On Apr 10, 2013, at 6:11 PM, jpm miao wrote:

Thanks for your comments, David

avg_cost_2012 and asset_2012 are numeric vectors of length 39

while x2 and y1 are longer vectors whose range is about the same as (avg_cost_2012, asset_2012)

I also present the data by dput below. Is it clear? Thanks,

I've named the first object xy and the second object y1x2

xyplot( avg_cost_2012 ~ asset_2012, data=as.data.frame(xy),
          panel=function(x,y) {
          panel.xyplot(x,y, type="p")
           panel.points( x=y1x2[,'x2'], y= y1x2[,'y1'], col="red")} )



Throwing in the scales argument does make the points from panel.points disappear.



Miao

        asset_2012      avg_cost_2012
1       3973730.0       0.0032199310
2       2391575.8       0.0034866607
3       2840943.5       0.0051450067
4       2040943.0       0.0063589398
5       1982715.2       0.0062530448
6       1618162.2       0.0054400342
7       820082.2        0.0042134623
8       1658596.8       0.0048834145
9       1762794.0       0.0062155737
10      93439.5 0.0042552036
11      218481.2        0.0069238420
12      2332477.0       0.0048621108
13      725835.5        0.0008902909
14      811575.2        0.0129624864
15      292223.0        0.0026141820
16      153862.2        0.0075244299
17      1272367.2       0.0068988788
18      734199.0        0.0098799510
19      421404.5        0.0050479335
20      189047.5        0.0048211174
21      529102.0        0.0096373243
22      56833.0 0.0061710425
23      125856.2        0.0083900410
24      598893.8        0.0066222964
25      258240.0        0.0061297368
26      159086.2        0.0088192099
27      122863.0        0.0100925693
28      404699.5        0.0081477489
29      453514.5        0.0084070531
30      545028.0        0.0060956804
31      1233365.5       0.0061105819
32      1192758.2       0.0081616218
33      147563.2        0.0083796600
34      247293.0        0.0102826553
35      1074838.2       0.0074134232
36      459227.5        0.0086199724
37      202332.0        0.0090614422
38      377401.2        0.0069230414
39      1876752.5       0.0102260772

