[R] performance analytics

[sheenmaria]

hi Michael,
am sorry for the incomplete reply .


csv file data havinmg like this , 

>getSymbols("IBM")
>weekly_data = to.weekly(week_name)		
>dataframe=data.frame(weekly_data)
>outputfile_name="F:\\R-programs\\Outputfile.csv"
>write.table(dataframe, file =outputfile_name,sep = ",",col.names
=TRUE,row.names = T)

> datafrom_table <- read.csv(file=outputfile_name,head=TRUE,sep=",")
> d12=dput(datafrom_table)

structure(list(week_name.Open = c(97.18, 99.08, 99.4, 96.91, 
98.57, 100, 98.6, 98.66, 96, 92.4, 93.86, 94, 94.71, 95.45, 96.4, 
96.3, 97.23, 102.06, 102.42, 105.4, 106.95, 105.57, 106.55, 103.11, 
104.93, 105.1, 105.5, 108.55, 109.66, 115.32, 114.72, 113.02, 
112.83, 108.9, 112.9, 116.34, 116.35, 115, 116.02, 119.31, 117.85, 
118.02, 113.78, 114.5, 113.49, 102.73, 102.59, 102.7, 105.41, 
109.34, 105.08, 110.9, 108.99, 100.05, 102.03, 98.55, 105.5, 
107.06, 105.16, 106.94, 109.52, 113.4, 115.8, 116.6, 119.1, 115.2, 
115.72, 117.1, 123.87, 122.04, 121.5, 125.12, 126.05, 124.01, 
127.47, 124.88, 127.1, 123.08, 117.5, 120.55, 121, 127.5, 126.54, 
128.2, 126.01, 123.63, 122.58, 122.87, 117.78, 113.73, 116.21, 
115.83, 101.5, 96.42, 92.22, 81.4, 94.76, 83.25, 79.13, 81.37, 
77.8, 83.82, 83.11, 82.35, 81.83, 87.11, 85.5, 84.76, 91.77, 
91.07, 95.58, 91.73, 84.63, 90.16, 85.11, 91.11, 97.69, 94.96, 
100.17, 99.08, 98.41, 99.36, 106, 102.98, 104.33, 101.32, 107.51, 
108.15, 108.47, 104.75, 105.69, 101.34, 103.42, 115.87, 116.63, 
119.17, 118.03, 116.81, 119.25, 117.67, 117.94, 118.78, 122.09, 
119.36, 120.39, 126.22, 123.36, 120.18, 119.53, 125.3, 127.43, 
127.9, 127.29, 126.97, 129.46, 129.3, 132.28, 131.68, 129.03, 
131.63, 125.92, 124.79, 122.65, 124.91, 126.48, 128.7, 126.27, 
128, 127.94, 128.9, 128.68, 128.26, 129.2, 129.9, 128.89, 125.21, 
131.26, 121.47, 124.69, 124.26, 128.93, 130.37, 127.35, 123.58, 
128.97, 122.97, 128.78, 130.03, 131.18, 128.83, 125.21, 123.31, 
126.99, 128.43, 131.45, 134.67, 136.18, 138.4, 137.3, 139.29, 
143.85, 146.7, 142.93, 144.24, 142.24, 146.02, 144.26, 144.99, 
145.31, 147.56, 148.2, 149.82, 159.21, 162.11, 164.82, 162.89, 
163.57, 163.15, 159.7, 157.35, 158.56, 161.34, 163.81, 163.36, 
165.71, 167.99, 172, 169.25, 167.85, 168.5, 168.44, 165.11, 163.87, 
165.2, 168.33, 173.52, 174.93, 178.74, 182.94, 179.95, 167.46, 
172.19, 160.65, 172.06, 163.06, 163.64, 173.57, 176.82, 171.54, 
184.59, 178, 181.66, 181.55, 187.48, 187.49, 182.22, 182.02, 
190.65, 193.46, 185.5, 184.97, 186.73, 183.23, 180.36, 188.63, 
193.09, 192.45, 191.76, 193.73, 197.75, 199.14, 201.72, 204.74, 
