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

From: Stratford, Jeffrey <jeffrey.stratford_at_wilkes.edu>
Date: Sun, 17 Apr 2011 10:51:07 -0400


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,
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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,
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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,
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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,
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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/


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