with(lili,plot(y,conc,pch=sample,col=sample,log="y"))
gives a better plot
Clint Bowman INTERNET: cl...@ecy.wa.gov
Air Quality Modeler INTERNET: cl...@math.utah.edu
Department of Ecology VOICE: (360) 407-6815
PO Box 47600 FAX: (360) 407-7534
Olympia, WA 98504-7600
USPS: PO Box 47600, Olympia, WA 98504-7600
Parcels: 300 Desmond Drive, Lacey, WA 98503-1274
On Tue, 30 Aug 2016, Clint Bowman wrote:
Hanna,
lili<-read.table("lili.txt",header=T) # don't forget to label the row number
if it's in your data
with(lili,plot(y,conc,pch=sample,col=sample))
Clint
Clint Bowman INTERNET: cl...@ecy.wa.gov
Air Quality Modeler INTERNET: cl...@math.utah.edu
Department of Ecology VOICE: (360) 407-6815
PO Box 47600 FAX: (360) 407-7534
Olympia, WA 98504-7600
USPS: PO Box 47600, Olympia, WA 98504-7600
Parcels: 300 Desmond Drive, Lacey, WA 98503-1274
On Tue, 30 Aug 2016, li li wrote:
Hi all,
I have the following data. I want to plot the data (y ~ conc)
with different symbols and colors corresponding to different levels of the
factor sample.
I could create a column with color and pch and then do the plot, but I am
sure there are much better ways.
Can anyone make suggestions?
Hanna
y conc sample
1 33 20.000000000 1
2 33 5.000000000 1
3 35 1.250000000 1
4 43 0.312500000 1
5 58 0.078125000 1
6 54 0.019531250 1
7 57 0.004882812 1
8 57 0.001220703 1
9 32 20.000000000 1
10 32 5.000000000 1
11 34 1.250000000 1
12 52 0.312500000 1
13 57 0.078125000 1
14 58 0.019531250 1
15 59 0.004882812 1
16 50 0.001220703 1
17 34 20.000000000 2
18 34 5.000000000 2
19 38 1.250000000 2
20 53 0.312500000 2
21 57 0.078125000 2
22 57 0.019531250 2
23 57 0.004882812 2
24 52 0.001220703 2
25 34 20.000000000 2
26 33 5.000000000 2
27 36 1.250000000 2
28 48 0.312500000 2
29 58 0.078125000 2
30 57 0.019531250 2
31 58 0.004882812 2
32 53 0.001220703 2
33 34 20.000000000 2
34 35 5.000000000 2
35 37 1.250000000 2
36 49 0.312500000 2
37 55 0.078125000 2
38 59 0.019531250 2
39 57 0.004882812 2
40 54 0.001220703 2
41 36 20.000000000 3
42 33 5.000000000 3
43 36 1.250000000 3
44 51 0.312500000 3
45 57 0.078125000 3
46 57 0.019531250 3
47 59 0.004882812 3
48 56 0.001220703 3
49 33 20.000000000 3
50 32 5.000000000 3
51 35 1.250000000 3
52 47 0.312500000 3
53 57 0.078125000 3
54 56 0.019531250 3
55 57 0.004882812 3
56 53 0.001220703 3
57 33 20.000000000 3
58 34 5.000000000 3
59 38 1.250000000 3
60 52 0.312500000 3
61 56 0.078125000 3
62 61 0.019531250 3
63 56 0.004882812 3
64 55 0.001220703 3
[[alternative HTML version deleted]]
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