Efficient solution for forward filling missing values in a pandas dataframe column?

Question

I need to forward fill values in a column of a dataframe within groups. I should note that the first value in a group is never missing by construction. I have the following

Answer 1

Using ffill() directly will give the best results. Here is the comparison

%timeit df.b.ffill(inplace = True)
best of 3: 311 µs per loop

%timeit df['b'] = df.groupby('a')['b'].transform(lambda x: x.fillna(method='ffill'))
best of 3: 2.34 ms per loop

%timeit df['b'] = df.groupby('a')['b'].fillna(method='ffill')
best of 3: 4.41 ms per loop