重新排列r中的数据帧

Question

我正在尝试使用我拥有的一些现有库存数据。最终我想对数据生成加权回报，但我需要先改变它的结构。

现有代码：

library(reshape2) 
library(xts) 
data <- read.csv(file="mini_r_weights.csv",head=TRUE,sep=",") 
names(data) 
wts=data[4] 
head(wts) 
head(data, n=18) 
try=data[1:3] 
try 

输出：

> data <- read.csv(file="mini_r_weights.csv",head=TRUE,sep=",") 

> names(data) 
[1] "Date" "Symbol" "Close" "Weight" 

> wts=data[4] 

> head(wts) 
    Weight 
1 0.3 
2 0.3 
3 0.3 
4 0.3 
5 0.3 
6 0.3 

> head(data, n=18) 
     Date Symbol  Close Weight 
1 1/13/2012 AAPL 54.90965 0.30 
2 1/17/2012 AAPL 55.54924 0.30 
3 1/18/2012 AAPL 56.12606 0.30 
4 1/19/2012 AAPL 55.94817 0.30 
5 1/20/2012 AAPL 54.97374 0.30 
6 1/23/2012 AAPL 55.90357 0.30 
7 1/13/2012 DIS 36.19277 0.25 
8 1/17/2012 DIS 36.26817 0.25 
9 1/18/2012 DIS 36.77713 0.25 
10 1/19/2012 DIS 37.17299 0.25 
11 1/20/2012 DIS 37.05046 0.25 
12 1/23/2012 DIS 36.99391 0.25 
13 1/13/2012 IBM 158.84454 0.45 
14 1/17/2012 IBM 159.58929 0.45 
15 1/18/2012 IBM 160.53796 0.45 
16 1/19/2012 IBM 160.05033 0.45 
17 1/20/2012 IBM 167.14319 0.45 
18 1/23/2012 IBM 168.43763 0.45 

> try=data[1:3] 

> try 
     Date Symbol  Close 
1 1/13/2012 AAPL 54.90965 
2 1/17/2012 AAPL 55.54924 
3 1/18/2012 AAPL 56.12606 
4 1/19/2012 AAPL 55.94817 
5 1/20/2012 AAPL 54.97374 
6 1/23/2012 AAPL 55.90357 
7 1/13/2012 DIS 36.19277 
8 1/17/2012 DIS 36.26817 
9 1/18/2012 DIS 36.77713 
10 1/19/2012 DIS 37.17299 
11 1/20/2012 DIS 37.05046 
12 1/23/2012 DIS 36.99391 
13 1/13/2012 IBM 158.84454 
14 1/17/2012 IBM 159.58929 
15 1/18/2012 IBM 160.53796 
16 1/19/2012 IBM 160.05033 
17 1/20/2012 IBM 167.14319 
18 1/23/2012 IBM 168.43763 

我所需要的数据（在这种情况下， “试”），在下面的格式：

Date   AAPL  DIS   IBM 
1/13/2012 54.90964982 36.19276852 158.8445426 
1/17/2012 55.54924437 36.26817012 159.5892927 
1/18/2012 56.12605664 36.77713093 160.5379623 
1/19/2012 55.94817349 37.17298933 160.0503284 
1/20/2012 54.97374008 37.05046173 167.1431858 
1/23/2012 55.90357191 36.99391053 168.4376323 

谢谢

Answer 1

这将使用r eshape2 dcast功能。这个问题之前已经在这里找到答案，你可以阅读更多关于投功能here和here

真的很快，虽然，这里是你的可能是什么样子：

d = dcast(try, Date~Symbol) 

Answer 2

尝试dcast如下图所示

library(reshape2) 
library(xts) 
data <-read.table(read.csv(file="mini_r_weights.csv",head=TRUE,sep=",") 
names(data) 
wts=data[4] 
head(wts) 
head(data, n=18) 
try=data[1:3] 
try 
temp=dcast(data,Date~Symbol,value.var="Close") 

的结果是

> temp 
    Date  AAPL  DIS  IBM 
1 1/13/12 54.90965 36.19277 158.8445 
2 1/17/12 55.54924 36.26817 159.5893 
3 1/18/12 56.12606 36.77713 160.5380 
4 1/19/12 55.94817 37.17299 160.0503 
5 1/20/12 54.97374 37.05046 167.1432 
6 1/23/12 55.90357 36.99391 168.4376