python - 有没有更好的方法来根据大小写进行名称分类？

Question

我想对自由文本书写名称进行分类，并在此之后创建一个分类变量

1. Only first : 只有第一个字母是大写
2. 标准用法:每个单词的首字母大写
3. All capital : 每个字母都是大写
4. All small : 每个字母都在情人的情况下
5. Unidentified : 不属于以上 4 个类别中的任何一个

这是我的数据

Id   Name
1    Donald trump
2    Barack Obama
3    Hillary ClintoN
4    BILL GATES
5    jeff bezoz
6    Mark Zuckerberg

我想要什么

Id   Name                 Category
1    Donald trump         Only first
2    Barack Obama         Standard usage
3    Hillary ClintoN      Unidentified      
4    BILL GATES           All capital
5    jeff bezoz           All small
6    Mark Zuckerberg      Standard usage

我做的是

df['Uppercase'] = df['Name'].str.findall(r'[A-Z]').str.len()
df['Lowercase'] = df['Name'].str.findall(r'[a-z]').str.len()
df['WordCount'] = df['Name'].str.count(' ') + 1

然后使用map函数做一些逻辑，比如我们:

`df['Lowercase'] = 0` for `All capital`
`df['Uppercase'] = 0` for `All small`
`df['Uppercase'] - df['WordCount'] = 0` for `Standard usage`
`df['Uppercase'] = 1 and `df['WordCount']` for `Only first`

如果这不属于任何它标记为 Unidentified

但是，naBih baWazir 会根据标准规则被记录为Standard usage，而不是Unidentified，我认为还有更好的办法所以

Answer 1

使用函数 Series.str.islower Series.str.isupper Series.str.istitle和新专栏 numpy.select :

#test all letters without first for lower and first value for upper
m1 = df['Name'].str[1:].str.islower() & df['Name'].str[0].str.isupper()
m2 = df['Name'].str.istitle()
m3 = df['Name'].str.islower()
m4 = df['Name'].str.isupper()

df['Category'] = np.select([m1, m2, m3, m4], 
                           ['Only first','Standard usage','All small','All capital'], 
                           default='Unidentified ')
print (df)
   Id             Name        Category
0   1     Donald trump      Only first
1   2     Barack Obama  Standard usage
2   3  Hillary ClintoN   Unidentified 
3   4       BILL GATES     All capital
4   5       jeff bezoz       All small
5   6  Mark Zuckerberg  Standard usage

---

@Jon Clements 的想法，谢谢:

m1 = df['Name'].str[1:].str.islower() & df['Name'].str[0].str.isupper()
df1 = df.Name.agg([str.istitle, str.islower, str.isupper])

df['Category'] = np.select(
    [m1, *df1.values.T], 
    ['Only first','Standard usage','All small','All capital'], 
    default='Unidentified '
)