208.46, 209.31, 204.94, 204.57, 199.06, 207.18, 202.44, 199.44, 
198.04, 195.22, 187.92, 192.14, 198.83, 193.54, 195.46, 190.3, 
185.73, 190.92, 196.5, 199.43, 198.88, 200.99, 195.56, 196.61, 
200.55, 206.88, 205.6, 210.96), week_name.High = c(99.5, 100.33, 
100.9, 98.66, 100.44, 100.4, 99.52, 99.5, 96.01, 94.85, 94.47, 
95.81, 95.5, 96.94, 96.8, 97.66, 103, 103.17, 106.25, 108.05, 
107.25, 107.67, 106.55, 105.65, 107.02, 106.92, 109.66, 110.04, 
116.48, 118.82, 114.72, 114.6, 113.15, 113.85, 117.35, 118.89, 
117.78, 118.1, 119.5, 119.6, 121.46, 119.94, 115.01, 116.25, 
113.95, 106.42, 105.15, 109.19, 110.26, 110.4, 112, 112.19, 108.99, 
105.59, 106.72, 107.79, 109.4, 108.05, 108.93, 110.32, 116.63, 
116.41, 118, 119.79, 119.1, 118.37, 119.22, 125, 124.9, 124.43, 
125.99, 128.83, 126.4, 129.99, 129.04, 127.14, 127.1, 125.83, 
122.64, 124.5, 130, 130.93, 129.5, 129.97, 128.25, 125.35, 125.45, 
124, 119.95, 124, 121.99, 116.96, 102.62, 99, 92.46, 94.67, 94.76, 
85.4, 82.09, 82.4, 85.88, 85.43, 87.27, 82.81, 87.67, 90.41, 
86.59, 92.67, 94.94, 97.1, 96.82, 92.49, 93.28, 91.24, 93, 98.71, 
99.86, 102.66, 102.45, 102.04, 103.86, 106.75, 106.82, 104.71, 
106.12, 108.67, 108.8, 110.64, 109.14, 106.79, 106.27, 103.65, 
116.88, 118.15, 119.96, 119.91, 119.96, 120.88, 120.23, 118.93, 
119.25, 122.88, 122.74, 120.18, 127.1, 128.61, 124.11, 123.25, 
126, 128.24, 128.94, 128.32, 128.9, 129.98, 129.86, 132.31, 132.97, 
131.85, 132.89, 134.25, 127.75, 126.07, 124.2, 128.06, 128.83, 
129.09, 128.37, 128.93, 130.73, 129.8, 129.3, 132.28, 131.04, 
132, 128.93, 133.1, 131.99, 126.39, 128.22, 129.97, 131.94, 131.47, 
128.4, 128.83, 131.6, 128.8, 131.2, 132.34, 132.49, 130.2, 126.02, 
127.6, 130, 132.09, 135, 136.28, 139.94, 143.03, 141.4, 144.26, 
146.93, 147.53, 145.43, 146.44, 145.87, 146.3, 146.01, 146.4, 
148.2, 148.86, 150, 159.79, 164.35, 164.99, 166.25, 164.84, 164.26, 
164.31, 167.72, 159.64, 162.74, 164.73, 164.75, 166.34, 168.77, 
173.54, 173.48, 172.77, 171.41, 168.67, 169.89, 165.96, 165.61, 
168.24, 174.65, 177.77, 176.46, 185.63, 184.05, 182.29, 174, 
172.99, 172.72, 173.72, 169.58, 173.87, 177.67, 180.91, 186.63, 
190.53, 183.39, 188.07, 187.78, 189.84, 189.97, 182.98, 193.61, 
194.9, 194.3, 187.33, 186.48, 188.71, 183.72, 190.52, 192.79, 
194.81, 194.46, 193.86, 199.23, 201.19, 201.57, 207.52, 207.92, 
209.69, 210.69, 205.97, 207.64, 208.17, 208.93, 203.25, 201.47, 
198.26, 198.08, 196.7, 199.64, 199.99, 197.2, 196.85, 191.14, 
196.85, 197.84, 199.94, 200.88, 202, 201, 196.11, 201.82, 207.99, 
