python电话 邮箱正则匹配清洗

</pre>做数据清洗时候，难免会碰到有些客户电话，邮箱乱填写，一看就明显不正确，用到python写个正则表达式可以进行快速的清洗</p><p>废话不多说，上代码：</p><p><pre name="code" class="python">#encoding:utf-8'''Created on 2015年9月18日@author: ZHOUMEIXU204'''import MySQLdbimport  reimport pandas  as pdcon=MySQLdb.connect(host="10.10.109.62", port=1333, user="zhoumeixu204", \                     passwd="zhoumeixu204@123456!", db="ubs", use_unicode=True, charset="utf8")result=pd.read_sql("SELECT cust_id , USR_MP,USR_EMAIL FROM ubs.usr_oper_info;",con)def    mobile_match(x):    pattern=re.compile(r'1[3,5,4,7,8]{1}[0-9]{9}')    match=pattern.match(x)    if match:        return   True    else:        return Falseresult['mobile_judge']=result['USR_MP'].map(mobile_match)def  email_match(x):    if x.strip().endswith('pingan.com.cn'):        patten=re.compile(r'[a-zA-Z]{1,15}[0-9]{3}\@pingan\.com\.cn')        match=patten.match(x)        if match:            return True        else:            return  False    else:        if len(x) > 7:            if re.match("^.+\\@(\\[?)[a-zA-Z0-9\\-\\.]+\\.([a-zA-Z]{2,3}|[0-9]{1,3})(\\]?)$", x) != None:                return True            else:                return False        else:            return False         result['usr_email_judge']=result['USR_EMAIL'].map(email_match)result.to_excel(u"D:\\匹配结果.xls",index=False)print(result.head())con.close()

实际都是一些技巧，记录一些，免得要用时候又要查找