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本篇内容介绍了“R语言数据框怎么合并-merge”的有关知识,在实际案例的操作过程中,不少人都会遇到这样的困境,接下来就让小编带领大家学习一下如何处理这些情况吧!希望大家仔细阅读,能够学有所成!
站在用户的角度思考问题,与客户深入沟通,找到昂仁网站设计与昂仁网站推广的解决方案,凭借多年的经验,让设计与互联网技术结合,创造个性化、用户体验好的作品,建站类型包括:网站设计、成都网站制作、企业官网、英文网站、手机端网站、网站推广、域名注册、网页空间、企业邮箱。业务覆盖昂仁地区。> df1 = data.frame(CustomerId = c(1:6), Product = c(rep("Toaster", 3), rep("Radio", 3))) > df1 > CustomerId Product 1 1 Toaster 2 2 Toaster 3 3 Toaster 4 4 Radio 5 5 Radio 6 6 Radio > df2 = data.frame(CustomerId = c(2, 4, 6), State = c(rep("Alabama", 2), rep("Ohio", 1))) > df > CustomerId State 1 2 Alabama 2 4 Alabama 3 6 Ohio
> merge(x = df1, y = df2, by = "CustomerId", all = TRUE) > CustomerId Product State 1 1 Toaster2 2 Toaster Alabama 3 3 Toaster 4 4 Radio Alabama 5 5 Radio 6 6 Radio Ohio
> merge(x = df1, y = df2, by = "CustomerId", all.x = TRUE) > CustomerId Product State 1 1 Toaster2 2 Toaster Alabama 3 3 Toaster 4 4 Radio Alabama 5 5 Radio 6 6 Radio Ohio
> merge(x = df1, y = df2, by = "CustomerId", all.y = TRUE) > CustomerId Product State 1 2 Toaster Alabama 2 4 Radio Alabama 3 6 Radio Ohio
> merge(x = df1, y = df2, by = NULL) > CustomerId.x Product CustomerId.y State 1 1 Toaster 2 Alabama 2 2 Toaster 2 Alabama 3 3 Toaster 2 Alabama 4 4 Radio 2 Alabama 5 5 Radio 2 Alabama 6 6 Radio 2 Alabama 7 1 Toaster 4 Alabama 8 2 Toaster 4 Alabama 9 3 Toaster 4 Alabama 10 4 Radio 4 Alabama 11 5 Radio 4 Alabama 12 6 Radio 4 Alabama 13 1 Toaster 6 Ohio 14 2 Toaster 6 Ohio 15 3 Toaster 6 Ohio 16 4 Radio 6 Ohio 17 5 Radio 6 Ohio 18 6 Radio 6 Ohio
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