207.94, 211.75, 211.79), week_name.Low = c(96.26, 97.93, 94.55, 
96.2, 97.96, 97.81, 97.8, 96.46, 88.77, 92.26, 92.1, 93.55, 93.57, 
95.33, 94.53, 93.91, 97.23, 101.35, 102.21, 104.53, 103.57, 105.21, 
101.56, 102.1, 104.44, 104.1, 105.24, 108.1, 109.45, 113.52, 
110.02, 109.7, 103.7, 108.08, 111.63, 115.32, 114.3, 114.83, 
115.79, 115, 116.42, 110.96, 111.68, 112.83, 99.27, 101.34, 101.38, 
101.5, 104.72, 104, 104.13, 107.26, 99.03, 97.04, 100.05, 98.5, 
103.7, 100.6, 104.7, 104.53, 109.05, 111.8, 112.69, 113.81, 113.34, 
113.86, 115.28, 115.54, 121.64, 120.5, 120.78, 125.03, 123.02, 
124, 124.06, 122.86, 122.36, 118.15, 116.6, 120.4, 119.9, 126.13, 
126.25, 125.75, 123.68, 121.55, 121.5, 113.17, 115, 110.61, 109.95, 
96.6, 83.51, 84.35, 78.82, 79.52, 82.74, 75.4, 69.5, 76.79, 75.31, 
78.06, 80.32, 79.68, 81.52, 84.25, 82.11, 81.76, 89.69, 90.16, 
92.2, 84.19, 82.85, 83.02, 83.64, 89.41, 91.8, 94.85, 98.52, 
96.44, 98.2, 99.25, 99.83, 100.57, 101.74, 101.02, 105.11, 107.05, 
104.23, 103.51, 100.47, 99.5, 102.52, 115.06, 116.05, 116.7, 
116.21, 116.12, 116.92, 115.15, 116.16, 118.16, 118.94, 117.26, 
120.22, 121.25, 119.55, 119.15, 119.53, 125.17, 126.46, 124.26, 
126, 126.11, 127, 129.19, 130.68, 128.67, 129, 125.37, 121.9, 
121.74, 121.61, 124.11, 125.57, 125.47, 125.2, 126.57, 127.64, 
127.55, 127.12, 127.84, 127.77, 128.71, 116, 125.15, 121.4, 121.47, 
124.13, 122.82, 128.34, 127.12, 120.61, 122.17, 127.85, 122.93, 
127.04, 128.76, 126.96, 126.44, 122.42, 122.28, 125.39, 128.43, 
130.78, 133.67, 136.12, 138.27, 136.7, 138.53, 142.63, 143.27, 
141.18, 141.5, 141.28, 143.52, 144.15, 144.33, 145.06, 146.64, 
146.75, 149.38, 158.67, 162, 162.85, 162.52, 159.03, 158.85, 
159.21, 151.71, 157.52, 161.15, 163.11, 162.3, 162.19, 167.4, 
167.5, 167.82, 166.53, 165.9, 164.13, 162.73, 161.52, 163.8, 
168.01, 173.52, 173.58, 178.65, 178.5, 166, 161.85, 157.13, 159.53, 
166, 158.76, 161.54, 165.76, 173.04, 168.88, 184.11, 176.17, 
179.03, 180.74, 181.16, 180, 177.06, 180.84, 190.32, 181.91, 
179.04, 183.34, 180.27, 177.35, 179.32, 188.22, 191, 191.28, 
190.83, 192.46, 196.45, 196.81, 201.61, 203.7, 206.02, 203.37, 
202.17, 196.79, 198.87, 202.9, 198.56, 194.63, 193.2, 187, 187.56, 
192.14, 191.68, 188.9, 188.05, 181.85, 183.2, 188.56, 193.02, 
197.24, 197.72, 194.2, 193.18, 193.25, 200.51, 204.9, 203.9, 
208.5), week_name.Close = c(98.9, 99.34, 97.11, 98.54, 100.38, 
98.58, 98.99, 96.91, 91.81, 94.11, 93.99, 95, 95.21, 96.62, 96.18, 
95.21, 102.21, 103.16, 105.57, 107.04, 105.18, 106.23, 103.22, 
105.33, 105.1, 105.01, 108.97, 109.66, 116.38, 114.52, 113.89, 
