https://blog.youkuaiyun.com/baixiaofuzh-cnhttps://blog.youkuaiyun.com/https://blog.youkuaiyun.com/baixiaofu/article/details/80756479https://blog.youkuaiyun.com/baixiaofu/article/details/80756479baixiaofuThu, 21 Jun 2018 17:04:08 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80734817https://blog.youkuaiyun.com/baixiaofu/article/details/80734817baixiaofuTue, 19 Jun 2018 15:45:50 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80731811https://blog.youkuaiyun.com/baixiaofu/article/details/80731811baixiaofuTue, 19 Jun 2018 14:52:32 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80728752https://blog.youkuaiyun.com/baixiaofu/article/details/80728752baixiaofuTue, 19 Jun 2018 10:32:50 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80708742https://blog.youkuaiyun.com/baixiaofu/article/details/80708742baixiaofuFri, 15 Jun 2018 18:16:40 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80705573https://blog.youkuaiyun.com/baixiaofu/article/details/80705573baixiaofuFri, 15 Jun 2018 15:31:08 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80118031https://blog.youkuaiyun.com/baixiaofu/article/details/80118031baixiaofuSat, 28 Apr 2018 17:13:27 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80042907https://blog.youkuaiyun.com/baixiaofu/article/details/80042907baixiaofuTue, 24 Apr 2018 00:01:00 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80047384https://blog.youkuaiyun.com/baixiaofu/article/details/80047384baixiaofuMon, 23 Apr 2018 14:36:15 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/80041996https://blog.youkuaiyun.com/baixiaofu/article/details/80041996baixiaofuSun, 22 Apr 2018 21:00:48 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/79889710https://blog.youkuaiyun.com/baixiaofu/article/details/79889710baixiaofuWed, 11 Apr 2018 18:00:44 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/79878134https://blog.youkuaiyun.com/baixiaofu/article/details/79878134baixiaofuTue, 10 Apr 2018 17:53:51 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/77075279https://blog.youkuaiyun.com/baixiaofu/article/details/77075279baixiaofuThu, 10 Aug 2017 23:49:52 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/75174773https://blog.youkuaiyun.com/baixiaofu/article/details/75174773baixiaofuSat, 15 Jul 2017 17:11:22 +0800>转换成为表2 表1： 表2： R实现数据的透视功能，使用reshape2包中的melt()函数和dcast()函数。在《R语言实战》这本书中有着详细的介绍。我在这里引用了其中的一些内容。 首先是融合函数，融合顾名思义就是把原先的数据进行融化合并，具体melt()函数会融合成什么样的形式呢？ Library(reshape2]]>https://blog.youkuaiyun.com/baixiaofu/article/details/72869646https://blog.youkuaiyun.com/baixiaofu/article/details/72869646baixiaofuMon, 05 Jun 2017 17:49:51 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/72630725https://blog.youkuaiyun.com/baixiaofu/article/details/72630725baixiaofuMon, 22 May 2017 22:07:21 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/72593778https://blog.youkuaiyun.com/baixiaofu/article/details/72593778baixiaofuSun, 21 May 2017 08:09:24 +0800https://blog.youkuaiyun.com/baixiaofu/article/details/71910598https://blog.youkuaiyun.com/baixiaofu/article/details/71910598baixiaofuSat, 13 May 2017 23:27:57 +0800目标数据—>（数据预处理）—>变换]]>