        x2      y1
1       50118.72        0.012116846
2       51286.14        0.012053508
3       52480.75        0.011990503
4       53703.18        0.011927830
5       54954.09        0.011865489
6       56234.13        0.011803480
7       57543.99        0.011741804
8       58884.37        0.011680460
9       60255.96        0.011619448
10      61659.50        0.011558769
11      63095.73        0.011498421
12      64565.42        0.011438406
13      66069.34        0.011378724
14      67608.30        0.011319373
15      69183.10        0.011260355
16      70794.58        0.011201669
17      72443.60        0.011143315
18      74131.02        0.011085294
19      75857.76        0.011027605
20      77624.71        0.010970248
21      79432.82        0.010913224
22      81283.05        0.010856531
23      83176.38        0.010800171
24      85113.80        0.010744143
25      87096.36        0.010688448
26      89125.09        0.010633085
27      91201.08        0.010578054
28      93325.43        0.010523355
29      95499.26        0.010468989
30      97723.72        0.010414954
31      100000.00       0.010361253
32      102329.30       0.010307883
33      104712.85       0.010254846
34      107151.93       0.010202140
35      109647.82       0.010149768
36      112201.85       0.010097727
37      114815.36       0.010046019
38      117489.76       0.009994643
39      120226.44       0.009943599
40      123026.88       0.009892888
41      125892.54       0.009842508
42      128824.96       0.009792461
43      131825.67       0.009742747
44      134896.29       0.009693364
45      138038.43       0.009644314
46      141253.75       0.009595596
47      144543.98       0.009547211
48      147910.84       0.009499157
49      151356.12       0.009451436
50      154881.66       0.009404047
51      158489.32       0.009356991
52      162181.01       0.009310267
53      165958.69       0.009263875
54      169824.37       0.009217815
55      173780.08       0.009172087
56      177827.94       0.009126692
57      181970.09       0.009081629
58      186208.71       0.009036899
59      190546.07       0.008992500
60      194984.46       0.008948434
61      199526.23       0.008904700
62      204173.79       0.008861299
63      208929.61       0.008818229
64      213796.21       0.008775492
65      218776.16       0.008733088
66      223872.11       0.008691015
67      229086.77       0.008649275
68      234422.88       0.008607867
69      239883.29       0.008566791
70      245470.89       0.008526048
71      251188.64       0.008485636
72      257039.58       0.008445558
73      263026.80       0.008405811
74      269153.48       0.008366396
75      275422.87       0.008327314
76      281838.29       0.008288565
77      288403.15       0.008250147
78      295120.92       0.008212062
79      301995.17       0.008174309
80      309029.54       0.008136888
81      316227.77       0.008099799
82      323593.66       0.008063043
83      331131.12       0.008026619
84      338844.16       0.007990528
85      346736.85       0.007954768
86      354813.39       0.007919341
87      363078.05       0.007884246
88      371535.23       0.007849483
89      380189.40       0.007815053
90      389045.14       0.007780955
91      398107.17       0.007747189
92      407380.28       0.007713756
93      416869.38       0.007680654
94      426579.52       0.007647885
95      436515.83       0.007615449
96      446683.59       0.007583344
97      457088.19       0.007551572
98      467735.14       0.007520132
99      478630.09       0.007489024
100     489778.82       0.007458249
101     501187.23       0.007427806
102     512861.38       0.007397695
103     524807.46       0.007367916
104     537031.80       0.007338470
105     549540.87       0.007309356
106     562341.33       0.007280574
107     575439.94       0.007252125
108     588843.66       0.007224007
109     602559.59       0.007196222
110     616595.00       0.007168770
111     630957.34       0.007141649
112     645654.23       0.007114861
113     660693.45       0.007088405
114     676082.98       0.007062281
115     691830.97       0.007036490
116     707945.78       0.007011031
117     724435.96       0.006985904
118     741310.24       0.006961109
119     758577.58       0.006936647
120     776247.12       0.006912517
121     794328.23       0.006888719
122     812830.52       0.006865254
123     831763.77       0.006842120
124     851138.04       0.006819320
125     870963.59       0.006796851
126     891250.94       0.006774714
127     912010.84       0.006752910
128     933254.30       0.006731438
129     954992.59       0.006710299
130     977237.22       0.006689491
131     1000000.00      0.006669016
132     1023292.99      0.006648873
133     1047128.55      0.006629063
134     1071519.31      0.006609585
135     1096478.20      0.006590438
136     1122018.45      0.006571625
137     1148153.62      0.006553143
138     1174897.55      0.006534994
139     1202264.43      0.006517177
140     1230268.77      0.006499692
141     1258925.41      0.006482540
142     1288249.55      0.006465720
143     1318256.74      0.006449232
144     1348962.88      0.006433076
145     1380384.26      0.006417253
146     1412537.54      0.006401762
147     1445439.77      0.006386603
148     1479108.39      0.006371777
149     1513561.25      0.006357282
150     1548816.62      0.006343120
151     1584893.19      0.006329291
152     1621810.10      0.006315793
153     1659586.91      0.006302628
154     1698243.65      0.006289795
155     1737800.83      0.006277294
156     1778279.41      0.006265126
157     1819700.86      0.006253290
158     1862087.14      0.006241786
159     1905460.72      0.006230614
160     1949844.60      0.006219775
161     1995262.31      0.006209268
162     2041737.94      0.006199093
163     2089296.13      0.006189251
164     2137962.09      0.006179740
165     2187761.62      0.006170562
166     2238721.14      0.006161717
167     2290867.65      0.006153203
168     2344228.82      0.006145022
169     2398832.92      0.006137173
170     2454708.92      0.006129656
171     2511886.43      0.006122472
172     2570395.78      0.006115620
173     2630267.99      0.006109100
174     2691534.80      0.006102913
175     2754228.70      0.006097057
176     2818382.93      0.006091534
177     2884031.50      0.006086343
178     2951209.23      0.006081485
179     3019951.72      0.006076959
180     3090295.43      0.006072765
181     3162277.66      0.006068903
182     3235936.57      0.006065374
183     3311311.21      0.006062176
184     3388441.56      0.006059311
185     3467368.50      0.006056779
186     3548133.89      0.006054579
187     3630780.55      0.006052710
188     3715352.29      0.006051175
189     3801893.96      0.006049971
190     3890451.45      0.006049100
191     3981071.71      0.006048561
192     4073802.78      0.006048354
193     4168693.83      0.006048480
194     4265795.19      0.006048937
195     4365158.32      0.006049727
196     4466835.92      0.006050850
197     4570881.90      0.006052304
198     4677351.41      0.006054091
199     4786300.92      0.006056210
200     4897788.19      0.006058662
201     5011872.34      0.006061445