112.71, 109.22, 113.44, 116.69, 115.8, 114.52, 116.25, 119.03, 
117.77, 118.03, 113.37, 114.8, 113.4, 101.45, 102.22, 101.97, 
105.83, 109.39, 104.53, 111.65, 108.1, 100.05, 102.93, 103.4, 
104.98, 107.93, 105.14, 106.16, 110.08, 114.23, 114.01, 115.55, 
119.06, 115.14, 116.31, 117.28, 124.35, 121.69, 122.03, 125.24, 
126.49, 124.2, 127.36, 125.86, 126.71, 123.46, 118.53, 121.5, 
121.54, 128.66, 126.25, 127.56, 126.6, 124.59, 122.86, 121.73, 
117.29, 115.19, 116.21, 114.46, 100.62, 92.21, 92.51, 79.66, 
92.68, 83.87, 77.48, 79.89, 76.9, 84.86, 82.77, 81.99, 81.25, 
86.82, 85.71, 84.92, 91.6, 90.93, 96.82, 93.84, 84.37, 89.05, 
83.48, 91.22, 98.71, 94.52, 101.56, 99.95, 100.43, 99.95, 106.19, 
102.9, 104.58, 101.89, 108.37, 107.49, 107.62, 104.52, 105.83, 
101.65, 103.62, 116.44, 117.63, 119.92, 118.7, 116.86, 119.32, 
118.05, 117.46, 118.88, 121.57, 119.33, 119.75, 127.04, 123.06, 
120.11, 120.56, 126, 128.21, 128.2, 126.35, 127.04, 129.93, 128.65, 
132.31, 132.45, 129.48, 131.78, 126.12, 124.67, 121.88, 124, 
126.85, 128.57, 126.41, 127.83, 127.98, 128.59, 129.35, 128.36, 
132.23, 130.73, 129.6, 126.27, 130.44, 124.45, 125.26, 124.13, 
128.5, 130.65, 128.98, 121.86, 128.67, 129.79, 128.41, 130.76, 
132, 127.77, 126.47, 123.4, 127.58, 129.61, 131.79, 134.65, 135.25, 
139.66, 142.83, 139.84, 143.32, 146.46, 143.64, 145.39, 142.89, 
144.99, 144.28, 144.51, 145.34, 147.48, 147.64, 150, 159.63, 
162, 164.82, 163.22, 164.84, 161.88, 159.93, 161.39, 157.68, 
161.37, 164.25, 163.95, 165.94, 167.67, 172.15, 169.1, 168.86, 
168.26, 167.5, 164.75, 163.17, 165.02, 167.62, 174.54, 174.99, 
175.28, 183.7, 180.75, 166.22, 172.99, 158.98, 172.62, 166.98, 
162.42, 173.13, 174.51, 173.29, 186.62, 186.59, 182.25, 184.63, 
187.32, 187.35, 181.48, 182.21, 190.84, 192.18, 182.89, 184.75, 
183.88, 181.59, 179.16, 189.98, 192.5, 192.82, 192.62, 193.42, 
197.53, 200.66, 201, 205.72, 207.77, 209.47, 204.94, 202.72, 
198.62, 207.08, 203.75, 199.44, 197.76, 194.3, 188.54, 192.51, 
198.29, 192.86, 195.83, 189.67, 184.79, 190.83, 196.68, 198.76, 
199.01, 200.5, 195.69, 194.85, 200.95, 207.15, 205.29, 210.47, 
210.59), week_name.Volume = c(37282600L, 34490200L, 72103000L, 
35304600L, 35062300L, 31814600L, 21716900L, 26604600L, 56820200L, 
38721500L, 35459800L, 29067900L, 33197100L, 18164700L, 29511500L, 
52169000L, 61078300L, 33877500L, 35091600L, 36793800L, 22759500L, 
27778100L, 66518900L, 32973100L, 37168200L, 27784000L, 25912300L, 
37629500L, 54802800L, 71895500L, 58311600L, 40516500L, 59093200L, 
35039700L, 27696100L, 35034600L, 31115400L, 38788700L, 34072400L, 
