Hello,
I'd have a time series, where I am plotting the means and sd of a distance
for a variety of positions along a bird's bill. I'd like to set each line
(represented by "point") to start at zero, so that I can look at the
absolute change along the series. At the moment I only know how to do that
in Excel, by subtracting the value of time 1, point 1 from all other times
for point 1. My actual data set has many points ( 20 per bird, only 3 shown
here), so I would love to make this faster in R. Ideally, I would have
another column titled "adj_mean" for the adjusted means.
Here is an example.
> sort2v4
point time mean sd
1 1 1 52.501000 1.5073927
3 1 2 54.501818 0.8510329
4 1 3 56.601739 1.5787222
5 1 4 57.200000 1.2292726
6 1 5 59.300000 2.2632327
7 1 6 57.800893 1.4745218
8 1 7 55.303508 2.2661855
9 1 8 51.100943 1.8540025
10 1 9 50.600000 1.7126977
2 1 10 52.904716 1.1010460
111 2 1 50.605963 1.2633969
113 2 2 52.203828 0.7890765
114 2 3 54.100909 1.1013344
115 2 4 55.000000 1.1547005
116 2 5 57.001725 1.6341500
117 2 6 55.003591 1.5652438
118 2 7 52.911089 1.7373914
119 2 8 49.204022 1.0350809
120 2 9 48.904103 0.8747568
112 2 10 50.915700 0.8765483
131 3 1 48.608228 0.8433913
133 3 2 49.307101 0.4827703
134 3 3 51.310824 0.9424023
135 3 4 52.413350 0.6997860
136 3 5 54.116723 1.1927297
137 3 6 52.618161 1.1686288
138 3 7 49.822764 1.6303473
139 3 8 47.107336 1.2013356
140 3 9 47.104214 1.1986148
132 3 10 48.719484 0.6765047
and I would like it to look like this... (which I did in Excel). The start
of each time 1-10 has an adj_mean of 0.
> sort2v4
point time mean sd adj_mean
1 1 1 52.501 1.5073927 0
3 1 2 54.501818 0.8510329 2.000818
4 1 3 56.601739 1.5787222 4.100739
5 1 4 57.2 1.2292726 4.699
6 1 5 59.3 2.2632327 6.799
7 1 6 57.800893 1.4745218 5.299893
8 1 7 55.303508 2.2661855 2.802508
9 1 8 51.100943 1.8540025 -1.400057
10 1 9 50.6 1.7126977 -1.901
2 1 10 52.904716 1.101046 0.403716
111 2 1 50.605963 1.2633969 0
113 2 2 52.203828 0.7890765 1.597865
114 2 3 54.100909 1.1013344 3.494946
115 2 4 55 1.1547005 4.394037
116 2 5 57.001725 1.63415 6.395762
117 2 6 55.003591 1.5652438 4.397628
118 2 7 52.911089 1.7373914 2.305126
119 2 8 49.204022 1.0350809 -1.401941
120 2 9 48.904103 0.8747568 -1.70186
112 2 10 50.9157 0.8765483 0.309737
131 3 1 48.608228 0.8433913 0
133 3 2 49.307101 0.4827703 0.698873
134 3 3 51.310824 0.9424023 2.702596
135 3 4 52.41335 0.699786 3.805122
136 3 5 54.116723 1.1927297 5.508495
137 3 6 52.618161 1.1686288 4.009933
138 3 7 49.822764 1.6303473 1.214536
139 3 8 47.107336 1.2013356 -1.500892
140 3 9 47.104214 1.1986148 -1.504014
132 3 10 48.719484 0.6765047 0.111256
Thank you so much for your help.
Kristiina
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