To use dput function to present the data
> dput(cbind(avg_cost_2012, asset_2012))
structure(c(0.00321993102627396, 0.00348666071050862, 0.00514500670171978,
0.00635893976088426, 0.00625304477271035, 0.00544003417356045,
0.00421346233925224, 0.00488341453548038, 0.00621557372817221,
0.00425520359585793, 0.00692384201718875, 0.00486211080732891,
0.00089029087751351, 0.0129624864137572, 0.00261418199497039,
0.00752442992607212, 0.00689887882046544, 0.00987995102314728,
0.00504793348921874, 0.00482111735730959, 0.00963732431899178,
0.00617104252791857, 0.0083900410469978, 0.00662229644462707,
0.00612973679503377, 0.00881920986708858, 0.0100925692602712,
0.0081477488720749, 0.00840705306981286, 0.00609568037628165,
0.0061105818615996, 0.00816162181738723, 0.00837965998751208,
0.0102826552802113, 0.0074134231730932, 0.00861997236733968,
0.00906144215028246, 0.00692304142052871, 0.0102260771876649,
3973730, 2391575.75, 2840943.5, 2040943, 1982715.25, 1618162.25,
820082.25, 1658596.75, 1762794, 93439.5, 218481.25, 2332477,
725835.5, 811575.25, 292223, 153862.25, 1272367.25, 734199, 421404.5,
189047.5, 529102, 56833, 125856.25, 598893.75, 258240, 159086.25,
122863, 404699.5, 453514.5, 545028, 1233365.5, 1192758.25, 147563.25,
247293, 1074838.25, 459227.5, 202332, 377401.25, 1876752.5), .Dim = c(39L,
2L), .Dimnames = list(NULL, c("avg_cost_2012", "asset_2012")))

