Re: [R] side by side histogram after splitting data by year

From: jim holtman <jholtman_at_gmail.com>
Date: Sun, 17 Apr 2011 19:29:41 -0400

Will one of these do it for you:

> str(x)

'data.frame': 550 obs. of 5 variables:

 $ year    : Factor w/ 2 levels "one","two": 1 1 1 1 1 1 1 1 1 1 ...
 $ size    : Factor w/ 2 levels "large","small": 2 2 2 2 2 2 2 2 2 2 ...
 $ distance: num  30.9 121.5 46.1 46.1 46.1 ...
 $ taken   : int  10 2 12 1 4 1 10 3 5 5 ...
 $ mass    : num  13.88 2.78 16.65 1.39 5.55 ...

> require(lattice)
> histogram(~taken|year, x)

> histogram(~taken|year*size, x)
>

On Sun, Apr 17, 2011 at 10:51 AM, Stratford, Jeffrey <jeffrey.stratford_at_wilkes.edu> wrote:
> Hi everyone,
>
>
>
> I'm looking to produce a side-by-side histogram of the number of trips
> taken by jays with a particular number of acorns after accounting for
> year (year "one" and year "two"). I know this involves indexing first
> then creating a histogram but I'm not sure how I'd do this. I want to
> explore the possibilities that jays are altering their strategies in
> different years.  Data are below.
>
>
>
> This is a common need for myself so any help would be greatly
> appreciated!
>
>
>
> Thanks,
>
>
>
> Jeff
>
>
>
>
>
>
>
> structure(list(year = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L), .Label = c("one", "two"), class = "factor"), size = structure(c(2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("large", "small"), class
> = "factor"), distance = c(30.8735, 121.505, 46.055, 46.055, 46.055,
> 9.343, 46.055, 46.055, 46.055, 85.271, 85.271, 85.271, 85.271, 85.271,
> 85.271, 30.8735, 30.8735, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343,
> 9.343, 152.717, 152.717, 152.717, 152.717, 152.717, 152.717, 152.717,
> 46.055, 46.055, 152.717, 152.717, 20.698, 20.698, 17.217, 17.217, 9.343,
> 9.343, 17.217, 46.055, 152.717, 46.055, 17.217, 152.717, 17.217, 17.217,
> 46.055, 30.8735, 30.8735, 30.8735, 5.69, 30.8735, 17.217, 30.8735,
> 30.8735, 30.8735, 30.8735, 30.8735, 9.343, 9.343, 17.217, 17.217,
> 17.217, 17.217, 17.217, 17.217, 9.343, 9.343, 17.217, 17.217, 17.217,
> 20.698, 17.217, 17.217, 17.217, 5.42, 17.217, 17.217, 17.217, 9.343,
> 30.8735, 30.8735, 30.8735, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343,
> 9.343, 9.343, 9.343, 9.343, 9.343, 9.343, 17.217, 9.343, 9.343, 9.343,
> 9.343, 9.343, 9.343, 9.343, 9.343, 30.8735, 30.8735, 17.217, 17.217,
> 46.055, 36.239, 17.217, 17.217, 17.217, 46.055, 30.8735, 30.8735,
> 17.217, 17.217, 17.217, 121.505, 152.717, 152.717, 17.217, 152.717,
> 121.505, 121.505, 121.505, 121.505, 121.505, 9.343, 121.505, 9.343,
> 121.505, 121.505, 30.8735, 121.505, 17.217, 17.217, 17.217, 9.343,
> 30.8735, 85.271, 85.271, 85.271, 85.271, 85.271, 85.271, 9.343, 85.271,
> 85.271, 85.271, 85.271, 20.698, 9.343, 30.8735, 17.217, 20.698, 30.8735,
> 17.217, 85.271, 121.505, 121.505, 85.271, 85.271, 85.271, 85.271,
> 121.505, 121.505, NA, 121.505, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343,
> 9.343, 30.8735, 17.217, 9.343, 9.343, 9.343, 30.8735, 30.8735, 30.8735,
> 9.343, 9.343, 30.8735, 17.217, 5.42, 17.217, 85.271, 85.271, 30.8735,
