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.Q: Grouping by multiple columns in pandas groupby My pandas dataframe is like this: import pandas as pd import numpy as np df = pd.DataFrame({'a': ['1', '1', '2', '2', '2', '2', '2', '3', '3', '3', '3', '3'], 'b': ['a', 'a', 'a', 'a', 'a', 'a', 'b', 'a', 'a', 'a', 'a', 'b'], 'c': ['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'y'], 'd': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], 'e': ['y', 'y', 'y', 'y', 'y', 'y', 'y', 'y', 'y', 'y', 'y', 'z'], 'f': [np.nan, 'a', 'b', 'b', 'b', 'c', np.nan, 'a', 'b', 'b', 'c', 'c']}) df = df.dropna(inplace=True) What I need is to group the rows that share the same values in column a, b, and c. The result should be like this: grouped_df = pd.DataFrame({'a': ['1', '2', '3', '3'], 'b': ['a', 'a', 'a', 'b'], 3e33713323


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