> dput(cbind(avg_cost_2012, asset_2012))
structure(c(0.00321993102627396, 0.00348666071050862, 0.00514500670171978,
0.00635893976088426, 0.00625304477271035, 0.00544003417356045,
0.00421346233925224, 0.00488341453548038, 0.00621557372817221,
0.00425520359585793, 0.00692384201718875, 0.00486211080732891,
0.00089029087751351, 0.0129624864137572, 0.00261418199497039,
0.00752442992607212, 0.00689887882046544, 0.00987995102314728,
0.00504793348921874, 0.00482111735730959, 0.00963732431899178,
0.00617104252791857, 0.0083900410469978, 0.00662229644462707,
0.00612973679503377, 0.00881920986708858, 0.0100925692602712,
0.0081477488720749, 0.00840705306981286, 0.00609568037628165,
0.0061105818615996, 0.00816162181738723, 0.00837965998751208,
0.0102826552802113, 0.0074134231730932, 0.00861997236733968,
0.00906144215028246, 0.00692304142052871, 0.0102260771876649,
3973730, 2391575.75, 2840943.5, 2040943, 1982715.25, 1618162.25,
820082.25, 1658596.75, 1762794, 93439.5, 218481.25, 2332477,
725835.5, 811575.25, 292223, 153862.25, 1272367.25, 734199, 421404.5,
189047.5, 529102, 56833, 125856.25, 598893.75, 258240, 159086.25,
122863, 404699.5, 453514.5, 545028, 1233365.5, 1192758.25, 147563.25,
247293, 1074838.25, 459227.5, 202332, 377401.25, 1876752.5), .Dim = c(39L,
2L), .Dimnames = list(NULL, c("avg_cost_2012", "asset_2012")))
> dput(cbind(y1,x2))
structure(c(0.0121168460097573, 0.0120535083414464, 0.0119905029411228, 0.0119278298087863, 0.011865488944437, 0.0118034803480749, 0.0117418040197, 0.0116804599593122, 0.0116194481669117, 0.0115587686424983, 0.0114984213860722, 0.0114384063976332, 0.0113787236771814, 0.0113193732247168, 0.0112603550402394, 0.0112016691237491, 0.0111433154752461, 0.0110852940947302, 0.0110276049822015, 0.0109702481376601, 0.0109132235611057, 0.0108565312525386, 0.0108001712119587, 0.010744143439366, 0.0106884479347604, 0.010633084698142, 0.0105780537295108, 0.0105233550288669, 0.01046898859621, 0.0104149544315404, 0.010361252534858, 0.0103078829061627, 0.0102548455454547, 0.0102021404527338, 0.0101497676280001,
0.0100977270712536, 0.0100460187824943, 0.00999464276172216,
0.00994359900893722, 0.00989288752413946, 0.0098425083073289,
0.00979246135850551, 0.00974274667766932, 0.0096933642648203,
0.00964431411995847, 0.00959559624308384, 0.0095472106341964,
0.00949915729329613, 0.00945143622038305, 0.00940404741545717,
0.00935699087851848, 0.00931026660956695, 0.00926387460860262,
0.00921781487562548, 0.00917208741063551, 0.00912669221363276,
0.00908162928461716, 0.00903689862358877, 0.00899250023054757,
0.00894843410549355, 0.0089047002484267, 0.00886129865934705,
0.00881822933825459, 0.00877549228514933, 0.00873308750003123,
0.00869101498290033, 0.00864927473375661, 0.00860786675260009,
0.00856679103943074, 0.00852604759424859, 0.00848563641705362,
0.00844555750784583, 0.00840581086662524, 0.00836639649339183,
0.00832731438814562, 0.00828856455088657, 0.00825014698161472,
0.00821206168033005, 0.00817430864703257, 0.0081368878817223,
0.00809979938439918, 0.00806304315506327, 0.00802661919371454,
0.00799052750035301, 0.00795476807497865, 0.00791934091759149,
0.0078842460281915, 0.0078494834067787, 0.0078150530533531, 0.00778095496791469,
0.00774718915046345, 0.00771375560099939, 0.00768065431952253,
0.00764788530603284, 0.00761544856053037, 0.00758334408301507,
0.00755157187348694, 0.00752013193194602, 0.00748902425839228,
0.00745824885282571, 0.00742780571524633, 0.00739769484565418,
0.00736791624404916, 0.00733846991043136, 0.00730935584480073,
0.0072805740471573, 0.00725212451750105, 0.00722400725583199,
0.00719622226215011, 0.00716876953645541, 0.00714164907874794,
0.00711486088902762, 0.0070884049672945, 0.00706228131354857,
0.00703648992778981, 0.00701103081001822, 0.00698590396023384,
0.00696110937843665, 0.00693664706462666, 0.00691251701880381,
0.00688871924096819, 0.00686525373111974, 0.00684212048925849,
0.00681931951538441, 0.0067968508094975, 0.00677471437159781,
0.00675291020168529, 0.00673143829975996, 0.00671029866582183,
0.00668949129987087, 0.0066690162019071, 0.00664887337193053,
0.00662906280994112, 0.00660958451593892, 0.0065904384899239,
0.00657162473189606, 0.00655314324185539, 0.00653499401980194,
0.00651717706573567, 0.00649969237965659, 0.00648253996156468,
0.00646571981145995, 0.00644923192934242, 0.00643307631521209,
0.00641725296906895, 0.00640176189091297, 0.00638660308074418,
0.00637177653856259, 0.00635728226436819, 0.00634312025816097,
0.00632929051994092, 0.00631579304970808, 0.00630262784746244,
0.00628979491320396, 0.00627729424693267, 0.00626512584864858,
0.00625328971835167, 0.00624178585604192, 0.00623061426171939,
0.00621977493538403, 0.00620926787703585, 0.00619909308667488,
0.00618925056430109, 0.00617974030991447, 0.00617056232351507,
0.00616171660510281, 0.00615320315467778, 0.00614502197223991,
0.00613717305778924, 0.00612965641132575, 0.00612247203284944,
0.00611561992236033, 0.0061091000798584, 0.00610291250534367,
0.00609705719881611, 0.00609153416027573, 0.00608634338972257,
0.00608148488715655, 0.00607695865257775, 0.00607276468598614,
0.00606890298738169, 0.00606537355676445, 0.00606217639413439,
0.00605931149949152, 0.00605677887283583, 0.00605457851416734,
0.00605271042348603, 0.00605117460079189, 0.00604997104608494,
0.00604909975936518, 0.00604856074063263, 0.00604835398988726,
0.00604847950712906, 0.00604893729235803, 0.00604972734557423,
0.0060508496667776, 0.00605230425596814, 0.00605409111314588,
0.00605621023831082, 0.00605866163146293, 0.00606144529260223,
50118.7233627273, 51286.1383991365, 52480.7460249772, 53703.1796370253,
54954.0873857625, 56234.1325190349, 57543.9937337157, 58884.365535559,
60255.9586074358, 61659.5001861482, 63095.7344480193, 64565.4229034656, 66069.3448007596, 67608.2975391982, 69183.0970918936, 70794.5784384139, 72443.5960074991, 74131.0241300918, 75857.7575029184, 77624.7116628693,
79432.8234724282, 81283.05161641, 83176.3771102671, 85113.8038202378,
87096.3589956081, 89125.0938133746, 91201.083935591, 93325.4300796992,
95499.2586021437, 97723.7220955811, 1e+05, 102329.299228075,
104712.85480509, 107151.930523761, 109647.819614319, 112201.845430196,
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380189.396320561, 389045.14499428, 398107.170553498, 407380.277804113,
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549540.873857625, 562341.325190349, 575439.937337157, 588843.65535559,
602559.586074358, 616595.001861482, 630957.344480194, 645654.229034656, 660693.448007596, 676082.975391982, 691830.970918936, 707945.784384139, 724435.960074991, 741310.241300918, 758577.575029184, 776247.116628693,
794328.234724282, 812830.5161641, 831763.771102671, 851138.038202376,
870963.589956081, 891250.938133746, 912010.83935591, 933254.300796992,
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3801893.96320561, 3890451.4499428, 3981071.70553498, 4073802.77804113,
4168693.83470336, 4265795.18801593, 4365158.32240167, 4466835.92150963, 4570881.89614875, 4677351.41287198, 4786300.92322638, 4897788.19368447,
5011872.33627272), .Dim = c(201L, 2L), .Dimnames = list(NULL,
    c("y1", "x2")))




