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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
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The mul() method multiplies each value in the DataFrame with a specified value. The specified value must be an object that can be multiplied with the values of the DataFrame.
The mul() method of DataFrame object multiplies the elements of a DataFrame object with another DataFrame object, series or any other Python sequence. mul() does an elementwise multiplication of a DataFrame with another DataFrame, a pandas Series or a Python Sequence.
The dot() method of pandas DataFrame class does a matrix multiplication between a DataFrame and another DataFrame, a pandas Series or a Python sequence and returns the resultant matrix.
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.
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