how to increase labels distance from main plot in heatmaply r - r

I have a simple issue in interactive heatmap in R. I couldn't figure out how to increase margins (distance between x and y labels with main plot) in heatmaply?
I want to add a little bit of space in ylab (province) from heatmap. Could anybody help me?
enter image description here

You can change the margins with heatmaply by using margins
Since you did not provide any code in your question, I will use an example plot using mtcars and changing the y-axis margins
heatmaply(mtcars, margins = c(0, 200, 0, 0))
If you want to move the y-axis labels away from the graph, then that will be trickier. Currently, there doesn't appear to be a way to do this, however, here is a workaround. There is currently now way to move the y-axis labels in heatmaply. Overall, this is a poor workaround but it appears to be the best solution as of right now.
df <- mtcars
#extract the labels on the y axis. In this example mtcars y-axis labels are the row names
df2 <- as.data.frame(rownames(mtcars))
#you then have to add spaces to the end of the labels and then apply this to the dataframe you are using.
rownames(df) <- paste0(df2$`rownames(mtcars)`, " ")
#you can now run heatmaply on the new labels with added spaces
heatmaply(df)
Overall, plotly has some great features however it lacks in tuneability. heatmaply has even fewer features than plotly so it makes it even harder to tune your graph the way you want to.

Related

How to autoscale plot so axis are not cut off?

What is the R equivalent of Python's matplotlib's: plt.tight_layout() function. I keep plotting bar graphs in plotly and the axis labels are constantly cut out. And I want to scale the graphs to match.
N.B I am dynamically producing these graphs with different labels, so can't constantly play with margins to get it to fit.
Below is some fake data that will hopefully illustrate the problem
Organisation<-c("Organisation Alpha","Organisation Beta","Organisation Charlie","Organisation Delta")
Year<-c(2018,2018,2018,2018,2019,2019,2019,2019)
Values<-c(100,50,10,0,20,0,75,70)
Mock_data <- data.frame(Organisation, Year, Values, stringsAsFactors=FALSE)
p<-Mock_data %>% plot_ly(x=~Organisation,y=~Values,type='bar',frame=~Year,colors="Blues")
Think I have managed to resolve the issue:
layout(barmode = 'stack',autosize=F,yaxis=list(title=Title,automargin=TRUE),xaxis=list(automargin=T))

How to increase the interval of labels in geom_text?

I am trying to put labels beside some points which are very close to each other on geographic coordinate. Of course, the problem is overlapping labels. I have used the following posts for reference:
geom_text() with overlapping labels
avoid overlapping labels in ggplot2 charts
Relative positioning of geom_text in ggplot2?
The problem is that I do not want to relocate labels but increase the interval of labeling (for example every other 10 points).
I tried to make column as alpha in my dataframe to make unwanted points transparent
[![combined_df_c$alpha=rep(c(1,rep(0,times=11)),
times=length(combined_df_c$time)/
length(rep(c(1,rep(0,times=11)))))][1]][1]
I do not know why it does not affect the plot and all labels are plotted again.
The expected output is fewer labels on my plot.
You can do this by sequencing your dataframe for the labs of geom_text.
I used the build-in dataset mtcars for this, since you did not provide any data. With df[seq(1,nrow(df),6),] i slice the data with 6-steps. This are the labels which get shown in your graph afterwards. You could use this with any steps you want. The sliced dataframe is given to geom_text, so it does not use the original dataset anymore, just the sliced one. This way the amount of points for the labels and the amount of labels are equal.
df <- mtcars
labdf<- df[seq(1,nrow(df),6),]
ggplot()+
geom_point(data=df, aes(x=drat, y=seq(1:length(drat))))+
geom_text(data=labdf,
aes(x=drat, y=seq(1:length(drat))), label=labdf$drat)
The output is as expected: from 32 rows, just 6 get labeled.
You can easily adjust the code for your case.
also: you can put the aes in ggplot() which may be more useful if you use more then just gemo_point. I made it like this, so i can clarify: there is a different dataset used on geom_text()

Plotting a scaled version of a variable using ggplot2. Need to show the scale too

I am trying to plot a variable over time using ggplot2.
My current plot looks like this:
However, I want the scaled values with significant numbers shown on the axis. The scale needs to be shown at the top left corner. Something like:-
I don't want to scale the plot. The axis needs to show the significant numbers and the exponential scale needs to be shown at the top left.
Is this what you had in mind (my own MWE):
library(ggplot2)
df <- data.frame( x=rnorm(10), y=seq(1e8,10e8,by=1e8))
p <- ggplot(df)+
geom_point(aes(x=x,y=y/1e8))+
geom_text(aes(x=-Inf,y=Inf,label=as.character(paste("10^8"))), parse=T, hjust=1, vjust=0.8, size=5/14*10)+
scale_y_continuous(name="y")
gt <- ggplot_gtable(ggplot_build(p))
gt$layout$clip[gt$layout$name == "panel"] <- "off"
grid.draw(gt)
Basically divide by the exponent, and then write it manually at the top left. The parse=T renders the power as an actual power. That factor of 5/14 was mentioned on another post as being the rough factor by which geom_text size relates to the size you set text to be elsewhere on the graph (no idea why but I've found doing 5/14*text-size-you-want gives a decent looking geom_text). Finally the last three lines prevent the off-plot-panel text being cropped out (you wouldn't see the geom_text otherwise). Hope this gives you something to work with.