31575400L, 36526700L, 55268400L, 30288900L, 32096800L, 69116600L, 
46051300L, 25659000L, 47148000L, 28195400L, 39414600L, 38693000L, 
19929800L, 40717400L, 57960500L, 60116900L, 65627200L, 37134500L, 
40754300L, 27834600L, 39450600L, 52544400L, 42918100L, 48127600L, 
39096800L, 42806000L, 38850300L, 40554100L, 66402400L, 30926100L, 
36860400L, 41280900L, 38566900L, 25084400L, 40678500L, 33274500L, 
31999800L, 34940000L, 44494400L, 33408900L, 46532400L, 59004900L, 
44267500L, 28597400L, 35909400L, 31203800L, 34314800L, 24666200L, 
52464400L, 46239300L, 65242800L, 35473300L, 64743800L, 92429100L, 
67694100L, 59658900L, 57124300L, 49014100L, 58824600L, 78119400L, 
34933600L, 52366600L, 47455700L, 48363200L, 17953500L, 28316000L, 
40849400L, 40107300L, 71150300L, 50904900L, 51898900L, 40967100L, 
55929100L, 79527800L, 72403700L, 60473500L, 63944400L, 59507500L, 
62768300L, 31864500L, 46439300L, 55556000L, 46096800L, 42630800L, 
41405700L, 27170000L, 35055100L, 34231100L, 41116800L, 41658500L, 
28258100L, 26599100L, 37179800L, 59981900L, 36906700L, 29124700L, 
25766900L, 26769400L, 28636000L, 25199700L, 19870500L, 26587300L, 
40616200L, 29966100L, 34804800L, 39882700L, 55762400L, 35316400L, 
39296300L, 31506100L, 31122900L, 22663700L, 18406100L, 28149400L, 
30299600L, 34023700L, 19728600L, 18429900L, 28214900L, 30143100L, 
54549400L, 44290800L, 33539400L, 24370300L, 28241800L, 24394500L, 
30775100L, 32034400L, 33833600L, 30444800L, 17430600L, 24267600L, 
42690100L, 40276900L, 35084700L, 46575300L, 52467100L, 50683900L, 
33725800L, 38106600L, 36247600L, 35063700L, 35207000L, 33590800L, 
26983200L, 34873200L, 42114800L, 30349700L, 26447800L, 25598600L, 
24864600L, 28421300L, 21493500L, 21957500L, 31840900L, 27366900L, 
28739400L, 25971400L, 37617800L, 36301100L, 33387900L, 25886500L, 
24184000L, 24110800L, 16566000L, 26904000L, 22440100L, 27448800L, 
11905100L, 16973400L, 22515800L, 16245100L, 43051900L, 32415000L, 
23102000L, 25299000L, 14460200L, 26206300L, 22076300L, 30084300L, 
43281500L, 23560600L, 18318600L, 18516600L, 24189700L, 27181100L, 
28671300L, 27664200L, 24566100L, 26479700L, 17574600L, 26962300L, 
22120500L, 28242500L, 23468600L, 18954000L, 25544400L, 27951500L, 
33608200L, 27150100L, 51191400L, 48519200L, 47115400L, 31833500L, 
20994900L, 30576100L, 32972600L, 33780600L, 39165300L, 34860000L, 
29226400L, 43896300L, 27538400L, 21739700L, 23410900L, 24628600L, 
15736500L, 27018800L, 22239600L, 31429900L, 22126900L, 12119700L, 
24554100L, 21432000L, 37772600L, 21429500L, 21984400L, 16963100L, 
