我有一个称为'group1'的FFDF对象,该对象具有一百万行的数据,看起来像这样:
Location DateandTime Reading Group
1 1 01/01/2012 00:00:00 0.8 1
2 1 01/01/2012 00:30:00 0.4 1
3 1 01/01/2012 01:00:00 0.7 1
4 1 01/01/2012 01:30:00 0.2 1
我正在尝试为每个" dateAndtime"进行平均"阅读"和标准偏差,并创建一个新的DF来看起来像这样:
DateTime mean sd
1 01/01/2012 00:00:00 0.8 .2
2 01/01/2012 00:30:00 0.5 .5
3 01/01/2012 01:00:00 0.2 .3
4 01/01/2012 01:30:00 0.8 .8
,或者您可以使用dplyr
软件包
library(dplyr)
group1.stat <- group1 %>%
select(DateandTime, Reading) %>%
group_by(DateandTime) %>%
summarise_each(funs(mean = mean(., na.rm = TRUE), sd = sd(., na.rm = TRUE)))
group1.stat
这种dplyr
方法也将起作用:
library(dplyr)
newdf <- group1 %>%
group_by(DateandTime) %>%
summarise(mean = mean(Reading), sd = sd(Reading))