GroupBy pandas DataFrame and select most common value

Question

I have a data frame with three string columns. I know that the only one value in the 3rd column is valid for every combination of the first two. To clean the data I have to

Answer 1

If you don't want to include NaN values, using Counter is much much faster than pd.Series.mode or pd.Series.value_counts()[0]:

def get_most_common(srs):
    x = list(srs)
    my_counter = Counter(x)
    return my_counter.most_common(1)[0][0]

df.groupby(col).agg(get_most_common)

should work. This will fail when you have NaN values, as each NaN will be counted separately.