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library(RODBC)#载入函数
channel=odbcConnectExcel("F:/实习/GIS练习/教材配套数据/lx/图表矢量化2/图表制作/泌乳曲线等原始市局.xlsx")#读取xlsx表格
mydata1=sqlFetch(channel,'泌乳point1')#泌乳曲线
mydata2=sqlFetch(channel,'DMI_point')#DMI曲线
mydata3=sqlFetch(channel,'weight_point')#weight曲线
print(mydata1)#泌乳曲线数据
print(mydata2)#DMI曲线数据
print(mydata3)#weight曲线数据
mydata3_y3<-mydata3[,4]#提取相应表格中的某一列，作为y值的数据
mydata3_x3<-mydata3[,2]#提取相应表格中的某一列，作为x值的数据
mydata2_x2<-mydata2[,2]
mydata2_y2<-mydata2[,4]
mydata1_x1<-mydata1[,2]
mydata1_y1<-mydata1[,4]
plot(mydata1_y1~mydata1_x1,type="l")
lines(mydata2_y2~mydata2_x2,col="blue")
lines(mydata3_y3~mydata3_x3,col="red")
运行结果
。
> library(RODBC)#载入函数
> channel=odbcConnectExcel("F:/实习/GIS练习/教材配套数据/lx/图表矢量化2/图表制作/泌乳曲线等原始市局.xlsx")#读取xlsx表格
>
> mydata1=sqlFetch(channel,'泌乳point1')#泌乳曲线
> mydata2=sqlFetch(channel,'DMI_point')#DMI曲线
> mydata3=sqlFetch(channel,'weight_point')#weight曲线
> print(mydata1)#泌乳曲线数据
Id POINT_X POINT_Y F4
1 1 31.12684 -342.7020 182.2980
2 2 34.07998 -334.5914 190.4086
3 3 36.44392 -326.2830 198.7170
4 4 38.31711 -317.8482 207.1518
5 5 39.90134 -309.3558 215.6442
6 6 41.28331 -300.8276 224.1724
7 7 42.52590 -292.2771 232.7229
8 8 43.55720 -283.6987 241.3013
9 9 44.57072 -275.1180 249.8820
10 10 45.58424 -266.5373 258.4627
11 11 46.59776 -257.9566 267.0434
12 12 47.61129 -249.3758 275.6242
13 13 48.74398 -240.8103 284.1897
14 14 49.98030 -232.2603 292.7397
15 15 51.59161 -223.7715 301.2285
16 16 53.60893 -215.3727 309.6273
17 17 55.93652 -207.0556 317.9444
18 18 58.56992 -198.8267 326.1733
19 19 61.69045 -190.7695 334.2305
20 20 65.15676 -182.8595 342.1405
21 21 68.95045 -175.0998 349.9002
22 22 73.29200 -167.6330 357.3670
23 23 78.24163 -160.5565 364.4435
24 24 84.08376 -154.2120 370.7880
25 25 91.04979 -149.1343 375.8657
26 26 98.97567 -145.7299 379.2701
27 27 107.35895 -143.7036 381.2964
28 28 115.95118 -142.8686 382.1314
29 29 124.58778 -142.8800 382.1200
30 30 133.14959 -144.0004 380.9996
31 31 141.63443 -145.6257 379.3743
32 32 150.06791 -147.5017 377.4983
33 33 158.45583 -149.5724 375.4276
34 34 166.79208 -151.8420 373.1580
35 35 175.06304 -154.3383 370.6617
36 36 183.23943 -157.1274 367.8726
37 37 191.21774 -160.4354 364.5646
38 38 199.09346 -163.9876 361.0124
39 39 206.93264 -167.6212 357.3788
40 40 214.74545 -171.3106 353.6894
41 41 222.53032 -175.0592 349.9408
42 42 230.31519 -178.8078 346.1922
43 43 238.10006 -182.5563 342.4437
44 44 245.88493 -186.3049 338.6951
45 45 253.66980 -190.0535 334.9465
46 46 261.40419 -193.9050 331.0950
47 47 269.13748 -197.7589 327.2411
48 48 276.87076 -201.6128 323.3872
49 49 284.60404 -205.4666 319.5334
50 50 292.33733 -209.3205 315.6795
51 51 300.04559 -213.2237 311.7763
52 52 307.72492 -217.1840 307.8160
53 53 315.40426 -221.1443 303.8557
54 54 323.08359 -225.1045 299.8955
55 55 330.76292 -229.0648 295.9352
56 56 338.41659 -233.0738 291.9262
57 57 346.02421 -237.1701 287.8299
58 58 353.63184 -241.2665 283.7335
