循环遍历 Pandas 数据框列中的列表元素以返回新列中的列表

Question

我有一个包含列表的列的数据框，我试图遍历数据框中的每一行并与该行列表的每个元素连接。我正在尝试编写代码来实现“molecule_species”中显示的结果。对此的任何想法将不胜感激。

数据框 =

import pandas as pd
df = pd.DataFrame({'molecule': ['a',
                                'b',
                                'c',
                                'd',
                                'e'],
                   'species' : [['dog'],
                                ['horse','pig'],
                                ['cat', 'dog'],
                                ['cat','horse','pig'],
                                ['chicken','pig']]})

我试图通过迭代行和列表元素来创建新列，将“分子”与“物种”中包含的列表中的每个元素连接起来。

df['molecule_species'] = [['a dog'],
                          ['b horse','b pig'],
                          ['c cat', 'c dog'],
                          ['d cat','d horse','d pig'],
                          ['e chicken','e pig']]

Answer 1

熊猫 > 0.25.0

使用Series.explode然后join返回列表GroupBy.agg：

df['molecule_species'] = (df.explode('species')
                            .apply(' '.join,axis=1)
                            .groupby(level=0)
                            .agg(list) )
print(df)

  molecule            species         molecule_species
0        a              [dog]                  [a dog]
1        b       [horse, pig]         [b horse, b pig]
2        c         [cat, dog]           [c cat, c dog]
3        d  [cat, horse, pig]  [d cat, d horse, d pig]
4        e     [chicken, pig]       [e chicken, e pig]

熊猫 < 0.25.0

df['molecule_species']=(df.reindex(df.index.repeat(df.species.str.len()))
                          .assign(species=np.concatenate(df.species.values))
                          .apply(' '.join,axis=1)
                          .groupby(level=0)
                          .agg(list) )
print(df)
  molecule            species         molecule_species
0        a              [dog]                  [a dog]
1        b       [horse, pig]         [b horse, b pig]
2        c         [cat, dog]           [c cat, c dog]
3        d  [cat, horse, pig]  [d cat, d horse, d pig]
4        e     [chicken, pig]       [e chicken, e pig]

另一种方法是 Series.str.cat

df2 = df.explode('species')
df['molecule_species']=df2['molecule'].str.cat(df2['species'],sep=' ').groupby(level=0).agg(list)

Answer 2

你可以试试这个，

>>> import pandas as pd
>>> df = pd.DataFrame({'molecule': ['a',
                                'b',
                                'c',
                                'd',
                                'e'],
                   'species' : [['dog'],
                                ['horse','pig'],
                                ['cat', 'dog'],
                                ['cat','horse','pig'],
                                ['chicken','pig']]})

>>> df['molecule_species'] = (df
    .apply(lambda x: [x['molecule'] + ' ' + m for m in x['species']], axis=1))
>>> df
  molecule            species         molecule_species
0        a              [dog]                  [a dog]
1        b       [horse, pig]         [b horse, b pig]
2        c         [cat, dog]           [c cat, c dog]
3        d  [cat, horse, pig]  [d cat, d horse, d pig]
4        e     [chicken, pig]       [e chicken, e pig]