普通打标签
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odue_df=df_train_stmt.loc[(df_train_stmt.AGE3>0)|(df_train_stmt.AGE4>0)|(df_train_stmt.AGE5>0)|(df_train_stmt.AGE6>0),['XACCOUNT']].drop_duplicates()odue_df['label']=1cust_df=df_acct[['CUSTR_NBR','XACCOUNT']].drop_duplicates()#做合并df_y=pd.merge(cust_df,odue_df,how='left',on='XACCOUNT').groupby('CUSTR_NBR').agg({'label':max}).reset_index().fillna(0) |
使用函数来打标签
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#标注标签 Labeldef label(row): if row['Date_received'] == 'null': return -1 if row['Date'] != 'null': td = pd.to_datetime(row['Date'], format='%Y%m%d') - pd.to_datetime(row['Date_received'], format='%Y%m%d') if td <= pd.Timedelta(15, 'D'): return 1 return 0dfoff['label'] = dfoff.apply(label, axis=1)#打标签，判断天数def get_label(s): s = s.split(':') if s[0]=='null': return 0 elif (date(int(s[0][0:4]),int(s[0][4:6]),int(s[0][6:8]))-date(int(s[1][0:4]),int(s[1][4:6]),int(s[1][6:8]))).days<=15: return 1 else: return -1dataset2.label = dataset2.label.apply(get_label) |
补充：python 根据标签名获取标签内容
看代码吧~
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import reimport json import requestsfrom bs4 import BeautifulSoupimport lxml.htmlfrom lxml import etree result = requests.get('http://example.webscraping.com/places/default/view/Algeria-4')with open('123.html', 'wb') as f: f.write(result.content)# print(parse_regex(result.text))test_data = """ <div> <ul> <li class="item-0"><a href="link1.html" rel="external nofollow" rel="external nofollow" id="places_neighbours__row">9,596,960first item</a></li> <li class="item-1"><a href="link2.html" rel="external nofollow" >second item</a></li> <li class="item-inactive"><a href="link3.html" rel="external nofollow" >third item</a></li> <li class="item-1"><a href="link4.html" rel="external nofollow" id="places_neighbours__row">fourth item</a></li> <li class="item-0"><a href="link5.html" rel="external nofollow" rel="external nofollow" >fifth item</a></li> <li class="good-0"><a href="link5.html" rel="external nofollow" rel="external nofollow" >fifth item</a></li> </ul> <book> <title lang="aaengbb">Harry Potter</title> <price id="places_neighbours__row">29.99</price> </book> <book> <title lang="zh">Learning XML</title> <price>39.95</price> </book> <book> <title>Python</title> <price>40</price> </book> </div> """# //div/ul/li/a[@id] 选取a标签中带有id属性的标签# //div/ul/li/a 选取所有a标签# //div/ul/li[2]/a"""/ 从根标签开始 必须具有严格的父子关系// 从当前标签 后续节点含有即可选出* 通配符 选择所有//div/book[1]/title 选择div下第一个book标签的title标签//div/book[1]/tittle[@lang="zh"] 选择div下第一个book标签的title标签并且内容是zh的title标签//div/book/title //book/title //title 具有相同结果 只不过选取路径不一样//book/title/@* 将title所有的属性值选出来//book/title/text() 将title的内容选择出来,使用内置函数//a[@href="link1.html" rel="external nofollow" rel="external nofollow" and @id="places_neighbours_row"]//div/book/[last()]/title/text() 将最后一个book元素选出//div/book[price > 39]/title/text() 将book子标签price数值大于３９的选择出来//li[starts-with(@class,'item')] 将class属性前缀是item的选出来//title[contains(@lang,"eng")]将title属性lang含有eng关键字的标签选出"""html = lxml.html.fromstring(test_data) # 加载任意一个字符串html_data = html.xpath('//title[contains(@lang,"eng")]') # xpath 查找路径# print(dir(html_data[0])) # 查看html_data有什么功能print(html_data)for i in html_data: print(i.text) |
以上为个人经验，希望能给大家一个参考，也希望大家多多支持服务器之家。
原文链接：https://blog.csdn.net/wj1298250240/article/details/103146274
