search for: scale_fill_gradient

..., 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=HProbCount)) + geom_tile()...

Hi, i get no success change the title of the "fill" (colour) legend and the defintion of "levels". Have anybody a hint how i can do this. df <- data.frame(variable=sample(c("A","B","C"),1000,replace=T,prob=c(0.22,0.28,0.5)),group=gl(2,500)) p <- ggplot(df, aes(x = variable)) p + geom_histogram(aes(y= ..count.. /

Given a data frame with a continuous variable and a factor. I would like to generate a histogram of the continuous variable, where each bar is filled with different colors according to the percentage of factor values falling into this region of the continuous variable. I looked into packages like 'lattice' and 'ggplot2'. Searching R-help revealed that 'histogram' is

...csv file with lat and lon coordinates) sites <- data.frame(read.csv(?/your/path/to/pointfile.csv?)) #Now make the map ggplot(data=df, aes(y=Latitude, x=Longitude)) + geom_raster(aes(fill=MAP)) + geom_point(data=sites, aes(x=x, y=y), color=?white?, size=3, shape=4) + theme_bw() + coord_equal() + scale_fill_gradient(?MAP (mm/yr)?, limits=c(0,2500)) + theme(axis.title.x = element_text(size=16), axis.title.y = element_text(size=16, angle=90), axis.text.x = element_text(size=14), axis.text.y = element_text(size=14), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.position = ?right?,...

...sites <- data.frame(read.csv(?/your/path/to/pointfile.csv?)) > > #Now make the map > ggplot(data=df, aes(y=Latitude, x=Longitude)) + > geom_raster(aes(fill=MAP)) + > geom_point(data=sites, aes(x=x, y=y), color=?white?, size=3, shape=4) + > theme_bw() + > coord_equal() + > scale_fill_gradient(?MAP (mm/yr)?, limits=c(0,2500)) + > theme(axis.title.x = element_text(size=16), > axis.title.y = element_text(size=16, angle=90), > axis.text.x = element_text(size=14), > axis.text.y = element_text(size=14), > panel.grid.major = element_blank(), > panel.grid.minor = element_blank...

...or of the borders between regions white size = 0.15) + #sets the thickness of the boarder lines coord_map("polyconic") + #sets the coordinates to polyconic (rounded lat and long) scale_fill_gradient(name = "Children Reached", #sets the gradient of the value scale: names the scale low = grey_2, #color of the low end high = orange_1) + #color of the high end...

Dear all, I am trying to plot a matrix I have? as an image str(matrixToPlot) ?num [1:21, 1:66] 0 0 0 0 0 0 0 0 0 0 . ?that contains only 0s and 1s, where the xlabel will be Labeled as str(xLabel) ?num [1:66] 1e+09 1e+09 1e+09 1e+09 1e+09 ... and the yLabels will be labeled as str(yLabel) ?num [1:21] -88 -87 -86 -85 -84 -83 -82 -81 -80 -79 ... I have found on the internet that I can do

...if ggplot can somehow generate it?): A B value T1 T2 0.347 T1 T3 0.669 T2 T3 0.214 T2 T1 0.347 T3 T1 0.669 T3 T2 0.214 T1 T1 1 T2 T2 1 T3 T3 1 Then I would run sorted<-data[order(data$A, data$B), ] ggplot(sorted, aes(A, B)) + geom_tile(aes(fill = value), colour = "white") + scale_fill_gradient(low = "black", high = "red") + I have solved this, but in (what I assume is) a really bad way involving for loops. There must be a better way to get form the first data frame above to the second! Cheers, Till -- Till Bayer 4700 King Abdullah University for Science and T...

...m=7) YlOrBr <- c("#FFFFD4", "#FED98E", "#FE9929", "#D95F0E", "#993404") ggmap(MyMap) + stat_density_2d(data=s_rit, aes(x=lon, y=lat, fill=..level.., alpha=..level..), geom="polygon", size=0.01, bins=16) + scale_fill_gradient(low="red", high="green") + scale_alpha(range = c(0,0.3), guide=FALSE) The above computes 2d density but it does not take the score (the weight into account). To do a weighted KDE I do : library(ks) mydensity <- kde(x = s_rit[,c(2,3)],w = s_rit$score) This computes a wei...

