One way. there may be better. The apply function will work with just
one row (or one column) at a time.
> DF
Month Week Estpassage MedFL
1 July 27 665 34
2 July 28 2232 35
3 July 29 9241 35
4 July 30 28464 35
5 Aug 31 41049 35
6 Aug 32 82216 35
7 Aug 33 230411 35
8 Aug 34 358541 35
9 Sept 35 747839 35
10 Sept 36 459682 36
11 Sept 37 609567 36
12 Sept 38 979475 36
13 Sept 39 837189 36
Build a function, say we call it switch.cond:
switch.cond <- function (x) {
if (x["Week"] >= 33) return( fun1(x) ) else
return( fun2(x) ) }
# Build two more functions to handle the dispatched rows
fun1 <-function(x){ cat("do function 1\n") }
# replace the cat-call with your first calculation
fun2 <-function(x){ cat("do function 2\n") }
# and use various x["<colname>"]'s as arguments
> apply(DF, 1, switch.cond)
do function 2
do function 2
do function 2
do function 2
do function 2
do function 2
do function 1
do function 1
do function 1
do function 1
do function 1
do function 1
do function 1
NULL
HTH:
David Winsemius
On Feb 9, 2009, at 5:11 PM, Jesús Guillermo Andrade wrote:
Dear Sirs: I've been working with several variables in a dataframe
that serve as part of a calculation that I need to perform in a
different way depending on its value. Let me explain:
The main dataframe is called llmcc
llmcc : 'data.frame': 283 obs. of 11 variables:
$ Area : num 308.8 105.6 51.4 51.4 52.9 ...
$ mFondo : num 30.1 10 10.2 10.2 40.4 ...
$ mFachada : num 22.95 6.7 4.72 4.72 4.72 ...
$ Marca : Factor w/ 132 levels "AA_Movilnet",..: 11 32 82 82 32
32 32 32 32 32 ...
$ Clase : int 8 4 1 1 1 1 1 1 12 1 ...
$ Categoria: int 2 6 6 6 1 1 1 1 1 1 ...
$ Phi : num 0.128 0.147 0.217 0.217 0.887 ...
$ Rf : num 0.119 0.102 0.147 0.147 0.143 ...
$ OldA : num 0.737 0.258 0.375 0.375 0.385 ...
$ OldCondo : num 4436 1555 2260 2260 2318 ...
$ NewA_Jon : num 1.069 0.368 0.256 0.256 0.264 ...
I perform an initial operation using the original variables plus one
numeric (Abase) that is external and has the same number of rows than
the dataframe:
alitemp <- ((Abase/llmcc$Clase)*PClase)+(((1/llmcc
$Categoria)*Abase)*PCategoria)+((Abase*llmcc$Phi)*PPhi)+((Abase*llmcc
$Rf)*PRf)
So, after I obtain the results of this calculation, I append the
series by creating an additional column within the original dataframe:
l
lmcc$Alitmp <- alitemp
Problem is: I need to calculate a new column using a formula that has
different structure depending on the values of llmcc$Clase, thus: for
any given row of llmcc where llmcc$Clase is >= 10 i would have to
perform some operations with other values in the same row that are, by
definition, different than the ones I would need in case of lmcc$Clase
is < 10.
I've managed to break down the original dataframe by using subsets,
and then performing the calculations, but then it is complicated to
put the results in the same order of the original dataframe.
I understand the workings of the control structures available in R but
after reading the docs and help files, I can´t figure how to perform a
conditional calculation row by row that checks first the values of a
given column and then applies the corresponding operation to another
column, so it outputs a series in the same exact order as the
dataframe.
Any light that you might share with me over this will be highly
appreciated.
Thanks in advance.
Guillermo.
Nunca le preguntes a un peluquero si necesitas un corte de pelo. Ley
de Murray.
------------------------------
Jesús Guillermo Andrade (Abg.)
Gerente de Litigios y Corporativo. EDM. AC. API.
Andrade & Moreno S.C. (http://amlegal.wordpress.com/)
[[alternative HTML version deleted]]
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