> 30.8735, 30.8735, 30.8735, 30.8735, 30.8735, 17.217, 85.271, 17.217,
> 30.8735, 30.8735, 85.271, 30.8735, 30.8735, 85.271, 30.8735, 30.8735,
> 30.8735, 30.8735, 30.8735, 30.8735, 17.217, 30.8735, 9.343, 30.8735,
> 30.8735, 30.8735, 30.8735, 9.343, 30.8735, 30.8735, 17.217, 9.343,
> 9.343, 9.343, 85.271, 30.8735, 30.8735, 46.055, 5.69, 85.271, 85.271,
> 17.217, 46.055, 85.271, 30.8735, 85.271, 46.055, 121.505, 121.505,
> 121.505, 17.217, 17.217, 25.508, 9.343, 17.217, 17.217, 9.343, 17.217,
> 9.343, 17.217, 34.35, 34.35, 46.055, 46.055, 9.343, 20.698, 17.217,
> 27.25, 20.54, 27.25, 20.698, 17.217, 20.698, 20.698, 15, 15, 8.35,
> 13.63, 20.34, 17.217, 5.69, 7.5, 7.5, 7.5, 7.5, 7.5, 7.5, 7.5, 7.5, 7.5,
> 30, 17.217, 5, 5, 5, 7.93, 7.93, 7.93, 5, 7.71, 5, 17.217, 8.175, 8.175,
> 6.69, 6.69, 6.69, 10.875, 5.345, 5.345, 5.345, 5.345, 3.54, 10.755,
> 10.755, 10.755, 19.61, 20.145, 20.145, 20.145, 10.34, 5.35, 6.34, 10.34,
> 5.35, 10.34, 9.343, 9.343, 9.343, 9.343, 137.111, 17.217, 137.111,
> 17.217, 137.111, 137.111, 17.217, 46.055, 46.055, 17.217, 17.77, 20.54,
> 17.217, 17.217, 20.54, 11.75, 11.75, 17.217, 56.89, 20.54, 20.54, 55,
> 75, 75, 75, 19.61, 19.61, 19.61, 19.61, 19.61, 25.508, 20.698, 5.42,
> 5.42, 19.61, 19.61, 19.61, 20.698, 5.42, 25.508, 5.42, 17.217, 16.92,
> 9.343, 9.343, 19.61, 9.343, 19.61, 19.61, 16.92, 16.92, 16.92, 5.42,
> 5.42, 19.61, 5.42, 9.343, 19.61, 5.42, 5.42, 19.61, 9.343, 46.055,
> 17.217, 5.42, 19.61, 5.69, 19.61, 17.217, 9.343, 5.42, 19.61, 19.61,
> 17.217, 35.508, 5.42, 5.42, 5.42, 19.61, 17.217, 5.69, 19.61, 19.61,
> 8.35, 17.217, 5.69, 19.61, 5.69, 5.69, 17.217, 19.61, 16.92, 19.61,
> 17.217, 9.343, 5.42, 17.217, 17.217, 9.343, 33.456, 17.217, 46.055,
> 137.11, 56.89, 54.25, 17.217, 56.89, 55, 17.217, 46.055, 20.698, 46.055,
> 54.25, 27.25, 53.5, 5.69, 53.5, 20.698, 20.698, 5.69, 17.217, 17.217,
> 17.217, 17.217, 17.217, 5.69, 17.217, 17.217, 17.217, 11.75, 17.217,
> 5.69, 11.75, 11.75, 5.42, 5.42, 17.217, 5.69, 20.54, 11.75, 5.69, 11.75,
> 17.217, 121.505, 121.505, 121.505, 11.75, 5.69, 11.75, 11.75, 20.698,
> 121.505, 17.217, 11.75, 17.217, 5.42, 17.217, 17.217, 5.42, 5.69,
> 121.505, 17.217, 5.42, 46.055, 5.69, 20.698, 46.055, 15.86, 15.86, 5.69,
> 5.69, 11.75, 5.42, 46.055, 5.42, 10.349, 121.505, 15.86, 25.508, 17.217,
> 17.217, 11.75, 17.217, 17.217, 17.217, 17.217, 17.217, 17.217, 46.055,
> 17.217, 17.217, 17.217, 17.217, 17.217, 5.42, 17.217, 17.217, 17.217,
> 9.343, 85.271, 46.055, 17.217, 17.217, 46.055, 25.508, 25.508, 25.508,
> 20.698, 19.61, 11.75, 11.75, 11.75, 20.698, 11.75, 11.75, 20.45, 11.75,
> 20.45, 20.45, 7.5, 11.75, 11.75, 20.45), taken = c(10L, 2L, 12L, 1L, 4L,
> 1L, 10L, 3L, 5L, 5L, 1L, 5L, 3L, 3L, 5L, 2L, 4L, 2L, 1L, 4L, 1L, 1L, 2L,
> 1L, 3L, 1L, 3L, 2L, 3L, 2L, 2L, 1L, 4L, 1L, 5L, 2L, 2L, 2L, 2L, 2L, 1L,
> 1L, 1L, 1L, 1L, 1L, 3L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 1L, 2L, 3L, 2L, 2L,
> 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 4L, 2L, 3L,
> 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 3L, 1L,
> 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 3L, 4L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L,
> 1L, 2L, 3L, 2L, 1L, 1L, 5L, 1L, 1L, 5L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 1L,
