在np.select中使用字符串条件的问题

Question

我试图根据一个字符串是否包含在另一个专栏中，在熊猫数据中创建一个新的列。我使用基于这个np.select的post。下面是一个示例dataframe和一个创建新列的示例函数

df=pd.DataFrame({'column':['one','ones','other','two','twos','others','three','threes']})

def add(df):

    conditions = [
        ('one' in df['column']),
        ('two' in df['column']),
        ('three' in df['column']),
        ('other' in df['column'])] 

    choices = [1, 2, 3, 0]
    df['Int'] = np.select(conditions, choices, default=0)

    return df

new_df=add(df)

我得到的输出是

   column  Int
0     one    0
1    ones    0
2   other    0
3     two    0
4    twos    0
5  others    0
6   three    0
7  threes    0

我想要的是

   column  Int
0     one    1
1    ones    1
2   other    0
3     two    2
4    twos    2
5  others    0
6   three    3
7  threes    3

我做错什么了？

Answer 1

如果需要测试子字符串，请使用Series.str.contains

 conditions = [
        (df['column'].str.contains('one')),
        (df['column'].str.contains('two')),
        (df['column'].str.contains('three')),
        (df['column'].str.contains('other'))] 

如果需要精确匹配，请使用Series.eq或==

 conditions = [
        (df['column'].eq('one')),
        (df['column'].eq('two')),
        (df['column'].eq('three')),
        (df['column'].eq('other'))] 

 conditions = [
        (df['column'] == 'one'),
        (df['column'] == 'two'),
        (df['column'] == 'three'),
        (df['column'] == 'other')] 

print (new_df)
   column  Int
0     one    1
1    ones    1
2   other    0
3     two    2
4    twos    2
5  others    0
6   three    3
7  threes    3