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Ask for help ;how to draw this kind of picture? Thanks!

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I have a dataset as follows(a part of my data,the real data is larger)

Date Index(Closing)  Rt(LN)
19-Dec-90 99.98 0.043164
20-Dec-90 104.39 0.044406
21-Dec-90 109.13 0.048472
24-Dec-90 114.55 0.048562
25-Dec-90 120.25 0.040898
26-Dec-90 125.27 0.000080
27-Dec-90 125.28 0.009296
28-Dec-90 126.45 0.009132
31-Dec-90 127.61 0.009593
2-Jan-91 128.84 0.009963
3-Jan-91 130.13 0.010017
4-Jan-91 131.44 0.004706
7-Jan-91 132.06 0.004684
8-Jan-91 132.68 0.004962
9-Jan-91 133.34 0.004714
10-Jan-91 133.97 0.004692
11-Jan-91 134.60  0.000446
14-Jan-91 134.66 0.000594
15-Jan-91 134.74 -0.003718
16-Jan-91 134.24 0.000074
17-Jan-91 134.25 -0.000074
18-Jan-91 134.24 0.000000
21-Jan-91 134.24 -0.003881
22-Jan-91 133.72 -0.004197
23-Jan-91 133.16 -0.004139
24-Jan-91 132.61 -0.004232
25-Jan-91 132.05 -0.004478
28-Jan-91 131.46 -0.003963
29-Jan-91 130.94 0.000000
30-Jan-91 130.94 -0.007436
31-Jan-91 129.97 -0.003546
1-Feb-91 129.51 -0.003558
4-Feb-91 129.05 -0.003649
5-Feb-91 128.58 0.004268
6-Feb-91 129.13 0.005098
7-Feb-91 129.79 0.004536
8-Feb-91 130.38 0.004515
11-Feb-91 130.97 0.002897
12-Feb-91 131.35 0.004254
13-Feb-91 131.91 0.004689
14-Feb-91 132.53 0.004517
19-Feb-91 133.13 0.003973
20-Feb-91 133.66 0.004628
21-Feb-91 134.28 0.004384
22-Feb-91 134.87 -0.003491
25-Feb-91 134.4 -0.003503
26-Feb-91 133.93 -0.003441
27-Feb-91 133.47 -0.003452
28-Feb-91 133.01 -0.003615 

and I want to draw a piture like this.I have write a gplot procesure,but the result was not perfect.Hope some one can do me a fovor!Tanks again!

Problem Definition

The user who posted this data wants to convert it into a graphical plot of some kind. However, it is not clear from the post what would be considered to be the perfect result. The data appears to be some form of financial data, possibly a stock market index with only the trading days reported. Non-trading days are omitted, perhaps. One question would be how should missing days be treated in the plot; should they simply be omitted or should they be included, with the data values imputed in some way? If the data values are imputed, should this be by interpolation between 2 days or by retention of the previous day(s) value? Another question is will any imputed data be used to model or predict future behaviour of the variables? What other purposes will the raw and/or processed data sets be used for? Without knowing the bigger picture, it is difficult to suggest an appropriate solution. The business problem the user is trying to address is not articulated. The risk is any solution could give misleading results if applied inappropriately. This could result in a poor business decision. Before this problem can be solved, it needs to be more clearly explained and defined, so that the appropriate strengths, weaknesses, risks and opportunities of any potential solution can be evaluated. Also, what sort of outcome is the user seeking? And is their expectation of perfection appropriate given the state of the data? These could be reasons why this problem has been ignored so far.