2013/4/11 David Winsemius <dwinsem...@comcast.net>

On Apr 10, 2013, at 12:44 AM, jpm miao wrote:

Hi David,

   Many thanks. I try to follow your example and code as follows:

xyplot( avg_cost_2012 ~ asset_2012,
          panel=function(x,y) {
          panel.xyplot(x,y, type="p")
panel.lines(x2, y1, col="red")},scales=list(x=list(log=10)))

However, I do see the points "p" of "avg_cost_2012 ~ asset_2012", but do not see the line for y1 against x2. y1 and x1 are numeric vectors of the same size. How can I fix it?

Without seeing the data it is difficult to enumerate the possible errors you could be making.

I say again:

Your example was not presented in a form that lent itself to easy editing. Please learn to use dput to present data structures.

-- David




Thnaks

Miao


2013/4/10 David Winsemius <dwinsem...@comcast.net>

On Apr 9, 2013, at 8:21 PM, jpm miao wrote:

Thank you very much.

Could it be done in Lattice package?



Your example was not presented in a form that lent itself to easy editing. Please learn to use dput to present data structures:

xyplot( 4:6 ~ 1:3,
       panel=function(x,y) {
                panel.xyplot(x,y, type="l")
panel.points(x=c(1.1, 2.1), y=c(4.1, 5.1), col="red") } )

--
David.


Thanks,

Miao


2013/4/10 Janesh Devkota <janesh.devk...@gmail.com>

Hi,

This should be fairly easy by using base R graphics.

Lets suppose your first data is represented by (x1,y1) and second data is
represented by (x2,y2)

You can use the following command.
plot(x1,y1,type="l")
points(x2,y2)

Hope it helps.


On Tue, Apr 9, 2013 at 8:24 PM, jpm miao <miao...@gmail.com> wrote:

Hi,

How can I plot two curves with distinct x and y vectors? I would like
to
join one of them by regular lines and plot the other just by points (no lines). Can it be done in regular R graphic tools, say "plot" function?
Can it be done in Lattice package, say "xyplot" function?

  Thanks,

Miao

My data look like this: two curves with different vector size

x                 y
3973730 0.00322  2391576 0.003487  2840944 0.005145  2040943 0.006359
1982715 0.006253  1618162 0.00544  820082.3 0.004213  1658597 0.004883
1762794 0.006216 93439.5 0.004255 218481.3 0.006924 2332477 0.004862 725835.5 0.00089 811575.3 0.012962 292223 0.002614 153862.3 0.007524
1272367 0.006899  734199 0.00988  421404.5 0.005048  189047.5 0.004821
529102 0.009637  56833 0.006171  125856.3 0.00839  598893.8 0.006622
258240
0.00613 159086.3 0.008819 122863 0.010093 404699.5 0.008148 453514.5 0.008407 545028 0.006096 1233366 0.006111 1192758 0.008162 147563.3
0.00838  247293 0.010283  1074838 0.007413  459227.5 0.00862  202332
0.009061  377401.3 0.006923  1876753 0.010226
and
x   y
50118.72 0.012117  51286.14 0.012054  52480.75 0.011991  53703.18
0.011928
54954.09 0.011865 56234.13 0.011803 57543.99 0.011742 58884.37 0.01168 60255.96 0.011619 61659.5 0.011559 63095.73 0.011498 64565.42 0.011438
66069.34 0.011379  67608.3 0.011319  69183.1 0.01126

       [[alternative HTML version deleted]]

______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.




        [[alternative HTML version deleted]]

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

David Winsemius, MD
Alameda, CA, USA



David Winsemius, MD
Alameda, CA, USA



David Winsemius, MD
Alameda, CA, USA

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

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