59 59 361.23946 -245.3628 279.6372
60 60 368.79776 -249.5488 275.4512
61 61 376.33003 -253.7821 271.2179
62 62 383.86230 -258.0154 266.9846
63 63 391.39456 -262.2487 262.7513
64 64 398.86780 -266.5849 258.4151
65 65 406.32474 -270.9496 254.0504
66 66 413.78167 -275.3142 249.6858
67 67 421.23861 -279.6788 245.3212
68 68 428.64660 -284.1257 240.8743
69 69 436.03832 -288.5999 236.4001
70 70 443.37011 -293.1714 231.8286
71 71 450.68080 -297.7767 227.2233
72 72 457.98400 -302.3940 222.6060
73 73 465.42869 -306.7789 218.2211
74 74 472.88297 -311.1481 213.8519
75 75 480.38446 -315.4350 209.5650
76 76 487.91615 -319.6694 205.3306
77 77 495.44785 -323.9037 201.0963
78 78 503.00814 -328.0865 196.9135
79 79 510.58756 -332.2348 192.7652
80 80 518.16698 -336.3831 188.6169
81 81 525.74639 -340.5313 184.4687
82 82 533.69000 -343.9216 181.0784
83 83 541.66523 -347.2460 177.7540
84 84 549.64045 -350.5704 174.4296
85 85 557.61568 -353.8948 171.1052
86 86 565.59091 -357.2192 167.7808
87 87 573.35120 -360.9991 164.0009
88 88 581.13647 -364.7337 160.2663
89 89 589.13224 -368.0068 156.9932
90 90 597.14584 -371.2376 153.7624
91 91 605.15943 -374.4685 150.5315
92 92 613.21514 -377.5896 147.4104
93 93 621.33887 -380.5314 144.4686
94 94 629.56160 -383.1852 141.8148
95 95 637.78433 -385.8389 139.1611
96 96 645.98160 -388.5689 136.4311
97 97 654.14786 -391.3917 133.6083
98 98 662.35817 -394.0804 130.9196
99 99 670.61246 -396.6328 128.3672
100 100 678.98841 -398.7505 126.2495
> print(mydata2)#DMI曲线数据
Id POINT_X POINT_Y F4
1 1 31.28888 -299.4756 225.5244
2 2 39.95343 -295.9645 229.0355
3 3 48.54570 -292.2838 232.7162
4 4 57.07901 -288.4648 236.5352
5 5 65.53809 -284.4866 240.5134
6 6 73.94816 -280.4034 244.5966
7 7 82.01873 -275.6914 249.3086
8 8 89.90284 -270.6688 254.3312
9 9 97.69892 -265.5090 259.4910
10 10 105.37509 -260.1767 264.8233
11 11 112.87883 -254.6040 270.3960
12 12 119.58630 -248.1143 276.8857
13 13 126.65271 -242.0089 282.9911
14 14 133.78500 -235.9668 289.0332
15 15 140.32555 -229.2923 295.7077
16 16 146.45350 -222.2324 302.7676
17 17 152.50688 -215.1088 309.8912
18 18 158.41520 -207.8635 317.1365
19 19 164.32352 -200.6183 324.3817
20 20 170.07372 -193.2471 331.7529
21 21 175.81075 -185.8655 339.1345
22 22 181.27892 -178.2828 346.7172
23 23 186.73601 -170.6919 354.3081
24 24 192.19309 -163.1009 361.8991
25 25 197.76372 -155.5933 369.4067
26 26 203.48446 -148.2004 376.7996
27 27 209.22498 -140.8250 384.1750
28 28 215.00090 -133.4807 391.5193
29 29 221.51796 -126.7833 398.2167
30 30 228.30185 -120.3507 404.6493
31 31 235.09385 -113.9264 411.0736
32 32 242.95589 -108.9877 416.0123
33 33 251.86421 -106.5881 418.4119
34 34 261.15600 -105.5565 419.4435
35 35 270.46994 -104.7579 420.2421
36 36 279.81016 -104.5004 420.4996
37 37 289.09813 -105.2862 419.7138
38 38 298.32370 -106.7714 418.2286
39 39 307.15508 -109.8060 415.1940
40 40 315.84406 -113.2562 411.7438
41 41 324.53304 -116.7064 408.2936
42 42 333.08701 -120.4783 404.5217
