Q:

plot scatter dots with normalised dot sizes?

Can I ask how to plot the figure? The size of each dot should correspond to its proportion at a particular time. 
Can arrows or continues lines also be used to show the trend instead of discrete dots? The width of the arrow/line will correspond to its proportion at a particular time. Also, it can handle missing data, e.g. set the position of missing data as blank or use a very thin arrow/line for missing data. 
Both python and R are good for me.
Raw data:
Time;Value A;Value A proportion;Value B;Value B proportion
1;5;90%;12;10%
2;7;80%;43;20%
3;7;80%;83;20%
4;8;70%;44;30%
5;10;80%;65;20%

An example of the plot is like this, but I am happy for other dot patterns.

A:

library(ggplot2)
library(reshape2)

myDF <- read.table("~/Desktop/test.txt",header=TRUE,sep=";")
# remove "%"
myDF <- data.frame(lapply(myDF, function(x) as.numeric(sub("%", "", x))) )

meltVar <- melt(myDF,id.vars = c("Time"),measure.vars = c("Value.A","Value.B"))
meltpropr <- melt(myDF,id.vars = c("Time"),measure.vars = c("Value.A.proportion","Value.B.proportion"))
newDF <- as.data.frame(cbind(meltVar,meltpropr[,"value"]))
names(newDF) <- c("Time","variable","value","prop")

ggplot(newDF,aes(x=Time, y=value)) + geom_point(aes(colour=variable , shape=variable, size = prop))

You can play with aes and theme to get the figure as you like.

