
  theme_classic()+
  geom_vline(xintercept = 0, linetype = 2) +
  geom_hline(yintercept = 0, linetype = 2) +
  theme(axis.text.x=element_text(angle = 90, vjust = 0.5, hjust=1)) + 
  scale_x_discrete(guide = guide_axis(check.overlap = TRUE))  +
  scale_color_identity()

How to conditionally highlight points in ggplot2 facet plots - mapping color to column

You should put color=ifelse(y<0, 'red', 'black') inside the aes(), so color will be set according to y values in each facet independently. If color is set outside the aes() as vector then the same vector (with the same length) is used in both facets and then you get error because length of color vector is larger as number of data points.

Then you should add scale_color_identity() to ensure that color names are interpreted directly.

ggplot(df) + geom_point(aes(x, y, color=ifelse(y<0, 'red', 'black'))) + 
   facet_grid(case ~. ,)+scale_color_identity()

R - setting manual color based on conditional value

You could simply change your y to ..y.. in your aes. Although it is probably best to aggregate your data before hand and use geom_bar similar to the post you linked. This should work:

ggplot(dnow,aes(x=x, y=y)) + stat_summary(fun.y=mean, geom="bar", aes(fill = ..y.. > 0.5), position=position_dodge(1)) + 
  stat_summary(fun.data = mean_se,geom="errorbar", color="grey40",position=position_dodge(1), width=.2) + 
  geom_hline(yintercept = 0.5) + labs(y="Mean Agreement") + theme_bw() +
  theme(panel.grid.major = element_blank(),panel.grid.minor = element_blank(), axis.title.y=element_blank()) + 
  scale_fill_manual(values = c('red', 'green')) + coord_flip()

..y.. refers to the computed mean from fun.y.

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