python - 应用具有两个数据框字段的函数

Question

我有一个像这样的数据框(创建示例数据框)；

df = pd.DataFrame({'language': ['ruby','ruby','ruby', np.nan,'ruby'],
                   'top_lang_owned': [['ruby', 'javascript', 'go'], 
                                      ['ruby', 'coffeescript'],
                                      ['javascript', 'coffeescript'],
                                      ['ruby', 'shell', 'go'],
                                      np.nan],
                   'top_lang_watched': [['ruby','go'], 
                                      ['javascript'],
                                      np.NaN,
                                      ['ruby', 'shell'],
                                      np.nan]})
df

  language    top_lang_owned          top_lang_watched
0 ruby     [ruby, javascript, go]     [ruby, go]
1 ruby     [ruby, coffeescript]       [javascript]
2 ruby     [javascript, coffeescript]  NaN
3 NaN      [ruby, shell, go]          [ruby, shell]
4 ruby      NaN                        NaN

dataframe.info();

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 2 columns):
language          4 non-null object
top_lang_owned    4 non-null object
dtypes: object(2)
memory usage: 208.0+ bytes

我想添加一个比较两个字段值的字段。 (伪代码)

if ("language" is in "top_lang_owned") 
then new_field = 1 othervise new_field = 0.

例如，所需的输出必须如下；

language  top_lang_owned           top_lang_watched  is_owned is_watched
0 ruby    [ruby, javascript, go]      [ruby, go]       1       1
1 ruby    [ruby, coffeescript]        [javascript]     1       0
2 ruby    [javascript, coffeescript]   NaN             0       0
3 NaN     [ruby, shell, go]           [ruby, shell]    NaN     NaN
4 ruby     NaN                         NaN             NaN     NaN

Answer 1

你当然可以做到，这是您可能想尝试的代码，

编辑:

def func(x):
    if x.language in x.top_lang_owned:
        return 1
    return 0

df['is_in_lang'] = df[~df.isna().any(1)].apply(func, axis=1)

输出:

    id language                    top_lang_owned  is_in_lang
0   21     ruby            [ruby, javascript, go]           1
1   25     ruby  [javascript, ruby, coffeescript]           1
2   38     ruby        [javascript, coffeescript]           0
3  108      NaN                 [ruby, shell, go]           NaN
4  173     ruby                               NaN           NaN