I have two time series data frames:
The first one:
head(df1) :
MSCI ACWI DJGlbl Russell 1000 Russell Dev S&P GSCI Industrial S&P GSCI Precious
1999-03-01 -0.7000000 0.2000000 -0.1000000 -1.5000000 -1.0000000 -0.4000000
1999-03-02 -0.5035247 0.0998004 -0.7007007 -0.2030457 0.4040404 -0.3012048
1999-03-03 -0.2024291 0.2991027 0.0000000 -0.6103764 0.1006036 -0.1007049
1999-03-04 0.7099391 0.2982107 1.5120968 -0.1023541 0.5025126 0.4032258
1999-03-05 2.4169184 0.8919722 2.1847071 2.7663934 -1.2000000 0.0000000
1999-03-08 0.3933137 0.3929273 0.5830904 -0.0997009 -0.2024291 1.1044177
tail(df1) :
MSCI ACWI DJGlbl Russell 1000 Russell Dev S&P GSCI Industrial S&P GSCI Precious
2011-12-23 0.68241470 0.84790673 0.9441385 0.6116208 0.5822862 -0.2345300
2011-12-26 -0.05213764 0.00000000 0.0000000 0.0000000 0.0000000 0.0000000
2011-12-27 0.20865936 0.05254861 0.3117693 0.2431611 0.0000000 -0.7233273
2011-12-28 -0.62467465 -1.20798319 -1.1655012 -0.9702850 -2.0414381 -2.4043716
2011-12-29 0.52383447 0.47846890 0.8647799 0.5511329 -0.0933126 -1.2504666
2011-12-30 0.26055237 1.03174603 -0.4676539 1.2180268 1.9613948 1.7388017
The second one:
head(df2) :
MSCI.ACWI DJGlbl Russell.1000 Russell.Dev S.P.GSCI.Industrial S.P.GSCI.Precious
1999-06-01 0.00000000 0.24438520 0.0000000 0 -0.88465521 0.008522842
1999-07-01 0.12630441 0.06755621 0.0000000 0 0.29394697 0.000000000
1999-08-02 0.07441812 0.18922829 0.0000000 0 0.02697299 -0.107155063
1999-09-01 -0.36952701 0.08684107 0.1117509 0 0.24520976 0.000000000
1999-10-01 0.00000000 0.00000000 0.0000000 0 0.00000000 1.941266205
1999-11-01 0.41879925 0.00000000 0.0000000 0 0.00000000 -0.197897901
tail(df2) :
MSCI.ACWI DJGlbl Russell.1000 Russell.Dev S.P.GSCI.Industrial S.P.GSCI.Precious
2011-07-01 0.00000000 0.0000000 0.0000000 0.0000000 0.00000000 -0.1141162
2011-08-01 0.00000000 0.0000000 0.0000000 0.0000000 0.02627347 0.0000000
2011-09-01 -0.02470873 0.2977585 -0.0911891 0.6367605 0.00000000 0.2830977
2011-10-03 0.42495188 0.0000000 0.4200743 -0.4420027 -0.41012646 0.0000000
2011-11-01 0.00000000 0.0000000 0.0000000 -0.6597739 0.00000000 0.0000000
2011-12-01 0.50273034 0.0000000 0.0000000 0.6476393 0.00000000 0.0000000
The first df cointains daily observations. The second df contains only the "first day of each month" forecasted values. I would like to substitute the values from the second df into the first one. In other words, the "first day of each month" values in the first df will be substituted for the "first day of each month" values from the second df. I tried to write an lapply loop that substitutes the values and was only trying to use match function. But I failed. I could not find the similar question at StackOverflow either...
Greatful for any suggestions!
P.S.
