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2.9 years ago
Hi, I need to streamline ELISA result processing. The input comprises of 4-6 pairs of data: independent value (i.e. compound concentration) + response value (readout from the reader). I found projects for both Python and R. Considering there is only a handful of input values to run curve fitting, is there any particular reason to choose R over Python, or vice versa? Best, Paul
python scikit-learn implementation is quite fast (in my experience much more than doing regression in R). Therefore, better to use python for large datasets. But you have a dataset with limited dimensionality, and R and python libraries for regression have similar proprierties. I think, in this case you can choose whatever you prefer