If I have a dataframe which is organized like this:
name color likes?
1 sally red 0
2 sally blue 1
3 sally green 1
4 jake red 0
5 jake blue 1
6 jake green 1
7 tom red 1
8 tom blue 0
9 tom green 0
And I want to create a matrix in the form:
red blue green
sally 0 1 1
jake 0 1 1
tom 1 0 0
Are there any built-in commands that might help me do this? Also, I
can't assume that there is an observation for every person-color. In
other words, in the original dataset, there might be some colors for
which sally offered no opinion. In some cases, this may be represented
by NA, in others, it may mean that no row exists for sally for that color.
Thank you!
Converting a dataframe to a matrix
3 messages · Jennifer Brea, Simon Blomberg, justin bem
xtabs is your friend:
xtabs(likes ~ color + name, data=dat)
color
name blue green red
jake 1 1 0
sally 1 1 0
tom 0 0 1
See ?xtabs for more info. Note that I changed the "likes?" column to
just "likes". It is a bad idea to have question marks in variable names.
Simon.
On Wed, 2009-03-11 at 01:42 -0400, Jennifer Brea wrote:
If I have a dataframe which is organized like this:
name color likes?
1 sally red 0
2 sally blue 1
3 sally green 1
4 jake red 0
5 jake blue 1
6 jake green 1
7 tom red 1
8 tom blue 0
9 tom green 0
And I want to create a matrix in the form:
red blue green
sally 0 1 1
jake 0 1 1
tom 1 0 0
Are there any built-in commands that might help me do this? Also, I
can't assume that there is an observation for every person-color. In
other words, in the original dataset, there might be some colors for
which sally offered no opinion. In some cases, this may be represented
by NA, in others, it may mean that no row exists for sally for that color.
Thank you!
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Simon Blomberg, BSc (Hons), PhD, MAppStat. Lecturer and Consultant Statistician School of Biological Sciences The University of Queensland St. Lucia Queensland 4072 Australia Room 320 Goddard Building (8) T: +61 7 3365 2506 http://www.uq.edu.au/~uqsblomb email: S.Blomberg1_at_uq.edu.au Policies: 1. I will NOT analyse your data for you. 2. Your deadline is your problem. The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. - John Tukey.
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