我正在尝试使用PandasSchema验证我的DataFrame列。我在验证某些列时遇到了麻烦，例如：
1.ip_address-应包含以下格式的IP地址1.1.1.1，或者如果为任何其他值，则该值应为null，否则会引发错误。2. initial_date-格式yyyy-mm-dd h：m：s或mm-dd-yyyy h：m：s等。3.客户类型应为[“类型1”、“类型2”、“类型3”]，否则会引发错误。4.客户满意=是/否或空白5.客户ID不应长于5个字符，例如-cus 01、cus 02 6.时间应为%：%：format或h：m：s format任何其他内容都会引发异常。

from pandas_schema import Column, Schema
def check_string(sr):
    try:
        str(sr)
    except InvalidOperation:
        return False
    return True
def check_datetime(self,dec):
        try:
            datetime.datetime.strptime(dec, self.date_format)
            return True
        except:
            return False
def check_int(num):
    try:
        int(num)
    except ValueError:
        return False
    return True
    

string_validation=[CustomElementValidation(lambda x: check_string(x).str.len()>5 ,'Field Correct')]
int_validation = [CustomElementValidation(lambda i: check_int(i), 'is not integer')]
contain_validation = [CustomElementValidation(lambda y: check_string(y) not in['type1','type2','type3'], 'Filed is correct')]
date_time_validation=[CustomElementValidation(lambda dt: check_datetime(dt).strptime('%m/%d/%Y %H:%M %p'),'is not a date
 time')]
null_validation = [CustomElementValidation(lambda d: d is not np.nan, 'this field cannot be null')]

schema = Schema([
                 Column('CompanyID', string_validation + null_validation),
                 Column('initialdate', date_time_validation),
                 Column('customertype', contain_validation),
                 Column('ip', string_validation),
                 Column('customersatisfied', string_validation)])
errors = schema.validate(combined_df)
errors_index_rows = [e.row for e in errors]
pd.DataFrame({'col':errors}).to_csv('errors.csv')