r - Merge new row into an existing xts ( purpose: to add current stock quote to historical object from quantmod) -


what , attach current stock price historical xts object. example, 

require(quantmod) x=getsymbols("aapl", = "2014-10-27" ,auto.assign=false) q = getquote('aapl')  # produces, > tail(x)            aapl.open aapl.high aapl.low aapl.close aapl.volume aapl.adjusted 2015-05-06    126.56    126.75   123.36     125.01    72141000        124.49 2015-05-07    124.77    126.08   124.02     125.26    43940900        125.26 2015-05-08    126.68    127.62   126.11     127.62    55550400        127.62 2015-05-11    127.39    127.56   125.63     126.32    42035800        126.32 2015-05-12    125.60    126.88   124.82     125.87    47109200        125.87 2015-05-13    126.15    127.19   125.87     126.01    34322000        126.01 > q               trade time     last change % change   open   high    low   volume aapl 2015-05-14 11:38:00 128.3993 2.3893 +1.8961% 127.45 128.45 127.16 22635316

what place "last" column q aapl.close column, high & low aapl.high, aapl.close, respectively. have tried far create new dataframe adding in new columns, renaming them , merging onto original xts not appear work. in advance.

you need create new xts object quote data , rbind historical data.

require(quantmod) x <- getsymbols("aapl", = "2014-10-27" ,auto.assign=false) q <- getquote('aapl')  qcols <- c("open","high","low","last","volume","last") qx <- xts(q[,qcols], as.date(q[,"trade time"])) y <- rbind(x, qx)  tail(y) #            aapl.open aapl.high aapl.low aapl.close aapl.volume aapl.adjusted # 2015-05-07    124.77    126.08   124.02     125.26    43940900        125.26 # 2015-05-08    126.68    127.62   126.11     127.62    55550400        127.62 # 2015-05-11    127.39    127.56   125.63     126.32    42035800        126.32 # 2015-05-12    125.60    126.88   124.82     125.87    47109200        125.87 # 2015-05-13    126.15    127.19   125.87     126.01    34322000        126.01 # 2015-05-14    127.45    128.45   127.16     128.40    22635316        128.40

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