Dear all,
I have a data frame of three columns, which I have sorted by Latitude as
follows:
> test2[60:80,]
Latitude Longitude Sim_1986
61948 85.25 -29.25 2.175345
61957 85.25 -28.75 8.750486
61967 85.25 -28.25 33.569305
61977 85.25 -27.75 23.702572
61988 85.25 -27.25 26.488602
62000 85.25 -26.75 23.915724
62012 85.25 -26.25 25.055082
62027 85.25 -25.75 26.609823
62047 85.25 -25.25 28.813068
62066 84.25 -24.75 25.069952
52341 84.75 -82.25 34.940380
52434 84.75 -81.75 56.192116
52531 84.75 -81.25 41.409431
52616 83.75 -80.75 56.717590
52701 83.75 -80.25 68.887123
52781 83.75 -79.75 74.133286
52865 83.75 -79.25 41.309422
52951 82.25 -78.75 69.863419
53052 82.25 -78.25 21.480116
53164 82.25 -77.75 58.799141
55979 82.25 -68.75 70.028358
What I am hoping to do is to use the aggregate command to calculate the mean of
Sim_1986' per 1-degree increment of Latitude. So, using the above subset of the
data frame as an example, a mean would be produced based on the Sim_1986 values
between where Latitude 85, 84, 83, 82. The maximum latitude in the dataset as a
whole is 83.75 and the minimum is -55.75.
Is it possible to also output corresponding latitude values for each 'grouped
mean', so that I can easily associate each mean value with its latitudinal band?
Many thanks for any help offered,
Steve
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