14691000L, 21713700L, 22510200L, 18005300L, 26489600L, 16787200L, 
15977000L, 15631400L, 18022300L, 30358900L, 19202500L, 15299800L, 
16875200L, 23183500L, 14138300L, 26339400L, 16651400L, 20490000L, 
23027000L, 18252500L, 13081600L, 22155100L, 32267700L, 17678100L, 
14494800L, 12456600L, 12291400L, 14303100L, 10614800L, 19380300L, 
18406400L, 25103400L, 19908200L, 12329200L), week_name.Adjusted = c(89.57, 
89.96, 87.94, 89.24, 90.91, 89.54, 89.92, 88.03, 83.4, 85.48, 
85.38, 86.29, 86.48, 87.76, 87.36, 86.48, 92.84, 93.71, 96.27, 
97.61, 95.91, 96.87, 94.12, 96.05, 95.84, 95.76, 99.37, 100, 
106.12, 104.43, 103.85, 103.14, 99.95, 103.81, 106.78, 105.97, 
104.8, 106.38, 108.93, 107.77, 108.01, 103.75, 105.05, 103.77, 
93.17, 93.87, 93.64, 97.19, 100.46, 96, 102.53, 99.27, 91.88, 
94.53, 94.96, 96.41, 99.12, 96.92, 97.87, 101.48, 105.3, 105.1, 
106.52, 109.76, 106.14, 107.22, 108.12, 114.63, 112.18, 112.5, 
115.93, 117.08, 114.96, 117.89, 116.5, 117.29, 114.28, 109.72, 
112.46, 112.5, 119.09, 116.86, 118.07, 117.64, 115.77, 114.17, 
113.12, 108.99, 107.04, 107.99, 106.36, 93.5, 85.68, 85.96, 74.02, 
86.12, 78.37, 72.4, 74.65, 71.86, 79.3, 77.34, 76.61, 75.92, 
81.13, 80.09, 79.35, 85.59, 84.97, 90.96, 88.16, 79.27, 83.66, 
78.43, 85.7, 92.74, 88.8, 95.42, 93.9, 94.36, 93.9, 99.77, 97.18, 
98.77, 96.23, 102.35, 101.52, 101.64, 98.71, 99.95, 96, 97.86, 
109.97, 111.09, 113.26, 112.63, 110.88, 113.21, 112.01, 111.45, 
112.8, 115.35, 113.22, 113.62, 120.54, 116.76, 113.96, 114.39, 
120.09, 122.2, 122.19, 120.42, 121.08, 123.83, 122.61, 126.1, 
126.24, 123.41, 125.6, 120.2, 118.82, 116.68, 118.71, 121.44, 
123.09, 121.02, 122.38, 122.52, 123.11, 123.83, 122.89, 126.59, 
125.15, 124.07, 121.5, 125.52, 119.75, 120.53, 119.44, 123.65, 
125.72, 124.11, 117.26, 123.81, 124.89, 123.56, 125.82, 127.65, 
123.56, 122.3, 119.33, 123.37, 125.34, 127.44, 130.21, 130.79, 
135.05, 138.12, 135.23, 138.59, 142.26, 139.52, 141.22, 138.79, 
140.83, 140.14, 140.37, 141.17, 143.25, 143.41, 145.7, 155.05, 
157.35, 160.09, 159.17, 160.75, 157.86, 155.96, 157.38, 153.76, 
157.36, 160.17, 159.88, 161.82, 163.51, 167.87, 165.64, 165.4, 
164.82, 164.07, 161.38, 159.83, 161.64, 164.19, 170.97, 171.41, 
171.69, 179.94, 177.05, 163.53, 170.19, 156.4, 169.82, 164.27, 
159.79, 170.32, 171.68, 170.48, 183.6, 183.57, 179.3, 181.64, 
184.28, 185.05, 179.26, 179.98, 188.5, 189.83, 180.65, 182.49, 
181.63, 179.37, 176.96, 187.65, 190.14, 190.46, 191, 191.79, 
195.87, 198.97, 199.31, 203.99, 206.02, 207.71, 203.22, 201.02, 
196.95, 205.34, 202.04, 198.59, 196.92, 193.47, 187.74, 191.69, 