The thing is that the above df's are time series. Namely I convert the df's to time series :
library(fPortfolio)
charvec=dfnottimeseries[,1]
df1=as.timeSeries(dfnottimeseries,charvec)
and the same for the second df (df2). For example:
dput(head(df1)) :
new("timeSeries"
, .Data = structure(c(-0.700000000000003, -0.503524672708963, -0.202429149797574,
0.709939148073025, 2.41691842900303, 0.393313667649942, 0.200000000000003,
0.0998003992015911, 0.299102691924224, 0.298210735586492, 0.891972249752221,
0.392927308447943, -0.0999999999999943, -0.700700700700703, 0,
1.51209677419355, 2.18470705064548, 0.583090379008741, -1.5,
-0.203045685279191, -0.610376398779241, -0.102354145342895, 2.76639344262295,
-0.0997008973080701, -1, 0.40404040404041, 0.100603621730377,
0.50251256281407, -1.2, -0.202429149797574, -0.400000000000006,
-0.301204819277106, -0.100704934541787, 0.403225806451604, 0,
1.10441767068274, 0.0999999999999943, 1.59840159840161, 2.94985250737463,
3.15186246418338, 0.55555555555555, 2.30202578268877, -0.0999999999999943,
0.800800800800798, 0.496524329692155, 0.691699604743086, 0.196270853778203,
0.685602350636634, -0.0999999999999943, 0, -0.100100100100109,
-0.100200400801598, 0.100300902708119, 0.300601202404807, -0.799999999999997,
0, -0.302419354838707, 0, 0.707785642062678, -0.200803212851394,
-0.200000000000003, -0.200400801603209, -0.100401606425697, -0.201005025125631,
0.201409869083588, 0.100502512562808, -0.200000000000003, -0.200400801603209,
-0.100401606425697, -0.201005025125631, 0.201409869083588, 0.100502512562808,
0, -0.299999999999997, -1.00300902708124, -0.303951367781152,
0.711382113821127, 0.40363269424824, -0.00938085999999316, 0.00938174008789637,
-0.196998120000003, -0.0751950428206875, 0.0470322689501711,
0.047010148983195, -0.00938085999999316, 0.00938174008789637,
-0.196998120000003, -0.0751950428206875, 0.0470322689501711,
0.047010148983195), .Dim = c(6L, 15L), .Dimnames = list(c("1999-03-01",
"1999-03-02", "1999-03-03", "1999-03-04", "1999-03-05", "1999-03-08"
), c("MSCI ACWI", "DJGlbl", "Russell 1000", "Russell Dev", "S&P GSCI Industrial ",
"S&P GSCI Precious", "S&P GSCI Energy", "UBS Bloomberg", "iBoxx $ Liquid",
"IBOXX ??? LQD", "iBoxx $ Liquid High Yield", "Markit IBOXX",
"DBIQ Emerging", "Barclays US", "iBoxx Sov Euro IL")))
, units = c("MSCI ACWI", "DJGlbl", "Russell 1000", "Russell Dev", "S&P GSCI Industrial ",
"S&P GSCI Precious", "S&P GSCI Energy", "UBS Bloomberg", "iBoxx $ Liquid",
"IBOXX ??? LQD", "iBoxx $ Liquid High Yield", "Markit IBOXX",
"DBIQ Emerging", "Barclays US", "iBoxx Sov Euro IL")
, positions = c(920246400, 920332800, 920419200, 920505600, 920592000, 920851200
)
, format = "%Y-%m-%d"
, FinCenter = "GMT"
, recordIDs = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")
, title = "Time Series Object"
, documentation = "Sun Oct 21 16:13:25 2012"
)
and
dput(head(df2))
new("timeSeries"
, .Data = structure(c(0, 0.126304409, 0.074418121, -0.369527006, 0, 0.41879925,
0.244385197, 0.067556211, 0.189228292, 0.086841066, 0, 0, 0,
0, 0, 0.111750885, 0, 0, 0, 0, 0, 0, 0, 0, -0.88465521, 0.293946971,
0.026972992, 0.245209764, 0, 0, 0.008522842, 0, -0.107155063,
0, 1.941266205, -0.197897901, -0.013096887, 0, 0, 0.388013092,
0.372488895, 0, -0.19041112, 0.136631233, 0, 0.183846748, 0.197612269,
0, -0.002248848, 0.274449827, -0.143453619, -0.128428882, 0,
0.144213551, -0.044105244, 0, -0.137138837, -0.074970085, 0,
0, -0.128433675, 0.141883192, -0.052900591, -0.062071483, 0.062037765,
0, -0.128433675, 0.141883192, -0.052900591, -0.062071483, 0.062037765,
0, -0.133904169, 0.360826639, -0.040831396, -0.060762388, 0,
0.129691732, 0.050392981, 0.020081642, 0.01978185, 0.030688482,
0, 0.012962734, 0.050392981, 0.020081642, 0.01978185, 0.030688482,
0, 0.012962734), .Dim = c(6L, 15L), .Dimnames = list(NULL, c("MSCI ACWI",
"DJGlbl", "Russell 1000", "Russell Dev", "S&P GSCI Industrial ",
"S&P GSCI Precious", "S&P GSCI Energy", "UBS Bloomberg", "iBoxx $ Liquid",
"IBOXX ??? LQD", "iBoxx $ Liquid High Yield", "Markit IBOXX",
"DBIQ Emerging", "Barclays US", "iBoxx Sov Euro IL")))
, units = c("MSCI ACWI", "DJGlbl", "Russell 1000", "Russell Dev", "S&P GSCI Industrial ",
"S&P GSCI Precious", "S&P GSCI Energy", "UBS Bloomberg", "iBoxx $ Liquid",
"IBOXX ??? LQD", "iBoxx $ Liquid High Yield", "Markit IBOXX",
"DBIQ Emerging", "Barclays US", "iBoxx Sov Euro IL")
, positions = c(928195200, 930787200, 933552000, 936144000, 938736000, 941414400
)
, format = "%Y-%m-%d"
, FinCenter = "GMT"
, recordIDs = structure(list(), .Names = character(0), row.names = integer(0), class = "data.frame")
, title = "Time Series Object"
, documentation = "Sun Oct 21 19:10:08 2012"
)