[R] two questions for R beginners
Petr PIKAL
petr.pikal at precheza.cz
Wed Mar 3 16:36:45 CET 2010
Hi
that is why I consider matrix is just a vector with dimensions and
data.frame is a rectangular structure similar to Excel table. That saved
me a lot of surprises.
But I must admit I am not a real beginner nowadays although I still learn
when using R, reading help list and trying sometimes to help others.
Regards
Petr
"John Sorkin" <jsorkin at grecc.umaryland.edu> napsal dne 03.03.2010
16:30:39:
> Petr,
> On the other hand . . .
>
> > mat<-matrix(1:12, 3,4)
> > dat<-as.data.frame(mat)
> > mat
> [,1] [,2] [,3] [,4]
> [1,] 1 4 7 10
> [2,] 2 5 8 11
> [3,] 3 6 9 12
> > dat
> V1 V2 V3 V4
> 1 1 4 7 10
> 2 2 5 8 11
> 3 3 6 9 12
>
> What you are demonstrating by your example is the manner in which the
data are
> organized deep in the guts of R, not the way people, especially R
beginners
> visualize objects in their mind. When I think of the integer sixty-nine,
I
> visualize 69, not 1000101 despite the fact that 69, as an integer is
> represented in the computer as 1000101.
> John
>
>
>
>
>
>
>
> John David Sorkin M.D., Ph.D.
> Chief, Biostatistics and Informatics
> University of Maryland School of Medicine Division of Gerontology
> Baltimore VA Medical Center
> 10 North Greene Street
> GRECC (BT/18/GR)
> Baltimore, MD 21201-1524
> (Phone) 410-605-7119
> (Fax) 410-605-7913 (Please call phone number above prior to faxing)>>>
Petr
> PIKAL <petr.pikal at precheza.cz> 3/3/2010 9:44 AM >>>
> "John Sorkin" <jsorkin at grecc.umaryland.edu> napsal dne 01.03.2010
> 15:19:10:
>
> > If it looks like a duck and quacks like a duck, it ought to behave
like
> a duck.
> >
> > To the user a matrix and a dataframe look alike . . . except a
dataframe
> can
>
> Well, matrix looks like a data.frame only on the first sight.
>
> mat<-matrix(1:12, 3,4)
> dat<-as.data.frame(mat)
>
>
> str(dat)
> 'data.frame': 3 obs. of 4 variables:
> $ V1: int 1 2 3
> $ V2: int 4 5 6
> $ V3: int 7 8 9
> $ V4: int 10 11 12
>
> str(mat)
> int [1:3, 1:4] 1 2 3 4 5 6 7 8 9 10 ...
>
> seems to me a pretty different look like.
>
> Regards
> Petr
>
>
> > hold non-numeric values. Thus to the users, a matrix looks like a
> special case
> > of a DF, or perhaps conversely. If you can address elements of one
> structure
> > using a given syntax, you should be able to address elements of the
> other
> > structure using the same syntax. To do otherwise leads to confusion
and
> is
> > counter intuitive.
> > John
> >
> >
> >
> >
> > John David Sorkin M.D., Ph.D.
> > Chief, Biostatistics and Informatics
> > University of Maryland School of Medicine Division of Gerontology
> > Baltimore VA Medical Center
> > 10 North Greene Street
> > GRECC (BT/18/GR)
> > Baltimore, MD 21201-1524
> > (Phone) 410-605-7119
> > (Fax) 410-605-7913 (Please call phone number above prior to faxing)>>>
> Petr
> > PIKAL <petr.pikal at precheza.cz> 3/1/2010 8:57 AM >>>
> > Hi
> >
> > r-help-bounces at r-project.org napsal dne 01.03.2010 13:03:24:
> >
> > < snip>
> >
> > > >
> > > > I understand that 2 dimensional rectangular matrix looks quite
> > > > similar to data frame however it is only a vector with dimensions.
> > > > As such it can have items of only one type (numeric, character,
> ...).
> > > > And you can easily change dimensions of matrix.
> > > >
> > > > matrix<-1:12
> > > > dim(matrix) <- c(2,6)
> > > > matrix
> > > > dim(matrix) <- c(2,2,3)
> > > > matrix
> > > > dim(matrix) <-NULL
> > > > matrix
> > > >
> > > > So rectangular structure of printed matrix is a kind of
coincidence
> > > > only, whereas rectangular structure of data frame is its main
> feature.
> > > >
> > > > Regards
> > > > Petr
> > > >>
> > > >> --
> > > >> Karl Ove Hufthammer
> > >
> > > Petr, I think that could be confusing! The way I see it is that
> > > a matrix is a special case of an array, whose "dimension" attribute
> > > is of length 2 (number of "rows", number of "columns"); and "row"
> > > and "column" refer to the rectangular display which you see when
> > > R prints to matrix. And this, of course, derives directly from
> > > the historic rectangular view of a matrix when written down.
