今天继续介绍 dplyr 包中的重要函数 mutate ，其基本功能为创建新列； mutate 中的选项几乎是无穷无尽的，可以通过各种函数之间的组合来对数据集做任意的处理，下面通过具体的案例来进行演示
这次我们使用R内置的数据集 msleep ，其中包括哺乳动物的睡眠时间。让我们首先加载包并查看数据：
library(tidyverse) msleepname genus vore order conservation sleep_total sleep_rem sleep_cycle <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> 1 Cheetah Acino~ carni Carn~ lc 12.1 NA NA 2 Owl mo~ Aotus omni Prim~ NA 17 1.8 NA 3 Mounta~ Aplod~ herbi Rode~ nt 14.4 2.4 NA 4 Greate~ Blari~ omni Sori~ lc 14.9 2.3 0.133mutate 基础操作
最简单的的操作就是根据其他列中的值进行计算。在示例代码中，我们将睡眠数据从以小时为单位更改为分钟为单位
msleep %>% select(name,sleep_total) %>% mutate(sleep_total_min = sleep_total * 60)name sleep_total sleep_total_min <chr> <dbl> <dbl> 1 Cheetah 12.1 726 2 Owl monkey 17 1020 3 Mountain beaver 14.4 864下列代码创建了两列新列：一列显示了睡眠时间与平均睡眠时间的差异，另一列显示了与睡眠时间最少的动物之间的差异；round( )对数据进行四舍五入操作
msleep %>% select(name, sleep_total) %>% mutate(AVG = sleep_total - round(mean(sleep_total), 1), MIN = sleep_total - min(sleep_total))# A tibble: 83 x 4 name sleep_total AVG MIN <chr> <dbl> <dbl> <dbl> 1 Cheetah 12.1 1.7 10.2 2 Owl monkey 17 6.6 15.1 3 Mountain beaver 14.4 4 12.5选择特定列按行求均值，rowwise( )说明按行进行操作
msleep %>% select(name, contains("sleep")) %>% rowwise() %>% mutate(avg = mean(c(sleep_rem,sleep_cycle)))name sleep_total sleep_rem sleep_cycle avg <chr> <dbl> <dbl> <dbl> <dbl> 1 Cheetah 12.1 NA NA NA 2 Owl monkey 17 1.8 NA NA 3 Mountain beaver 14.4 2.4 NA NA 4 Greater short-tail~ 14.9 2.3 0.133 1.22通过ifelse判断语句对数据进行操作，如果
brainwt > 4返回NA,不满足此条件返回原值msleep %>% select(name, brainwt) %>% mutate(brainwt2 = ifelse(brainwt > 4, NA, brainwt)) %>% arrange(desc(brainwt))name brainwt brainwt2 <chr> <dbl> <dbl> 1 African elephant 5.71 NA 2 Asian elephant 4.60 NA 3 Human 1.32 1.32 4 Horse 0.655 0.655也可以结合使用stringr的功能或正则表达式来对字符串列进行操作；
示例代码将返回动物名称的最后一个单词，并使其小写msleep %>% select(name) %>% mutate(name_last_word = tolower(str_extract(name, pattern = "\\w+$")))name name_last_word <chr> <chr> 1 Cheetah cheetah 2 Owl monkey monkey 3 Mountain beaver beaver对多列同时进行操作
mutate_all() 将对所有列进行操作 mutate_if()首先需要一个返回布尔值，如果是T，则将在这些变量上执行mutate指令 mutate_at()要求在vars() 参数内指定要进行改变的列 将所有数据转换为小写：
msleep %>% mutate_all(tolower)name genus vore order conservation sleep_total sleep_rem <chr> <chr> <chr> <chr> <chr> <chr> <chr> 1 cheetah acin~ carni carn~ lc 12.1 NA 2 owl mo~ aotus omni prim~ NA 17 1.8 3 mounta~ aplo~ herbi rode~ nt 14.4 2.4所有列添加
" /n "msleep %>% mutate_all(~paste(., " /n "))将
" /n "全部替换为空msleep_ohno <- msleep %>% mutate_all(~paste(., " /n ")) msleep_ohno %>% mutate_all(~str_replace_all(., "/n", "")) %>% mutate_all(str_trim)mutate_if()对数据进行判断
如果数据类型是数值，对其进行四舍五入操作
msleep %>% select(name, sleep_total:bodywt) %>% mutate_if(is.numeric, round)name sleep_total sleep_rem sleep_cycle awake brainwt bodywt <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Cheetah 12 NA NA 12 NA 50 2 Owl monkey 17 2 NA 7 0 0 3 Mountain beaver 14 2 NA 10 NA 1mutate_at( )对特定列进行操作
对列名含有
sleep的进行操作msleep %>% select(name, sleep_total:awake) %>% mutate_at(vars(contains("sleep")), ~(.*60))name sleep_total sleep_rem sleep_cycle awake <chr> <dbl> <dbl> <dbl> <dbl> 1 Cheetah 726 NA NA 11.9 2 Owl monkey 1020 108 NA 7 3 Mountain beaver 864 144 NA 9.6msleep %>% select(name, sleep_total:awake) %>% mutate_at(vars(contains("sleep")), ~(.*60)) %>% rename_at(vars(contains("sleep")), ~paste0(.,"_min"))name sleep_total_min sleep_rem_min sleep_cycle_min awake <chr> <dbl> <dbl> <dbl> <dbl> 1 Cheetah 726 NA NA 11.9 2 Owl monkey 1020 108 NA 7 3 Mountain beaver 864 144 NA 9.6保留原始数据
msleep %>% select(name, sleep_total:awake) %>% mutate_at(vars(contains("sleep")), funs(min = .*60))name sleep_total sleep_rem sleep_cycle awake sleep_total_min sleep_rem_min sleep_cycle_min <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Cheetah 12.1 NA NA 11.9 726 NA NA 2 Owl monkey 17 1.8 NA 7 1020 108 NAifelse创建2个级别的离散列
msleep %>% select(name, sleep_total) %>% mutate(sleep_time = ifelse(sleep_total > 10, "long", "short"))name sleep_total sleep_time <chr> <dbl> <chr> 1 Cheetah 12.1 long 2 Owl monkey 17 long 3 Mountain beaver 14.4 longcase_when创建多级离散列
此函数在后续数据清洗中有大有，需要多多练习
msleep %>% select(name, sleep_total) %>% mutate(sleep_total_discr = case_when( sleep_total > 13 ~ "very long", sleep_total > 10 ~ "long", sleep_total > 7 ~ "limited", TRUE ~ "short"))name sleep_total sleep_total_discr <chr> <dbl> <chr> 1 Cheetah 12.1 long 2 Owl monkey 17 very long 3 Mountain beaver 14.4 very long 4 Greater short-tailed shrew 14.9 very long将数据转化为NA
msleep %>% select(name:order) %>% na_if("omni")name genus vore order <chr> <chr> <chr> <chr>
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