> 1L, 1L, 3L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L,
> 1L, 3L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L,
> 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L,
> 3L, 1L, 1L, 1L, 2L, 1L, 2L, 3L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
> 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
> 3L, 2L, 1L, 2L, 2L, 2L, 1L, 3L, 2L, 2L, 3L, 3L, 2L, 1L, 1L, 2L, 1L, 1L,
> 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 2L,
> 4L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 3L, 3L, 2L, 2L, 4L, 1L,
> 2L, 4L, 3L, 3L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 2L, 3L, 2L,
> 2L, 2L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 2L, 2L, 3L, 2L, 3L, 2L, 3L, 1L, 2L, 2L, 1L, 2L, 3L, 2L, 2L, 3L,
> 2L, 1L, 2L, 1L, 2L), mass = c(13.8758, 2.77516, 16.65096, 1.38758,
> 5.55032, 1.38758, 13.8758, 4.16274, 6.9379, 6.9379, 1.38758, 6.9379,
> 4.16274, 4.16274, 6.9379, 2.77516, 5.55032, 2.77516, 1.38758, 5.55032,
> 1.38758, 1.38758, 2.77516, 1.38758, 4.16274, 1.38758, 4.16274, 2.77516,
> 4.16274, 2.77516, 2.77516, 1.38758, 5.55032, 1.38758, 6.9379, 2.77516,
> 2.77516, 5.49268, 5.49268, 5.49268, 2.74634, 2.74634, 2.74634, 2.74634,
> 2.74634, 2.74634, 8.23902, 1.295, 3.885, 2.59, 2.59, 3.885, 2.59, 3.885,
> 1.295, 2.59, 3.885, 2.59, 2.59, 2.59, 1.295, 2.59, 2.59, 2.59, 1.295,
> 1.295, 1.295, 1.295, 1.295, 1.295, 2.59, 3.885, 2.59, 1.295, 5.18, 2.59,
> 3.885, 2.59, 1.295, 2.59, 1.295, 1.295, 1.295, 2.59, 2.59, 2.59, 2.59,
> 1.295, 2.59, 2.59, 2.59, 1.295, 2.59, 3.885, 1.295, 1.295, 1.295, 3.885,
> 1.295, 1.295, 1.295, 1.295, 1.295, 3.885, 5.18, 2.59, 1.295, 1.4429,
> 2.8858, 1.4429, 1.4429, 2.8858, 1.4429, 1.4429, 2.8858, 4.3287, 2.8858,
> 1.4429, 1.4429, 7.2145, 1.4429, 1.4429, 7.2145, 1.4429, 1.4429, 1.4429,
> 1.4429, 1.4429, 2.8858, 4.3287, 1.4429, 1.4429, 1.4429, 4.3287, 1.4429,
> 2.8858, 2.8858, 2.8858, 1.4429, 2.877, 2.877, 2.877, 2.877, 5.754,
> 2.877, 2.877, 2.877, 2.877, 2.877, 2.877, 8.631, 2.877, 2.877, 5.754,
> 2.877, 2.877, 2.877, 2.877, 5.754, 2.877, 2.877, 2.877, 2.877, 5.754,
> 5.754, 2.877, 2.877, 2.877, 2.877, 2.877, 2.877, 1.3719, 1.3719, 1.3719,
> 1.3719, 1.3719, 2.7438, 1.3719, 2.7438, 1.3719, 1.3719, 2.7438, 2.7438,
> 1.3719, 1.3719, 1.3719, 1.3719, 2.7438, 1.3719, 1.3719, 2.7438, 1.3719,
> 2.7438, 1.3719, 1.3719, 1.3719, 1.3719, 1.3719, 4.1157, 1.3719, 1.3719,
> 1.3719, 1.3719, 4.1157, 1.3719, 1.3719, 1.3719, 2.7438, 1.3719, 2.7438,
> 4.1157, 1.3719, 2.7438, 1.3719, 2.7438, 2.7438, 2.7438, 2.7438, 2.7438,
> 1.3719, 1.3719, 2.7438, 2.7438, 1.3719, 1.3719, 1.3719, 2.8316, 2.8316,
> 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316,
> 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316,
> 2.8316, 1.17028, 2.34056, 1.17028, 1.17028, 1.17028, 1.17028, 1.17028,
> 1.17028, 2.34056, 2.34056, 3.51084, 2.34056, 1.17028, 2.34056, 2.34056,
> 2.34056, 1.17028, 3.51084, 2.34056, 2.34056, 3.51084, 3.51084, 2.34056,
> 1.17028, 2.03456, 4.06912, 2.03456, 2.03456, 2.03456, 4.06912, 2.03456,
> 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
> 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
> 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