> > >
> > > When you went from "dim(matrix)<-c(2,6)" to "dim(matrix)<-c(2,2,3)"
> > > you stripped it of its special title of "matrix" and cast it out
> > > into the motley mob of arrays (some of whom are matrices, but
> > > "matrix" no longer is).
> > >
> > > So the "rectangular structure of printed matrix" is not a
coincidence,
> > > but is its main feature!
> >
> > Ok. Point taken. However I feel that possibility to manipulate
> > matrix/array dimensions by simple changing them as I showed above
> > together with perceiving matrix as a **vector with dimensions**
> prevented
> > me especially in early days from using matrices instead of data frames
> and
> > vice versa.
> >
> > Consider cbind and rbind confusing results for vectors with unequal
> mode.
> > Far to often we can see something like that
> >
> > > cbind(1:2,letters[1:2])
> > [,1] [,2]
> > [1,] "1" "a"
> > [2,] "2" "b"
> >
> > instead of
> >
> > > data.frame(1:2,letters[1:2])
> > X1.2 letters.1.2.
> > 1 1 a
> > 2 2 b
> >
> > and then a question why does not the result behave as expected. Each
> type
> > of object has some features which is good for some type of
> > manipulation/analysis/plotting bud quite detrimental for others.
> >
> > Regards
> > Petr
> >
> >
> > >
> > > To come back to Karl's query about why "$" works for a dataframe
> > > but not for a matrix, note that "$" is the extractor for getting
> > > a named component of a list. So, Karl, when you did
> > >
> > > d=head(iris[1:4])
> > >
> > > you created a dataframe:
> > >
> > > str(d)
> > > # 'data.frame': 6 obs. of 4 variables:
> > > # $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4
> > > # $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9
> > > # $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7
> > > # $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4
> > >
> > > (with named components "Sepal.Length", ... , "Petal.Width"),
> > > and a dataframe is a special case of a general list. In a
> > > general list, the separate components can each be anything.
> > > In a dataframe, each component is a vector; the different
> > > vectors may be of different types (logical, numeric, ... )
> > > but of course the elements of any single vector must be
> > > of the same type; and, in a dataframe, all the vectors must
> > > have the same length (otherwise it is a general list, not
> > > a dataframe).
> > >
> > > So, when you print a dataframe, R chooses to display it
> > > as a rectangular structure. On the other hand, when you
> > > print a general list, R displays it quite differently:
> > >
> > > d
> > > # Sepal.Length Sepal.Width Petal.Length Petal.Width
> > > # 1 5.1 3.5 1.4 0.2
> > > # 2 4.9 3.0 1.4 0.2
> > > # 3 4.7 3.2 1.3 0.2
> > > # 4 4.6 3.1 1.5 0.2
> > > # 5 5.0 3.6 1.4 0.2
> > > # 6 5.4 3.9 1.7 0.4
> > >
> > > d3 <- list(C1=c(1.1,1.2,1.3), C2=c(2.1,2.2,2.3,2.4))
> > > d3
> > > # $C1
> > > # [1] 1.1 1.2 1.3
> > > # $C2
> > > # [1] 2.1 2.2 2.3 2.4
> > >
> > > Notice the similarity (though not identity) between the print
> > > of d3 and the output of str(d). There is a bit more hard-wired
> > > stuff built into a dataframe which makes it more than simply
> > > a "list with all components vectors of equal length). However,
> > > one could also say that "the rectangular structure is its
> > > main feature".
> > >
> > > As to why "$" will not work on matrices: a matrix, as Petr
> > > points out, is a vector with a "dimensions" attribute which
> > > has length 2 (as opposed to a general array where the length
> > > of the dimensions attribute could be anything). Hence it is
> > > not a list of named components in the sense of "list".
> > >
> > > Hence "$" will not work with a matrix, since "$" will not
> > > be able to find any list-components. which is basically what
> > > the error message
> > >
> > > d2$Sepal.Width
> > > # Error in d2$Sepal.Width : $ operator is invalid for atomic
vectors
> > >
> > > is telling you: d2 is an atomic vector with a length-2 dimensions
> > > attribute. It has no list-type components for "$" to get its
> > > hands on.
> > >
> > > Ted.
> > >
> > > --------------------------------------------------------------------
> > > E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk>
> > > Fax-to-email: +44 (0)870 094 0861
> > > Date: 01-Mar-10 Time: 12:03:21
> > > ------------------------------ XFMail ------------------------------
> > >
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