[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_9":135,"_136":137},"pages/BookDetail",{"_9":10,"_11":12},"dehydratedState",{"_106":107,"_108":109},"book",{"_13":14,"_15":16,"_17":18,"_19":20,"_21":22,"_23":24,"_25":26,"_27":28,"_29":30,"_31":32,"_33":34,"_35":36,"_37":38,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":-5,"_56":57,"_58":59},"id",14,"resources",[88,89],"testimonials",[60,61,62],"title","Python数据分析与数据化运营(第2版)","status","p","pub_time","2026-05-17T13:52:00","subtitle","深度实战与价值提升","author","宋天龙","publisher","机械工业出版社","pub_date","2019-06-01","edition","2","isbn","9787111627760","cover","http://backend:8000/media/book_covers/book_14.png","rating",4.7,"reviews",14537,"desc","作为该系列的旗舰作，第 2 版在第 1 版基础上进行了大幅升级。全面适配 Python 3.x，新增了 50 多个数据工作流知识点、14 个挖掘主题和 8 个综合案例。\r\n\r\n本书不仅关注模型构建，更深入探讨了非结构化数据处理、AutoML 以及复杂的业务运营逻辑，是数据从业者进阶的必读书目。","outline","- **第一部分：Python 数据分析与挖掘**\r\n - 第1章：Python 与数据化运营基础（含 OCR、TensorFlow 延伸）\r\n - 第2章：数据来源（结构化、非结构化数据获取）\r\n - 第3章：10 条预处理经验（清洗、降维、样本不均衡处理等）\r\n - 第4章：常用数据模型（聚类、回归、分类、关联、异常检测、AutoML）\r\n- **第二部分：业务场景实战**\r\n - 第5章：会员数据化运营（生命周期、RFM、流失预测）\r\n - 第6章：商品数据化运营（分析模型、关联推荐、异常检测）\r\n - 第7章：流量数据化运营（来源分析、转化路径、归因分析）\r\n - 第8章：内容数据化运营（文本挖掘、情感分析、标签体系）\r\n - 第9章：数据化运营的价值提升（报告撰写、数据驱动闭环）","audience","- **资深数据分析师**：希望在业务深度与技术广度上寻求突破的专业人士。\r\n- **数据挖掘工程师**：关注算法落地与 AutoML 应用的技术专家。\r\n- **企业决策者**：希望了解如何构建数据驱动业务闭环的管理层。","features","- **深度实战**：旗舰级著作，业务逻辑最深，案例最全。\r\n- **技术领先**：全面覆盖 Python 3 生态，引入 AI 与非结构化处理。\r\n- **新增模块**：强化了内容运营与自动化机器学习部分。","jd_link","https://item.jd.com/12714271.html","dangdang_link","https://e.dangdang.com/products/1901309487.html","douban_link","sequence",94,"created_time","2026-04-26T11:24:00",{"_13":82,"_64":83,"_66":84,"_68":85,"_39":79,"_56":86,"_72":73,"_58":87,"_11":14},{"_13":75,"_64":76,"_66":77,"_68":78,"_39":79,"_56":80,"_72":73,"_58":81,"_11":14},{"_13":63,"_64":65,"_66":67,"_68":69,"_39":70,"_56":71,"_72":73,"_58":74,"_11":14},24,"name","赵雷","role","高级数据分析师","content","进阶必读。书里的很多业务分析框架（如RFM、AARRR）结合Python代码实现得非常优雅，实操性极强。",4,3,"is_enable",true,"2026-05-16T16:28:42.955088",23,"李娟","业务分析师","相较于第一版，新增的内容非常契合现在的商业环境。不仅教你怎么写代码，更教你怎么用数据驱动业务。",5,2,"2026-05-16T16:28:42.949087",22,"王鹏","数据产品经理","第一版就是我的入门书，第二版加入了更多新时代的案例和技术，内容更加饱满。经典之作，值得一看再看！",1,"2026-05-16T16:28:42.943088",{"_13":100,"_64":101,"_92":102,"_94":103,"_95":-5,"_43":104,"_98":105,"_11":14},{"_13":90,"_64":91,"_92":93,"_94":-5,"_95":96,"_43":97,"_98":99,"_11":14},16,"itHub 随书代码仓库(适用于熟悉git仓库)","type","link","file","url","https://github.com/beijingtl/python-data-analysis-operations-v2","本书的配套代码和数据，托管在 GitHub 仓库中。","updated_time","2026-05-16T16:02:35.151751",26,"随书代码仓库压缩包(适用于浏览器下载)","zip","http://backend:8000/media/book_resources/%E4%B9%A6%E7%B1%8Dpython%E6%95%B0%E6%8D%AE%E5%88%86%E6%9E%90%E4%B8%8E%E6%95%B0%E6%8D%AE%E5%8C%96%E8%BF%90%E8%90%A5_-_%E7%AC%AC2%E7%89%88.zip","","2026-05-16T16:02:35.285963","mutations",[],"queries",[110],{"_111":112,"_113":114,"_115":116,"_117":118},"dehydratedAt",1780755664609,"state",{"_120":12,"_121":86,"_122":112,"_123":-5,"_124":125,"_126":125,"_127":125,"_128":-5,"_129":-5,"_130":131,"_21":132,"_133":134},"queryKey",[11,119],"queryHash","[\"book\",\"14\"]","14","data","dataUpdateCount","dataUpdatedAt","error","errorUpdateCount",0,"errorUpdatedAt","fetchFailureCount","fetchFailureReason","fetchMeta","isInvalidated",false,"success","fetchStatus","idle",{"_106":158,"_108":159},"settings",{"_13":86,"_138":139,"_140":141,"_142":143,"_144":145,"_146":147,"_148":131,"_149":104,"_150":151,"_152":153,"_154":73,"_155":156,"_157":73},"sitename","数据常青藤","site_description","数据智能应用与落地才是数据的未来！","site_seo_description","介绍有关数据化运营、数据分析、数据挖掘、人工智能、机器学习、深度学习、神经网络、模式识别、自然语言处理、图像识别等方的知识，数据驱动运营，数据增长黑客","site_keywords","Python,Python数据分析与数据化运营,sklearn,广告分析,数据分析,数据化运营,日志解析,流量分析,渠道分析,电商流量数据化运营,聚类,数据化管理","article_sub_length",300,"show_google_adsense","google_adsense_codes","icp_beiancode","京ICP备2022002926号-1","analyticscode","","show_gongan_code","gongan_beiancode","