I am very new to R and don't have any computer program experience whatsoever. I am trying to generate a heatmap of the following data: Phylum,AI,AJT,BY,GA,Grt,Sm Acidobacteria,0.5,0.7,2.7,0.1,2.6,1.0 Actinobacteria,33.7,65.1,9.7,2.0,3.9,2.1 Bacteroidetes,9.7,5.6,0.7,13.2,41.1,21.6 CCM11b,0.0,0.0,0.0,0.0,0.0,0.1 Chlamydiae,0.1,0.1,0.0,0.0,1.0,0.2

...ath/to/pointfile.csv?)) > > > > #Now make the map > > ggplot(data=df, aes(y=Latitude, x=Longitude)) + > > geom_raster(aes(fill=MAP)) + > > geom_point(data=sites, aes(x=x, y=y), color=?white?, size=3, shape=4) + > > theme_bw() + > > coord_equal() + > > scale_fill_gradient(?MAP (mm/yr)?, limits=c(0,2500)) + > > theme(axis.title.x = element_text(size=16), > > axis.title.y = element_text(size=16, angle=90), > > axis.text.x = element_text(size=14), > > axis.text.y = element_text(size=14), > > panel.grid.major = element_blank(), > > pa...

Hello useRs, I have some problems when I try to plot a lattice. The lattice has 200 columns (X value) and 5 rows (Y value), with a total of 1000 squares. I want to plot this lattice with the squares having different colours according to a variable value. The variable I want to plot is cover value of a shrub, and it has values between 0 and 1. I want to plot the squares with value 1,

...de, he y values are in alphabetical order, but I want it in month order. The code is: library(reshape) library(ggplot2) library(scales) p <- ggplot(data.m, aes(variable, Month)) + geom_tile(aes(fill = value), colour = "white") p + scale_fill_gradient(low = "white", high = "black") Thank you! The used data is: Month variable value 1 Jan 1961 87.6666667 2 Feb 1961 133.6666667 3 Mar 1961 113.6666667 4 Apr 1961 50.6666667 5 May 1961 7.5000000 6 Jun 1961 0.0000000...

...sites <- data.frame(read.csv(?/your/path/to/pointfile.csv?)) > > #Now make the map > ggplot(data=df, aes(y=Latitude, x=Longitude)) + > geom_raster(aes(fill=MAP)) + > geom_point(data=sites, aes(x=x, y=y), color=?white?, size=3, shape=4) + > theme_bw() + > coord_equal() + > scale_fill_gradient(?MAP (mm/yr)?, limits=c(0,2500)) + > theme(axis.title.x = element_text(size=16), > axis.title.y = element_text(size=16, angle=90), > axis.text.x = element_text(size=14), > axis.text.y = element_text(size=14), > panel.grid.major = element_blank(), > panel.grid.minor = element_blank...

..._colour_brewer p * Scales now automatically shrink to what is actually displayed on the plot, not the underlying data used for statistical transformation. If you want the old behaviour, supply `shrink = FALSE` to the facetting specification. (Fixes #125) * `scale_colour_gradient` and `scale_fill_gradient` now use a colour scheme with constant hue but varying chroma and luminance. This is better because it creates a natural ordering inline with the order of the colour values. FACETS * Converted from proto to S3 objects, and class methods (somewhat) documented in `facet.r`. This should make i...

..._colour_brewer p * Scales now automatically shrink to what is actually displayed on the plot, not the underlying data used for statistical transformation. If you want the old behaviour, supply `shrink = FALSE` to the facetting specification. (Fixes #125) * `scale_colour_gradient` and `scale_fill_gradient` now use a colour scheme with constant hue but varying chroma and luminance. This is better because it creates a natural ordering inline with the order of the colour values. FACETS * Converted from proto to S3 objects, and class methods (somewhat) documented in `facet.r`. This should make i...

...;t create a legend, unless you tell it what > > > labels it should use - there's an example at > > > http://had.co.nz/ggplot2/scale_identity.html. Otherwise, if you have > > > a continuous scale and you want something that works in black and > > > white, p + scale_fill_gradient(low="white", high="black") might be > > > easier. > > > > > > Hadley > > > > > > > > >> > > >> > y$color = factor(y$Fnd) > > >> > y$color = c("black","darkgray","light...