Pandas: df.mul vs df.rmul

Question

Can anybody help me understand the difference (if any) between the two methods: df.mul and df.rmul? The documentation looks identical:

docs for mul

docs for rmul

Answer 1

The documentation is not identical. As stated in the documentation, df.mul(other) is equivalent to df * other, while df.rmul(other) is equivalent to other * df.

This probably doesn't matter for most cases, but it will matter if, e.g., you have a dataframe of object dtype whose elements have noncommutative multiplication. Maybe you wrote a quaternion class and filled a dataframe with quaternions. Someone with more Pandas experience might be able to come up with more practical cases where it matters.