CODEWITHSUNDEEP
r
Uzay26
Uzay26

Reputation: 21

frequency table with several CALCULATED variables in R

R Newbie has a simple data table (DT) that has the number of households (NumHH) in several United States (Residences):

NumHH   Residence
6   AK
4   AL
7   AR
6   AZ
1   CA
2   CO
2   CT
1   AK
4   AL
6   AR
3   AZ
1   CA
6   CO
3   CT
5   AL

By using with(), 

with(DT, table(NumHH, Residence))

I can get a table that's close to what I want:

     Residence
NumHH AK AL AR AZ CA CO CT
    1  1  0  0  0  2  0  0
    2  0  0  0  0  0  1  1
    3  0  0  0  1  0  0  1
    4  0  2  0  0  0  0  0
    5  0  1  0  0  0  0  0
    6  1  0  1  1  0  1  0
    7  0  0  1  0  0  0  0

but I need a table that provides the frequency of several ranges per residence. The frequencies are calculated this way:

##Frequency of ranges per State
One <- DT$NumHH <=1                             ##Only 1 person/household
Two_Four <- ((DT$NumHH <=4) - (DT$NumHH <=1))   ##2 to 4 people in Household
OverFour <- DT$NumHH >4                         ##More than 4 people in HH

Ideally, the result would look like this:

            Residence
NumHH       AK AL AR AZ CA CO CT
  One       1  0  0  0  2  0  0
  Two_Four  0  2  0  1  0  1  2
  OverFour  1  1  2  1  0  1  0

I've tried:

  1. with() - I am only able to do one range at a time with "with()", such as: with(DT, table (One, Residence)) - and that gives me a FALSE row and a TRUE row by state.

  2. data.frames asks me to name each state ("AK", "AL", "AR", etc.), but with() already knows.

  3. I have also tried ddply, but got a list of each calculation's (150 unlabeled rows in 4 columns - not the desired 3 labeled rows in 50 columns for each state), so I'm obviously not doing it right.

Any assistance is greatly appreciated.

Upvotes: 2

Views: 87

Answers (1)

thelatemail
thelatemail

Reputation: 93803

Use ?cut to establish your groups before using table:

with(dat, table( NumHH=cut(NumHH, c(0,1,4,Inf), labels=c("1","2-4",">4")), Residence))
#     Residence
#NumHH AK AL AR AZ CA CO CT
#  1    1  0  0  0  2  0  0
#  2-4  0  2  0  1  0  1  2
#  >4   1  1  2  1  0  1  0

Upvotes: 3

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