> 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
> 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 4.06912, 2.03456,
> 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 1.189102041, 1.189102041,
> 1.189102041, 2.378204082, 3.567306123, 2.378204082, 4.756408164,
> 2.378204082, 2.378204082, 2.378204082, 1.189102041, 1.189102041,
> 1.189102041, 1.189102041, 2.378204082, 1.189102041, 2.378204082,
> 1.189102041, 3.567306123, 3.567306123, 2.378204082, 2.378204082,
> 4.756408164, 1.189102041, 2.378204082, 4.756408164, 3.567306123,
> 3.567306123, 4.756408164, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232,
> 2.45232, 2.45232, 2.45232, 2.45232, 4.90464, 2.45232, 2.45232, 2.45232,
> 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 4.90464, 4.90464,
> 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232,
> 4.90464, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232,
> 2.45232, 2.45232, 7.35696, 2.45232, 2.45232, 2.45232, 4.90464, 2.45232,
> 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 4.90464,
> 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232,
> 2.45232, 2.45232, 2.45232, 2.45232, 4.90464, 2.45232, 2.45232, 2.45232,
> 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.64516, 1.76344, 1.76344,
> 1.76344, 2.64516, 2.64516, 1.76344, 1.76344, 1.76344, 2.64516, 1.76344,
> 1.76344, 1.76344, 1.76344, 1.76344, 1.76344, 2.64516, 2.64516, 0.88172,
> 0.88172, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
> 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
> 2.46532, 2.46532, 4.93064, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
> 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 4.93064,
> 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 4.93064, 2.46532, 2.46532,
> 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 4.93064, 2.46532,
> 2.46532, 4.93064, 2.46532, 2.46532, 2.46532, 4.93064, 4.93064, 2.46532,
> 4.93064, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
> 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939,
> 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939,
> 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939,
> 2.28446939, 2.28446939, 4.56893878, 4.568938778, 6.853408167,
> 4.56893878, 6.85340817, 4.56893878, 6.85340817, 2.28446939, 4.56893878,
> 4.568938778, 2.284469389, 4.56893878, 6.85340817, 4.56893878,
> 4.56893878, 6.85340817, 4.56893878, 2.28446939, 4.56893878, 2.28446939,
> 4.56893878 )), .Names = c("year", "size", "distance", "taken", "mass"),
> class = "data.frame", row.names = c(NA,
>
> -550L))
>
>
>
>
>
> *****************************************
>
> Jeffrey A. Stratford, Ph.D.
>
> Department of Health and Biological Sciences
>
> 84 W. South St.
>
> Wilkes Univertsity, PA 18766
>
> 570-332-2942
>
> http://web.wilkes.edu/jeffrey.stratford/
>
> *****************************************
>
>
>
>
>        [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help_at_r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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>

-- 
Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?

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