Series.str.str.str方法-优快云博客

本文通过一个具体的字符串操作案例展示了如何使用Python中的pandas进行数据处理，包括字符串的获取、切片和正则表达式的匹配等。通过对电子邮件地址的解析，演示了不同字符串方法的应用。

In [29]: aaa
Out[29]: 
Dave     [dave, oogle.com]
Rob        [rob, mail.com]
Steve    [steve, mail.com]
Wes                    NaN
dtype: object

In [30]: aaa.str.get(0)
Out[30]: 
Dave      dave
Rob        rob
Steve    steve
Wes        NaN
dtype: object

In [31]: aaa.str[0]
Out[31]: 
Dave      dave
Rob        rob
Steve    steve
Wes        NaN
dtype: object

In [32]: data.str.findall(pat,flags=re.IGNORECASE)
Out[32]: 
Dave     [(dave, google, com)]
Rob        [(rob, gmail, com)]
Steve    [(steve, gmail, com)]
Wes                        NaN
dtype: object

In [33]: data.str.findall(pat,flags=re.IGNORECASE).str[0]
Out[33]: 
Dave     (dave, google, com)
Rob        (rob, gmail, com)
Steve    (steve, gmail, com)
Wes                      NaN
dtype: object

In [34]: data.str.findall(pat,flags=re.IGNORECASE).str[0][0]
Out[34]: ('dave', 'google', 'com')

In [35]: data.str.findall(pat,flags=re.IGNORECASE).str[0].str[0]
Out[35]: 
Dave      dave
Rob        rob
Steve    steve
Wes        NaN
dtype: object

In [36]: data.str.findall(pat,flags=re.IGNORECASE).str[0].str[0].str[0]
Out[36]: 
Dave       d
Rob        r
Steve      s
Wes      NaN
dtype: object