itertools.chain.from_iterable工作在嵌套的数字列表上，而不是字符串列表上？

Question

我的数据框架中有一列由列表组成，我想将每一行的所有列表组合成一个单元格中的单个列表。

这是列的样子

df.terms.dropna()
0     [Algorithms, Brain, Brain Mapping, Computer Si...
4     [Adult, Algorithms, Cerebrovascular Circulatio...
5     [Algorithms, Brain, Brain Mapping, Hemodynamic...
7     [Adult, Algorithms, Brain, Cerebrovascular Cir...
10    [Animals, Base Composition, Birds, Genetic Var...
Name: mesh_terms, dtype: object

我设法把它们结合在一起

0    [[Algorithms, Brain, Brain Mapping, Computer S...],[Adult, Algorithms, Cerebrovascular Circulatio...],[Algorithms, Brain, Brain Mapping, Hemodynamic...],[list_index_7],[list_index_10]]
Name: mesh_terms, dtype: object

但是我想要一个很长的列表，其中包含像[Algorithms, Brain, Brain Mapping, Computer Si..., ... , Animals, Base Composition, Birds, Genetic Var...]这样的所有字符串

我尝试过使用itertools，但是它仍然给了我一个嵌套列表，但是它在本例中有效

list2d = [[1,2,3],[4,5,6], [7], [8,9]]
list(itertools.chain.from_iterable(list2d))

[1, 2, 3, 4, 5, 6, 7, 8, 9]

也尝试过flattened = [val for sublist in list_of_lists for val in sublist]也没能让它起作用。

请帮帮忙！

以下是所有子列表的完整列表

['Algorithms', 'Brain', 'Brain Mapping', 'Computer Simulation', 'Hemodynamics', 'Humans', 'Linear Models', 'Magnetic Resonance Imaging', 'Models, Neurological'] ['Adult', 'Algorithms', 'Cerebrovascular Circulation', 'Computer Simulation', 'Female', 'Functional Laterality', 'Globus Pallidus', 'Humans', 'Image Processing, Computer-Assisted', 'Magnetic Resonance Imaging', 'Male', 'Models, Neurological', 'Nonlinear Dynamics', 'Reinforcement (Psychology)', 'Reward', 'Young Adult'] ['Algorithms', 'Brain', 'Brain Mapping', 'Hemodynamics', 'Humans', 'Image Interpretation, Computer-Assisted', 'Linear Models', 'Magnetic Resonance Imaging', 'Models, Neurological'] ['Adult', 'Algorithms', 'Brain', 'Cerebrovascular Circulation', 'Female', 'Hemodynamics', 'Humans', 'Image Interpretation, Computer-Assisted', 'Magnetic Resonance Imaging', 'Male', 'Statistics, Nonparametric', 'Young Adult'] ['Animals', 'Base Composition', 'Birds', 'Genetic Variation', 'Genome', 'Genomics', 'Mammals', 'Molecular Sequence Data', 'Phylogeny', 'Reptiles', 'Retroelements', 'Tandem Repeat Sequences']

Answer 1

将值转换为列表，然后转换为DataFrame或Series构造函数：

df_mesh = pd.DataFrame({'terms': [['Algorithms','Brain'],['Adult','Algorithms']]})
print (df_mesh)
                 terms
0  [Algorithms, Brain]
1  [Adult, Algorithms]

df = pd.DataFrame({'new': [df_mesh['terms'].tolist()]})
print (df)
                                          new
0  [[Algorithms, Brain], [Adult, Algorithms]]

s = pd.Series([df_mesh['terms'].tolist()])
print (s)
0    [[Algorithms, Brain], [Adult, Algorithms]]
dtype: object

编辑：

s1 = pd.Series([[val for sublist in df_mesh['terms'] for val in sublist]])
print (s1)
0    [Algorithms, Brain, Adult, Algorithms]
dtype: object

或者：

s1 = pd.Series([list(itertools.chain.from_iterable(df_mesh['terms']))])