197.45, 192.04, 195, 188.86, 184, 190.02, 195.84, 197.91, 199.01, 
200.5, 195.69, 194.85, 200.95, 207.15, 205.29, 210.47, 210.59
)), .Names = c("week_name.Open", "week_name.High", "week_name.Low", 
"week_name.Close", "week_name.Volume", "week_name.Adjusted"), class =
"data.frame", row.names = c("2007-01-08", 
"2007-01-12", "2007-01-22", "2007-01-29", "2007-02-05", "2007-02-12", 
"2007-02-16", "2007-02-26", "2007-03-05", "2007-03-12", "2007-03-19", 
"2007-03-26", "2007-04-02", "2007-04-09", "2007-04-16", "2007-04-23", 
"2007-04-30", "2007-05-07", "2007-05-14", "2007-05-21", "2007-05-25", 
"2007-06-04", "2007-06-11", "2007-06-18", "2007-06-25", "2007-07-02", 
"2007-07-09", "2007-07-16", "2007-07-23", "2007-07-30", "2007-08-06", 
"2007-08-13", "2007-08-20", "2007-08-27", "2007-08-31", "2007-09-10", 
"2007-09-17", "2007-09-24", "2007-10-01", "2007-10-08", "2007-10-15", 
"2007-10-22", "2007-10-29", "2007-11-05", "2007-11-12", "2007-11-19", 
"2007-11-26", "2007-12-03", "2007-12-10", "2007-12-17", "2007-12-24", 
"2007-12-31", "2008-01-07", "2008-01-14", "2008-01-18", "2008-01-28", 
"2008-02-04", "2008-02-11", "2008-02-15", "2008-02-25", "2008-03-03", 
"2008-03-10", "2008-03-17", "2008-03-24", "2008-03-31", "2008-04-07", 
"2008-04-14", "2008-04-21", "2008-04-28", "2008-05-05", "2008-05-12", 
"2008-05-19", "2008-05-23", "2008-06-02", "2008-06-09", "2008-06-16", 
"2008-06-23", "2008-06-30", "2008-07-07", "2008-07-14", "2008-07-21", 
"2008-07-28", "2008-08-04", "2008-08-11", "2008-08-18", "2008-08-25", 
"2008-08-29", "2008-09-08", "2008-09-15", "2008-09-22", "2008-09-29", 
"2008-10-06", "2008-10-13", "2008-10-20", "2008-10-27", "2008-11-03", 
"2008-11-10", "2008-11-17", "2008-11-24", "2008-12-01", "2008-12-08", 
"2008-12-15", "2008-12-22", "2008-12-29", "2009-01-05", "2009-01-12", 
"2009-01-16", "2009-01-26", "2009-02-02", "2009-02-09", "2009-02-13", 
"2009-02-23", "2009-03-02", "2009-03-09", "2009-03-16", "2009-03-23", 
"2009-03-30", "2009-04-06", "2009-04-13", "2009-04-20", "2009-04-27", 
"2009-05-04", "2009-05-11", "2009-05-18", "2009-05-22", "2009-06-01", 
"2009-06-08", "2009-06-15", "2009-06-22", "2009-06-29", "2009-07-06", 
"2009-07-13", "2009-07-20", "2009-07-27", "2009-08-03", "2009-08-10", 
"2009-08-17", "2009-08-24", "2009-08-31", "2009-09-04", "2009-09-14", 
"2009-09-21", "2009-09-28", "2009-10-05", "2009-10-12", "2009-10-19", 
"2009-10-26", "2009-11-02", "2009-11-09", "2009-11-16", "2009-11-23", 
"2009-11-30", "2009-12-07", "2009-12-14", "2009-12-21", "2009-12-28", 
"2010-01-04", "2010-01-11", "2010-01-15", "2010-01-25", "2010-02-01", 
