I have a dataset that looks like this:
> averages
compound control.0 control.30 surgery.0 surgery.30
1. A 3.609958 3.578200086 3.556325 3.669107598
2. B 4.984090 4.798330495 4.965342 4.812247664
I want to make a graph for only compound A that plots two lines- one connecting (0, control.0) to (30, control.30) and one that plots (0, surgery.0) to (30, surgery.30). I also have 200 compounds so I would ideally like to be able to have the program go down the list and spit out a graph for each compound without me manually going in and changing the line number. How would I go about doing this?
For two line segments per graph, use this:
with(subset(averages, compound=="A"), plot(c(0,30,NA,0,30),c(control.0,control.30,NA,surgery.0,surgery.30), type="l"))
Then change the subset condition to create a loop.
Related
I want to plot the data by using function(). My data consists of 4 vectors, say a, b, c and d.
I have to plot them by choice of vector at that time.
For example
i want to plot vector a and c then graph must have 2 lines....
if i want 2 plot all 4 vectors then there must be 4 lines in graph.
Till I have tried switch() but i think thats not suitable related to my work.
Is it even possible to write such code in an anonymous function ?
If yes, what is the right way, and if not, is there any workaround ?
I have the following basic code. The first line sums p along dimension 1 to create a 1 x column array. The next line plot A. Unfortunately, it seems that Julia assumes it must plot many lines (in this case just points) along dimension 2.
A = sum(p,dims = 1)
plot(A)
So, my question is, how can I plot a simple line when the data is in a 1 x column array?
I assume you use Plots.jl. The following is from Plots.jl's documentation.
If the argument [to plot] is a "matrix-type", then each column will map to a series, cycling through columns if there are fewer columns than series. In this sense, a vector is treated just like an "nx1 matrix".
The number of series plot(a) tries to plot is the number of columns in a.
To get a single series, you can do one of the followings
plot(vec(a)) # `vec` will give you a vector view of `a` without an allocation
plot(a') # or `plot(transpose(a))`. `transpose` does not allocate a new array
plot(a[:]) # this allocates a new array so you should probably avoid it
I have a dataset that looks like the one shown in the code.
What I am guaranteed is that the "(var)x" (domain) of the variable is always between 0 and 1. The "(var)y" (co-domain) can vary but is also bounded, but within a larger range.
I am trying to get an average over the "(var)x" but over the different variables.
I would like some kind of selective averaging, not sure how to do this in R.
ax=c(0.11,0.22,0.33,0.44,0.55,0.68,0.89)
ay=c(0.2,0.4,0.5,0.42,0.5,0.43,0.6)
bx=c(0.14,0.23,0.46,0.51,0.78,0.91)
by=c(0.1,0.2,0.52,0.46,0.4,0.41)
qx=c(0.12,0.27,0.36,0.48,0.51,0.76,0.79,0.97)
qy=c(0.03,0.2,0.52,0.4,0.45,0.48,0.61,0.9)
a<-list(ax,ay)
b<-list(bx,by)
q<-list(qx,qy)
What I would like to have something like
avgd_x = c(0.12,0.27,0.36,0.48,0.51,0.76,0.79,0.97)
and
avgd_y would have contents that would
find the value of ay and by at 0.12 and find the mean with ay, by and qy.
Similarly and so forth for all the values in the vector with the largest number of elements.
How can I do this in R ?
P.S: This is a toy dataset, my dataset is spread over files and I am reading them with a custom function, but the raw data is available as shown in the code below.
Edit:
Some clarification:
avgd_y would have the length of the largest vector, for example, in the case above, avgd_y would be (ay'+by'+qy)/3 where ay' and by' would be vectors which have c(ay(qx(i))) and c(by(qx(i))) for i from 1 to length of qx, ay' and by' would have values interpolated at data points of qx
My data is (sort of) like this:
thing value
a 100
a 101
. .
a 99
b 201
b 202
. .
b 199
I want to compare the median of the values by thing. Normally I would make a boxplot with something like boxplot(value ~ thing, data = table), but there is a catch.
The problem
The number of values of each thing is about 100,000. Consequently I have had to process my table in sections. I process all values for thing a, then all values for thing b, etc.
Is there a way to make a boxplot and then add more plots to it, like using plot and dots? I want to use the base plotting system if possible (to make the plots consistent).
However, if that isn't possible, I guess ggplot2 might have to be the go.
I should add, what I'm hoping to achieve is something like the image here:
http://www.statmethods.net/graphs/images/boxplot1.jpg
Is there a way to get quantmod to draw a square line chart?
I've tried modifying my time series so that each data point is replicated one second before the next datapoint (hoping this would approximate a square line), but quantmod seems to data on the x axis sequentially & evenly spaces without regard to the actually values of x (i.e. the horizontal space between one point an the next is the same whether the delta-T is 1 second or 1 minute).
I suppose I could convert my timeseries from a sparse to a dense one (one entry per second instead of one entry per change in value), but this seems very kludgy and should be unnecessary.
I'm constructing my time series thus:
library(quantmod)
myNumericVector <- c(3,7,2,9,4)
myDateTimeStrings <- paste("2011-10-31", c("5:26:00", "5:26:10", "5:26:40", "5:26:50", "5:27:00"))
myXts <- xts(myNumericVector, order.by=as.POSIXct(myDateTimeStrings))
And drawing the chart like so:
chartSeries(myXts, type="line", show.grid="true", theme=chartTheme("black"))
To illustrate what I have vs. what I want, the result looks like the blue line below but I'd like something more like the green:
Also, for the curious, here is the code that replicates points in the time series such that the gap between one value and the next are as small as possible:
mySquareDateTimes <- rep(as.POSIXct(myDateTimeStrings),2)[-1]
mySquareDateTimes[seq(2,8,by=2)] <- mySquareDateTimes[seq(2,8,by=2)] - 1
mySquareXts <- xts(rep(myNumericVector,each=2)[-10], order.by=mySquareDateTimes)
chartSeries(mySquareXts, type="line", show.grid="true", theme=chartTheme("black"))
The results are less than ideal.
You want a line.type of "step":
chartSeries(myXts, line.type="s")
See ?plot, specifically "type" under ... in the Arguments section (you may want "S" instead of "s").