rearranging dataframe in r

Question

I am trying to work with some existing stock data I have. Ultimately I want to generate weighted returns on the data but I need to change it's structure first.

Existing Code:

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

Output:

> 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

I need the data (in this case "try") in the format below:

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

thank you

Answer 1

This would be done using reshape2 dcast function. This question has been answered here before, and you can read more about the cast function here and here

Really quickly though, here is how yours might look:

d = dcast(try, Date~Symbol)

Answer 2

Try dcast as shown below

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")

The results are

> 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