"2010-02-08", "2010-02-12", "2010-02-22", "2010-03-01", "2010-03-08", 
"2010-03-15", "2010-03-22", "2010-03-29", "2010-04-05", "2010-04-12", 
"2010-04-19", "2010-04-26", "2010-05-03", "2010-05-10", "2010-05-17", 
"2010-05-24", "2010-05-28", "2010-06-07", "2010-06-14", "2010-06-21", 
"2010-06-28", "2010-07-02", "2010-07-12", "2010-07-19", "2010-07-26", 
"2010-08-02", "2010-08-09", "2010-08-16", "2010-08-23", "2010-08-30", 
"2010-09-03", "2010-09-13", "2010-09-20", "2010-09-27", "2010-10-04", 
"2010-10-11", "2010-10-18", "2010-10-25", "2010-11-01", "2010-11-08", 
"2010-11-15", "2010-11-22", "2010-11-29", "2010-12-06", "2010-12-13", 
"2010-12-20", "2010-12-27", "2011-01-03", "2011-01-10", "2011-01-14", 
"2011-01-24", "2011-01-31", "2011-02-07", "2011-02-14", "2011-02-18", 
"2011-02-28", "2011-03-07", "2011-03-14", "2011-03-21", "2011-03-28", 
"2011-04-04", "2011-04-11", "2011-04-18", "2011-04-25", "2011-05-02", 
"2011-05-09", "2011-05-16", "2011-05-23", "2011-05-27", "2011-06-06", 
"2011-06-13", "2011-06-20", "2011-06-27", "2011-07-01", "2011-07-11", 
"2011-07-18", "2011-07-25", "2011-08-01", "2011-08-08", "2011-08-15", 
"2011-08-22", "2011-08-29", "2011-09-02", "2011-09-12", "2011-09-19", 
"2011-09-26", "2011-10-03", "2011-10-10", "2011-10-17", "2011-10-24", 
"2011-10-31", "2011-11-07", "2011-11-14", "2011-11-21", "2011-11-28", 
"2011-12-05", "2011-12-12", "2011-12-19", "2011-12-23", "2011-12-30", 
"2012-01-09", "2012-01-13", "2012-01-23", "2012-01-30", "2012-02-06", 
"2012-02-13", "2012-02-17", "2012-02-27", "2012-03-05", "2012-03-12", 
"2012-03-19", "2012-03-26", "2012-04-02", "2012-04-09", "2012-04-16", 
"2012-04-23", "2012-04-30", "2012-05-07", "2012-05-14", "2012-05-21", 
"2012-05-25", "2012-06-04", "2012-06-11", "2012-06-18", "2012-06-25", 
"2012-07-02", "2012-07-09", "2012-07-16", "2012-07-23", "2012-07-30", 
"2012-08-06", "2012-08-13", "2012-08-20", "2012-08-27", "2012-08-31", 
"2012-09-10", "2012-09-17", "2012-09-24", "2012-10-01", "2012-10-05"
))
> 

-------------------------------------------------------------------------------------------------------------------------------------
datafrom_table having these values .

i used to do with 

d=dput(head(datafrom_table, 30))

charts.PerformanceSummary(d, rf = 0, main = NULL, method = "ModifiedVaR",
width = 0,event.labels = NULL, ylog = FALSE, wealth.index = FALSE, gap = 12)

it gives the result . but the number of morethan 40 it print a blank chart
sheet. 

i hop now u can reply to me ..

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