Manually creating an object that looks like a heatmap color key

I'm working on trying to create a key for a heatmap, but as far as I know, I cannot use the existing tools for adding a legend since I've generated the colors myself (I manually turn a scaled variable into rgb values for a short rainbow ( [255,0,0] to [0,0,255] ).
Basically, all I want to do is use the rightmost 10th of the screen to create a rectangle with these 10 colors: "#0000FF", "#0072FF", "#00E3FF", "#00FFAA", "#00FF38", "#39FF00", "#AAFF00", "#FFE200", "#FF7100", "#FF0000"
with three numerical labels - at 0, max/2, and max
In essence, I want to manually produce an object that looks like a rudimentary heatmap color key.
As far as I know, split.screen can only split the screen in half, which isn't what I'm looking for. I want the graphic I already know how to produce to take up the leftmost 90% of the screen, and I want this colored rectangle to take up the other 10%.
Thanks.
EDIT: I greatly appreciate the advice about the best way to the the plot - that said, I still would like to know the best way to do the task originally asked - creating the legend by hand; I already am able to produce the exact heatmap graphic that I'm looking for - the false coloring wasn't the only problem with ggplot that I was having - it was just the final factor convincing me to switch. I need a non ggplot solution.
EDIT #2: This is close to the solution I am looking for, except this only goes up to 10 instead of accepting a maximum value as a parameter (I will be running this code on multiple data-sets, all with different maximum values - I want the legend to reflect this). Additionally, if I change the size of the graph, the key falls apart into disconnected squares.
Take a look at the layouts function (link). I think you want something like this:
layout(matrix(c(1,2), 1, 2, byrow = TRUE), widths=c(9,1))
## plot heatmap
## plot legend
I would also recommend the ggplot2 package and the geom_tile function which will take care of all of this for you.
Assuming your data is in a data frame with the x and y coordinates and heatmap value (e.g. gdat <- data.frame(x_coord=c(1,2,...), y_coord=c(1,1,...), val=c(6,2,...))) Then you should be able to produce your desired heat map plot with the following ggplot command:
ggplot(gdat) + geom_tile(aes(x=x_coord, y=y_coord, fill=val)) +
scale_fill_gradient(low="#0000FF", high="#FF0000")
To get your data into the following format you may want to look into the very useful reshape2 package.
Given a script no ggplot restriction on this answer here is how one could produce the plot with just base R.
colors <- c("#0000FF", "#0072FF", "#00E3FF", "#00FFAA", "#00FF38",
"#39FF00", "#AAFF00", "#FFE200", "#FF7100", "#FF0000")
layout(matrix(c(1,2), 1, 2, byrow = TRUE), widths=c(9,1))
plot(rnorm(20), rnorm(20), col=sample(colors, 20, replace=TRUE))
par(mar=c(0,0,0,0))
plot(x=rep(1,10), y=1:10, col=colors, pch=15, cex=7.1)
You may have to adjust the cex for your device.

Mosaic plot with labels in each box showing a name and percentage of all observations

I would like to create a mosaic plot (R package vcd, see e.g. http://cran.r-project.org/web/packages/vcd/vignettes/residual-shadings.pdf ) with labels inside the plot. The labels should show either a combination of the various factors or some custom label and the percentage of total observations in this combination of categories (see e.g. http://i.usatoday.net/communitymanager/_photos/technology-live/2011/07/28/nielsen0728x-large.jpg , despite this not quite being a mosaic plot).
I suspect something like the labeling_values function might play a role here, but I cannot quite get it to work.
library(vcd)
library(MASS)
data("Titanic")
mosaic(Titanic, labeling = labeling_values)
Alternative ways to represent two variables with categorical data in a friendly way for non-statisticians are also welcome and are acceptable solutions.
Here is an example of adding proportions as labels. As usual, the degree of customization of a plot is a matter of taste, but this shows at least the principles. See ?labeling_cells for further possibilities.
labs <- round(prop.table(Titanic), 2)
mosaic(Titanic, pop = FALSE)
labeling_cells(text = labs, margin = 0)(Titanic)

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