data.frame to xts conversion result appear with quotation marks - xts

Question

I know there are various examples on stackoverflow thats discusses this problem but even after going through them I was still unable to find a solution. What is the best way to convert to numeric with regard to OHLCV thats appearing as characters. What am I missing here or doing wrong?
rm(list = ls(all = TRUE))
setwd("~/Documents/R")
library(jsonlite)
library(ggplot2)
library(forecast)
library(xts)
library(quantmod)
library(anytime)
library(highfrequency)
library(lubridate)
setwd("~/Documents/R/STK/csv")
gdax <- read.csv(file="GDAX_BTCUSD.csv", sep="\t", dec=".", header=FALSE, stringsAsFactors = FALSE, na.strings = "NA")
options(scipen=999)
gdax <- na.omit(gdax[,c(9,4,5,6,7,8)])
colnames(gdax) <- c("Date", "Open", "High", "Low", "Close", "Volume")
> class(gdax)
[1] "data.frame"
> head(gdax)
Date Open High Low Close Volume
1 2016-05-16 00:00:00 461.4800000000 461.4900000000 461.4700000000 461.4900000000 5.345398
2 2016-05-16 00:01:00 461.4700000000 461.4900000000 461.4700000000 461.4900000000 4.650470
3 2016-05-16 00:02:00 461.4800000000 461.4900000000 461.4700000000 461.4900000000 1.360030
4 2016-05-16 00:03:00 461.4900000000 461.4900000000 461.4900000000 461.4900000000 0.586860
5 2016-05-16 00:04:00 461.4700000000 461.4700000000 461.4700000000 461.4700000000 0.135180
6 2016-05-16 00:05:00 461.4700000000 461.5000000000 461.4400000000 461.5000000000 11.257970
GDAX_BTC <- xts(gdax[, 2:6], order.by=as.POSIXct(gdax[,1], tz="UTC"))
> head(GDAX_BTC)
Open High Low Close Volume
2016-05-16 00:00:00 "461.4800000000" "461.4900000000" "461.4700000000" "461.4900000000" " 5.34539836"
2016-05-16 00:01:00 "461.4700000000" "461.4900000000" "461.4700000000" "461.4900000000" " 4.65047000"
2016-05-16 00:02:00 "461.4800000000" "461.4900000000" "461.4700000000" "461.4900000000" " 1.36003000"
2016-05-16 00:03:00 "461.4900000000" "461.4900000000" "461.4900000000" "461.4900000000" " 0.58686000"
2016-05-16 00:04:00 "461.4700000000" "461.4700000000" "461.4700000000" "461.4700000000" " 0.13518000"
2016-05-16 00:05:00 "461.4700000000" "461.5000000000" "461.4400000000" "461.5000000000" " 11.25797000"
> class(GDAX_BTC)
[1] "xts" "zoo"
GDAX_BTC <- xts(gdax[,-1], order.by=as.POSIXct(gdax$Date, format = "%Y-%m-%d %H:%M:%S"))
# no changes in the output.
#
R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.2
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] lubridate_1.7.1 highfrequency_0.5.2 anytime_0.3.0 quantmod_0.4-12 TTR_0.23-2 xts_0.10-1
[7] zoo_1.8-0 forecast_8.2 ggplot2_2.2.1 jsonlite_1.5
loaded via a namespace (and not attached):
[1] Rcpp_0.12.14 magrittr_1.5 munsell_0.4.3 colorspace_1.3-2 lattice_0.20-35 rlang_0.1.6 quadprog_1.5-5
[8] stringr_1.2.0 plyr_1.8.4 tools_3.4.3 nnet_7.3-12 parallel_3.4.3 grid_3.4.3 RApiDatetime_0.0.3
[15] timeDate_3042.101 gtable_0.2.0 tseries_0.10-42 yaml_2.1.16 lazyeval_0.2.1 lmtest_0.9-35 tibble_1.4.1
[22] curl_3.1 fracdiff_1.4-2 stringi_1.1.6 compiler_3.4.3 pillar_1.0.1 scales_0.5.0