如何从具有特定值的 pandas DataFrame 数组列中选择行

Question

我有带有数组列的熊猫数据框：id,classes,text71,`["performer_146", "performer_42"]`,`adipiscing urna. molestie `72,["performer_42"],`a ligula odio elementum, neque suscipit. egestas Maecenas`73,["performer_146"],`vestibulum orci nec vestibulum, ligula orci et mauris lobortis, et Aliquam`74,["performer_0"],tincidunt non interdum nunc ultrices mi accumsan elementum arcu venenatis75,`["performer_146", "performer_42"]`, orci elementum non finibus dolor. Cras76,`["performer_42", "performer_146"]`,`mi lectus Maecenas eleifend neque amet, `77,["performer_146"],` platea placerat. odio Morbi rutrum, eu Cras`我阅读了这个 CSV 并将“类”列的值转换为数组：import pandas as pdimport astdf = pd.read_csv(filename, quotechar='`')df['classes'] = df['classes'].apply(lambda x: ast.literal_eval(x))现在我想在“类”值中选择带有“performer_0”的行。像这样：df['performer_0' in df['classes']]但是这段代码不起作用：Traceback（最近一次调用最后一次）：文件“d:\pyenv\pandas\lib\site-packages\pandas\core\indexes\base.py”，第 2657 行，在 get_loc return self._engine.get_loc(key) File 中pandas_libs\index.pyx"，第 108 行，在 pandas._libs.index.IndexEngine.get_loc 文件 "pandas_libs\index.pyx"，第 132 行，在 pandas._libs.index.IndexEngine.get_loc 文件 "pandas_libs\hashtable_class_helper.pxi" ，第 1601 行，在 pandas._libs.hashtable.PyObjectHashTable.get_item 文件“pandas_libs\hashtable_class_helper.pxi”，第 1608 行，在 pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: False我怎样才能做到这一点？

Answer 1

我发现最简单的方法是组合apply和选择：

df[df['classes'].apply(lambda x: 'performer_0' in x)]

Answer 2

如果你在 pandas 0.25+ 上工作，你可以使用explode：

df[df['classes'].explode().eq(performer_0).any(level=0)]