I find the following Pandas code pretty easy to read: (df .groupby(['a', 'b', 'c'], as_index=False) .agg({'d': sum, 'e': mean, 'f', np.std}) .assign

I find the following Pandas code pretty easy to read: (df .groupby(['a', 'b', 'c'], as_index=False) .agg({'d': sum, 'e': mean, 'f', np.std}) .assign(g=lambda x: x.a / x.c) .query("g > 0.05") .merge(df2, on='a')) There are now methods in pandas to do pretty much anything, so you can chain them together into one easy-to-read manipulation without lots of intermediate variables.