43 43 341.49479 -124.5634 400.4366
44 44 349.82288 -128.8085 396.1915
45 45 358.04954 -133.2497 391.7503
46 46 366.17223 -137.8766 387.1234
47 47 374.25133 -142.5806 382.4194
48 48 382.19927 -147.5032 377.4968
49 49 390.11269 -152.4801 372.5199
50 50 397.94161 -157.5900 367.4100
51 51 405.69750 -162.8096 362.1904
52 52 413.42213 -168.0754 356.9246
53 53 421.08208 -173.4352 351.5648
54 54 428.71408 -178.8344 346.1656
55 55 436.30499 -184.2916 340.7084
56 56 443.86197 -189.7953 335.2047
57 57 451.38770 -195.3420 329.6580
58 58 458.88651 -200.9247 324.0753
59 59 466.34723 -206.5586 318.4414
60 60 473.78590 -212.2212 312.7788
61 61 481.17283 -217.9514 307.0486
62 62 488.51831 -223.7337 301.2663
63 63 495.70897 -229.7053 295.2947
64 64 502.77807 -235.8210 289.1790
65 65 509.85083 -241.9330 283.0670
66 66 516.77951 -248.2096 276.7904
67 67 523.68497 -254.5117 270.4883
68 68 530.56817 -260.8381 264.1619
69 69 537.45138 -267.1645 257.8355
70 70 544.33458 -273.4910 251.5090
71 71 551.26945 -279.7606 245.2394
72 72 558.26014 -285.9660 239.0340
73 73 565.61399 -291.7362 233.2638
74 74 573.13052 -297.2946 227.7054
75 75 580.72081 -302.7523 222.2477
76 76 588.40147 -308.0822 216.9178
77 77 596.18327 -313.2635 211.7365
78 78 603.96507 -318.4448 206.5552
79 79 611.94139 -323.3064 201.6936
80 80 620.73892 -326.4465 198.5535
81 81 629.77714 -328.8236 196.1764
82 82 638.90656 -330.8328 194.1672
83 83 648.07686 -332.6449 192.3551
84 84 657.29581 -334.1984 190.8016
85 85 666.58104 -335.2866 189.7134
86 86 675.91712 -335.7148 189.2852
87 87 685.26056 -335.5474 189.4526
88 88 694.58727 -334.9589 190.0411
89 89 703.89522 -334.0898 190.9102
90 90 713.17504 -332.9553 192.0447
91 91 722.40531 -331.4884 193.5116
92 92 731.45940 -329.1817 195.8183
93 93 740.40728 -326.4729 198.5271
94 94 749.35386 -323.7598 201.2402
95 95 758.29396 -321.0254 203.9746
96 96 767.22574 -318.2645 206.7355
97 97 776.12662 -315.4050 209.5950
98 98 785.02517 -312.5385 212.4615
99 99 793.88446 -309.5527 215.4473
100 100 802.73399 -306.5392 218.4608
> print(mydata3)#weight曲线数据
Id POINT_X POINT_Y F4
1 1 27.81421 -204.2399 320.7601
2 2 32.64929 -211.8404 313.1596
3 3 37.48438 -219.4410 305.5590
4 4 42.31946 -227.0416 297.9584
5 5 47.15454 -234.6422 290.3578
6 6 51.96841 -242.2562 282.7438
7 7 56.74109 -249.8961 275.1039
8 8 61.51361 -257.5361 267.4639
9 9 66.15102 -265.2589 259.7411
10 10 70.75058 -272.9937 252.0063
11 11 76.13925 -280.2101 244.7899
12 12 81.89151 -287.1409 237.8591
13 13 87.70981 -294.0179 230.9821
14 14 93.75312 -300.6979 224.3021
15 15 99.80419 -307.3711 217.6289
16 16 106.03699 -313.8728 211.1272
17 17 112.46908 -320.1749 204.8251
18 18 119.13965 -326.2285 198.7715
19 19 126.14915 -331.8866 193.1134
20 20 133.38725 -337.2436 187.7564
21 21 140.83196 -342.3093 182.6907
22 22 148.47640 -347.0724 177.9276
23 23 156.32784 -351.4885 173.5115
24 24 164.31645 -355.6483 169.3517
25 25 172.38275 -359.6569 165.3431
26 26 180.51680 -363.5278 161.4722
27 27 188.67112 -367.3546 157.6454
