试试看：

# lazy grouping
groups = df.groupby('a')

# where all the rows within a group is NaN
all_na = groups['b'].transform(lambda x: x.isna().all())

# fill global mode
df.loc[all_na, 'b'] = df['b'].mode()[0]

# fill with local mode
mode_by_group = groups['b'].transform(lambda x: x.mode()[0])
df['b'] = df['b'].fillna(mod_by_group)

You are getting the IndexError: index out of bounds because last a column value a3没有对应的B列值，因此没有组可填充。Solution would be have try catch block while fillna and then apply ffill and bfill。以下是代码解决方案。

data_stack = [['a1','b1'],['a1','b2'],['a1','b1'],['a1',np.nan],['a2','b1'], 
['a2','b2'],['a2','b2'],['a2',np.nan],['a2','b2'],['a3',np.nan]]
df_try_stack = pd.DataFrame(data_stack, columns=["a","b"])

# This function will fill na values of group to the mode value
def fillna_group(grp):
    try:
        return grp.fillna(grp.mode()[0])
    except BaseException as e:
        print('Error as no correspindg group: ' + str(e))
df_try_stack["b"] = df_try_stack["b"].fillna(df_try_stack.groupby(["a"]) 
['b'].transform(lambda grp : fillna_group(grp)))
df_try_stack = df_try_stack.ffill(axis = 0)
df_try_stack = df_try_stack.bfill(axis =0)