Let me preface this by saying I am not an expert in either R nor pgfplots but I will show you some working examples and you can decide whether or not these can or will work for you.
Code:
\documentclass[a4paper,11pt]{article}
\usepackage{pgfplots}
% This is a minimum working example of something I could use in a LaTeX document to produce a decent plot
\begin{document}
\begin{figure}[htp]
\centering
\begin{tikzpicture}
\begin{axis}[
%This is where I define my title, x and y-axis labels, grid type, etc...
title={\tiny{I-V Curves of MOSFET}},
xlabel={\tiny{$V_{DS}(V)$}},
ylabel={\tiny{$I_{D}(A)$}},
grid=major,
legend pos=outer north east,
]
% The x= and y= are both columns in my data file 'procedure_1a_iv_final', which is in my working directory
\addplot [black] table [x={Vds}, y={Vgs200}] {procedure_1a_iv_final};
\addlegendentry{\tiny{$V_{GS}=2.00V$}}
\addplot [gray] table [x={Vds}, y={Vgs205}] {procedure_1a_iv_final};
\addlegendentry{\tiny{$V_{GS}=2.05V$}}
\addplot [brown] table [x={Vds}, y={Vgs210}] {procedure_1a_iv_final};
\addlegendentry{\tiny{$V_{GS}=2.10V$}}
\addplot [violet] table [x={Vds}, y={Vgs215}] {procedure_1a_iv_final};
\addlegendentry{\tiny{$V_{GS}=2.15V$}}
\end{axis}
\end{tikzpicture}
% I can caption the plot or figure and refer to it later in my write-up using \ref{}
\caption{Put your caption here}
\label{iv:curves}
\end{figure}
\end{document}
Now, for the same plot in R. You can either just use the R interpreter similar to Pythons' or R studio. But, in essence you build the plot. I could write a script not unlike a Bash script but I prefer R studio(though I typically shy away from IDE's).
Code:
> curves <- read.table("procedure_1a_iv_final", header=TRUE, sep="")
> x <- curves$Vds
> plot(x, curves$Vgs215, col="blue", type="l", ann=FALSE)
> lines(x, curves$Vgs210, col="red", type="b")
> lines(x, curves$Vgs205, col="orange", type="l")
> lines(x, curves$Vgs200, col="yellow")
> title("MOSFET I-V Curves", xlab="Vds Voltage(V)", ylab="Id Current(A)")
Notice, I said 'build' above. This is because plot() by itself begins a new plot. The lines() function will add additional curves to the existing plot.
I myself have just begun to become familiar with R and I really like it. You can import data from Excel, csv files, databases, directly off the web, plain text files containing data(as I have done in the examples above), etc. Plus, there is built-in functionality to normalize the data, find standard deviation, etc.
Anyway, I hope this helps, or at least gives you a better idea of some other options apart from LabPlots. If you have any additional questions, let me know and I will try to answer them.
Regards