京公网安备 11010502048830号

","is_active",[],[160,161,162],{"_111":163,"_113":214,"_115":215,"_117":216},{"_111":163,"_113":196,"_115":197,"_117":198},{"_111":163,"_113":164,"_115":165,"_117":166},1780755664617,{"_120":168,"_121":86,"_122":169,"_123":-5,"_124":125,"_126":125,"_127":125,"_128":-5,"_129":-5,"_130":131,"_21":132,"_133":134},[167],"[\"about-settings\"]","about-settings",{"_13":80,"_170":171,"_172":173,"_174":175,"_176":177,"_178":179,"_180":181,"_182":183,"_184":185,"_186":187,"_188":-5,"_189":-5,"_190":-5,"_191":192,"_193":-5,"_194":195,"_157":73},1780755664613,"about_avatar","http://backend:8000/media/about_avatars/author_avatar.jpg","about_title","数据领域资深技术专家 / 触脉咨询合伙人 / 畅销书作者","about_description","宋天龙(TonySong)，触脉咨询合伙人，前Webtrekk中国区技术和咨询负责人。在数据领域工作17年，积累了丰富的数据工作经验、案例、场景和方法。擅长数据增长、构建、分析与运营，精通端到端数据价值链设计、业务需求转换、数据结构梳理、数据建模以及数据工程交付。服务客户包括SHEIN、联合利华、德国OTTO集团、Esprit、顺丰优选等。","research_fields","Agentic AI、数据化运营、数据分析、数据挖掘、机器学习、个性化推荐、精准营销、互联网和网站分析","social_roles","中国商业联合会数据分析专业委员会《中国大数据人才培养体系标准》专家组成员，虎啸奖评委会委员，DMT数字营销人才认证委员会认证委员","about_location","深圳, 中国","about_role","数据领域持续深耕","contact_email","517699029@qq.com","contact_github","https://github.com/beijingtl","contact_twitter","contact_linkedin","contact_xiaohongshu","contact_zhihu","https://www.zhihu.com/people/dataivy","contact_bilibili","wechat_qrcode","http://backend:8000/media/about_qrcodes/contact_weixin.jpg",{"_120":200,"_121":86,"_122":163,"_123":-5,"_124":125,"_126":125,"_127":125,"_128":-5,"_129":-5,"_130":131,"_21":132,"_133":134},[199],"[\"links\"]","links",[201,202],{"_13":210,"_64":211,"_93":212,"_56":80,"_72":73,"_206":207,"_58":213,"_209":213},{"_13":203,"_64":204,"_93":205,"_56":71,"_72":73,"_206":207,"_58":208,"_209":208},7,"网站LLM SiteMap入口","https://www.dataivy.cn/llm.txt","show_type","a","2026-05-23T15:24:05.993290","last_mod_time",6,"网站XML SiteMap入口","https://dataivy.cn/sitemap.xml","2026-05-23T15:23:26.977321",{"_120":137,"_121":86,"_122":217,"_123":-5,"_124":125,"_126":125,"_127":125,"_128":-5,"_129":-5,"_130":131,"_21":132,"_133":134},[136],"[\"settings\"]",1780755664594]

未找到该书籍