2
Name of member Allowance Type             Expenditure Type  Date          Amount, £

Adam Afriyie Office running costs (IEP/AOE) Incidentals     07/03/2009 111.09
Adam Afriyie Office running costs (IEP/AOE) Incidentals     11/05/2009 111.09
Adam Afriyie Office running costs (IEP/AOE) Incidentals     11/05/2009 51.75
Adam Holloway   Office running costs (IEP/AOE)  Incidentals  10/01/2009  35
Adam Holloway   Office running costs (IEP/AOE)  Incidentals  10/01/2009  413.23
Adam Holloway   Office running costs (IEP/AOE)  Incidentals  10/01/2009  9.55
Adam Holloway   Office running costs (IEP/AOE   IT equipment 07/03/2009 890.01
Adam Holloway   Communications Expenditure   Publications   12/04/2009  1774
Adam Holloway   Office running costs (IEP/AOE)  Incidentals  12/08/2009  1.1
Adam Holloway   Office running costs (IEP/AOE   Incidentals  12/08/2009  64.31
Adam Holloway   Office running costs (IEP/AOE)  Incidentals  12/08/2009  64.31

Hi im new to R and new to programming. This is a subset of the MP's expenses during a certain time period. I want to subtotal each MP's expenses and i used the code from another post

> aggregate(cbind(bsent, breturn, tsent, treturn, csales) ~ yname, data = foo, 
 +           FUN = sum)

and edited it to my own situation.

my code:

expenses2 <- aggregate(cbind(Amount..Â.) ~ Name.of.member, data = expenses, FUN = sum)

now although this code does do some sort of aggregation the numbers do not match up. for example one can calculate that Adam Afriyie's expenses are £273.93 however this code gives a result of 12697. I have no idea what this number represents. Can someone help me and tell me what im doing wrong??

Thank you in advance

mjv
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ATM
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    please, don't use special signs in variable names. Theoretically R can deal with them, but they tend to give some surprises. Plus, you don't need to do cbind(Amount)~Name.of.member, you can just do aggregate(Amount,Name.of.member,data=expenses,FUN=sum). Try that and see if you still have a wrong number – Joris Meys Dec 02 '10 at 16:36
  • Can you post the URL of the original data file? – James Dec 03 '10 at 10:40
  • Perhaps your Amount is being read in as a factor? A look at str (foo) would be able to tell you for sure. –  Dec 04 '10 at 04:03

3 Answers3

2

I pulled that text into an editor. Then made valid header names and put back the tabs that had apparently been replaced with spaces and read into R getting this object:

    MPexp <- structure(list(Name_of_member = c("Adam Afriyie", "Adam Afriyie", 
    "Adam Afriyie", "Adam Holloway", "Adam Holloway", "Adam Holloway", 
    "Adam Holloway", "Adam Holloway", "Adam Holloway", "Adam Holloway", 
    "Adam Holloway"), Allowance_Type = c("Office running costs (IEP/AOE)", 
    "Office running costs (IEP/AOE)", "Office running costs (IEP/AOE)", 
    " Office running costs (IEP/AOE)", " Office running costs (IEP/AOE)", 
    " Office running costs (IEP/AOE)", " Office running costs (IEP/AOE", 
    " Communications Expenditure", " Office running costs (IEP/AOE)", 
    " Office running costs (IEP/AOE", " Office running costs (IEP/AOE)"
    ), Expenditure_Tyoe = c("Incidentals", "Incidentals", "Incidentals", 
    "Incidentals", "Incidentals", "Incidentals", "IT equipment", 
    "Publications", "Incidentals", "Incidentals", "Incidentals"), 
        Date = c("07/03/09", "11/05/09", "11/05/09", "10/01/09", 
        "10/01/09", "10/01/09", "07/03/09", "12/04/09", "12/08/09", 
        "12/08/09", "12/08/09"), Amount = c(111.09, 111.09, 51.75, 
        35, 413.23, 9.55, 890.01, 1774, 1.1, 64.31, 64.31)), .Names = c("Name_of_member", 
    "Allowance_Type", "Expenditure_Tyoe", "Date", "Amount"), 
class = "data.frame", row.names = c(NA, 
    -11L))

Now this should yield the expected result with aggregate:

> aggregate(MPexp$Amount, MPexp["Name_of_member"], sum)
  Name_of_member       x
1   Adam Afriyie  273.93
2  Adam Holloway 3251.51

Reading your question again made me realize that you were using aggregate.formula so this would also work on that data:

> aggregate(Amount ~ Name_of_member, data=MPexp, FUN=sum)
  Name_of_member  Amount
1   Adam Afriyie  273.93
2  Adam Holloway 3251.51
IRTFM
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1

Using only your name column and your last amount column:

df <- data.frame(name = c(rep("Adam Afriyie", 3), rep("Adam Holloway", 8)),
                 amount = c(111.09, 111.09, 51.75, 35,
                   413.23, 9.55, 890.01, 1774, 1.1, 64.31, 64.31)
                 )

version 1

aggregate(df$amount, by = list(name = df$name), FUN = "sum")

version 2

aggregate(amount ~ name, data = df, FUN = "sum")

output:

1  Adam Afriyie  273.93
2  Adam Holloway 3251.51
mropa
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1

Another approach using plyr

library(plyr)

#Using data from mropa's answer
> ddply(df, .(name), summarise, sum = sum(amount))
           name     sum
1  Adam Afriyie  273.93
2 Adam Holloway 3251.51
Chase
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