28 28 196.99685 -370.7848 154.2152
29 29 205.55553 -373.5830 151.4170
30 30 214.33916 -375.5655 149.4345
31 31 223.25717 -376.7996 148.2004
32 32 232.25328 -377.2653 147.7347
33 33 241.23328 -377.9272 147.0728
34 34 250.20292 -378.7287 146.2713
35 35 259.19715 -379.2098 145.7902
36 36 268.20202 -379.4530 145.5470
37 37 277.20999 -379.3948 145.6052
38 38 286.21810 -379.3900 145.6100
39 39 295.21226 -379.8841 145.1159
40 40 304.21228 -379.7094 145.2906
41 41 313.19675 -379.0566 145.9434
42 42 322.15849 -378.1473 146.8527
43 43 331.11776 -377.2101 147.7899
44 44 340.06011 -376.1244 148.8756
45 45 349.00038 -375.0206 149.9794
46 46 357.93987 -373.9111 151.0889
47 47 366.84513 -372.5535 152.4465
48 48 375.75039 -371.1959 153.8041
49 49 384.60990 -369.5743 155.4257
50 50 393.45246 -367.8550 157.1450
51 51 402.22938 -365.8333 159.1667
52 52 410.98876 -363.7309 161.2691
53 53 419.72829 -361.5483 163.4517
54 54 428.45720 -359.3228 165.6772
55 55 437.18320 -357.0864 167.9136
56 56 445.85200 -354.6372 170.3628
57 57 454.49117 -352.0891 172.9109
58 58 463.07726 -349.3641 175.6359
59 59 471.66335 -346.6390 178.3610
60 60 480.24945 -343.9140 181.0860
61 61 488.72534 -340.8671 184.1329
62 62 497.01913 -337.3608 187.6392
63 63 505.16845 -333.5285 191.4715
64 64 513.21499 -329.4788 195.5212
65 65 521.10139 -325.1254 199.8746
66 66 528.94038 -320.6891 204.3109
67 67 536.69658 -316.1078 208.8922
68 68 544.37758 -311.4024 213.5976
69 69 552.02817 -306.6469 218.3531
70 70 559.60323 -301.7722 223.2278
71 71 567.16864 -296.8822 228.1178
72 72 574.67973 -291.9093 233.0907
73 73 582.19031 -286.9355 238.0645
74 74 589.70089 -281.9618 243.0382
75 75 597.31759 -277.1529 247.8471
76 76 605.00181 -272.4519 252.5481
77 77 612.68602 -267.7508 257.2492
78 78 620.37024 -263.0498 261.9502
79 79 628.21720 -258.6279 266.3721
80 80 636.19772 -254.4496 270.5504
81 81 644.10989 -250.1448 274.8552
82 82 651.97405 -245.7514 279.2486
83 83 660.08446 -241.8469 283.1531
84 84 668.60464 -238.9829 286.0171
85 85 677.41824 -237.1218 287.8782
86 86 686.26464 -235.4269 289.5731
87 87 695.15671 -233.9933 291.0067
88 88 704.09032 -232.8484 292.1516
89 89 713.05911 -232.0251 292.9749
90 90 722.05307 -231.5547 293.4453
91 91 731.05868 -231.4795 293.5205
92 92 740.05665 -231.8472 293.1528
93 93 749.01720 -232.7352 292.2648
94 94 757.89597 -234.2381 290.7619
95 95 766.66691 -236.2853 288.7147
96 96 775.32068 -238.7856 286.2144
97 97 783.86054 -241.6516 283.3484
98 98 792.30026 -244.8009 280.1991
99 99 800.62567 -248.2407 276.7593
100 100 808.94861 -251.6868 273.3132
>
> mydata3_y3<-mydata3[,4]#提取相应表格中的某一列，作为y值的数据
> mydata3_x3<-mydata3[,2]#提取相应表格中的某一列，作为x值的数据
> mydata2_x2<-mydata2[,2]
> mydata2_y2<-mydata2[,4]
> mydata1_x1<-mydata1[,2]
> mydata1_y1<-mydata1[,4]
>
> plot(mydata1_y1~mydata1_x1,type="l")
> lines(mydata2_y2~mydata2_x2,col="blue")
> lines(mydata3_y3~mydata3_x3,col="red")
>
和大家分享一下，还有很多需要完善的方面，多多赐教！！
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