January 2014
Beginner to intermediate
488 pages
8h 1m
Chinese
Content preview from R 錦囊妙計
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第六章
在本書中，我將這些因子視為
分組因子
（
grouping factors
）。藉由將資料分組，因子有
效地將資料切割成小塊。此外，分組資料在統計學中，常用來比較組平均、比較組比
例，與進行變異數分析等。
本章涵蓋之錦囊內容，部分包括使用分組因子將向量元素分配至各組別（錦囊 6.1）， 將
函數應用於向量中的各組（錦囊 6.5），應用函數至資料框架中的列資料組（錦囊 6.6）。
而在其他章節中，分組資料也應用於檢驗組平均值（錦囊 9.19），執行一因子變異數分
析（錦囊 11.20），以及依據群組繪製資料點（錦囊 10.4）等。
6.1 將向量分組
問題點
您有一個向量，其中每個向量元素隸屬於不同組別；而且，組別是依據分組因子界定。
您想要依據分組因子將向量元素分組。
解決方案
假設向量為
x
，因子為
f
。您可以使用
split
函數進行分組如下：
> groups <- split(x, f)
或者，使用
unstack
函數：
> groups <- unstack(data.frame(x,f))
以上兩個函數皆回傳一個向量列表，其中，每個向量都包含已分組的元素。
此外，
unstack
函數有更進階的功能：若所有的向量具有相同長度，則可將列表轉換為
資料框架。
討論說明
名稱為
Cars93
的資料集包含一個名為
Origin
的因子變數，此因子有兩個組別：
USA
與
non-USA
；也包含名為
MPG.city
的變數。我們可依據
Origin
為
MPG.city
資料進行分組，
如下所示：
> library(MASS)
> split(Cars93$MPG.city, ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.