That's a really bizarre reason not to use R. Python's distribution is about 30MB if I recall. It doesn't really make much sense to convert R to JS or Python, since the semantics are so different.
If you don't want to use R, Pandas in Python provides very powerful data frames (which are likely faster for many cases). However, it depends on NumPy, matplotlib, and a few other libraries, which probably total more than 60 MB.
If you don't want to use R, Pandas in Python provides very powerful data frames (which are likely faster for many cases). However, it depends on NumPy, matplotlib, and a few other libraries, which probably total more than 60 MB.