我搜索了论坛,但找不到任何对我有用的东西。我在这里有一个独特的数据集,我记录了我每天每小时所做的事情,我只是想找到所有独特的条目。例如,有大约一百天左右的“睡眠”条目,“家庭作业”,“晚餐”,我只想找到我所做的所有可能的事情,所有独特的条目。
我尝试了独特的(数据),这对我来说无处可寻,我尝试过独特的(数据[,1])。如果我写一个'for'循环来做那个,我怎么能合并列表,并进一步削减他们的独特性?
> data[, 1]
[1] morning prep work work work work
[6] work work work work homework
[11] MNT chat with Dan dinner movie movie
[16] sleep sleep sleep sleep sleep
[21] sleep sleep sleep sleep
Levels: chat with Dan dinner homework MNT morning prep movie sleep work
它的阶级是一个'因素'。独特可以很好地减少它,但是我如何将所有的日子组合成一个长的字符向量,我可以用来进行分析,例如......
sum(data=='sleep')
但是凭借我的列表,我将能够编写另一个'for'循环并轻松地总结一切......
答案 0 :(得分:0)
我有一种感觉,你只是在寻找table
功能。拉出“独特”因素并一次性计算频率:
myHomework <- data.frame(StuffIDid = c("morning prep", "work", "work", "work",
"work", "work", "work", "work", "work",
"homework", "MNT", "chat with Dan",
"dinner", "movie", "movie", "sleep",
"sleep", "sleep", "sleep", "sleep",
"sleep", "sleep", "sleep", "sleep"))
str(myHomework)
# 'data.frame': 24 obs. of 1 variable:
# $ StuffIDid: Factor w/ 8 levels "chat with Dan",..: 5 8 8 8 8 8 8 8 8 3 ...
table(myHomework[, "StuffIDid"])
#
# chat with Dan dinner homework MNT morning prep movie
# 1 1 1 1 1 2
# sleep work
# 9 8
或者,作为data.frame
:
data.frame(table(myHomework[, "StuffIDid"]))
# Var1 Freq
# 1 chat with Dan 1
# 2 dinner 1
# 3 homework 1
# 4 MNT 1
# 5 morning prep 1
# 6 movie 2
# 7 sleep 9
# 8 work 8