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import pandas as pddata = { "age": [50, 40, 30, 40, 20, 10, 30], "qualified": [True, False, False, False, False, True, True]}df = pd.DataFrame(data)newdf = df.mask(df["age"] > 30)print(newdf)age qualified 0 NaN NaN 1 NaN NaN 2 30.0 0.0 3 NaN NaN 4 20.0 0.0 5 10.0 1.0 6 30.0 1.0