Convert Dataframe object into xts

Question

> df <- read.csv("C:\\Users\\Vikas Kumar Dwivedi\\Desktop\\Yahoo.csv")
> df
         Date        Open        High         Low       Close   Adj.Close      Volume
1  01-03-2013        null        null        null        null        null        null
2  01-04-2013 1569.180054 1597.569946 1536.030029 1597.569946 1597.569946 77098000000
3  01-05-2013 1597.550049 1687.180054 1581.280029  1630.73999  1630.73999 76447250000


> df$Date <- as.Date(df$Date, format("%m/%d/%Y"))
> df <- df[order(df$Date), ]
> df<- as.xts(df[, 2], order.by = df$Date)
Error in UseMethod("as.xts") : 
  no applicable method for 'as.xts' applied to an object of class "factor"

I am not able to convert dataframe into xts? Could you please help me.

Answer 1

The problem is that the columns in your CSV contain numbers and characters, so read.csv() interprets them as factors. You need to do what quantmod::getSymbols.yahoo() does and set na.strings = "null" . That tells read.csv() to treat the character string "null" as a NA value.

csv <- "Date,Open,High,Low,Close,Adj.Close,Volume
01-03-2013,null,null,null,null,null,null
01-04-2013,1569.180054,1597.569946,1536.030029,1597.569946,1597.569946,77098000000
01-05-2013,1597.550049,1687.180054,1581.280029,1630.73999,1630.73999,76447250000"
d <- read.csv(text = csv, na.strings = "null")
# also note that your date format was wrong, and there is no need to wrap a character
# string in `format()`
d$Date <- as.Date(d$Date, format = "%m-%d-%Y")
#d <- d[order(d$Date), ]  # this isn't necessary, xts() will do it for you
(x <- xts(d[, 2], order.by = d$Date))
#               [,1]
# 2013-01-03      NA
# 2013-01-04 1569.18
# 2013-01-05 1597.55

Or you can do all of this with a call to read.csv.zoo() and wrap it in as.xts() if you prefer an xts object.

(x <- as.xts(read.csv.zoo(text = csv, format = "%m-%d-%Y", na.strings = "null")))
#               Open    High     Low   Close Adj.Close      Volume
# 2013-01-03      NA      NA      NA      NA        NA          NA
# 2013-01-04 1569.18 1597.57 1536.03 1597.57   1597.57 77098000000
# 2013-01-05 1597.55 1687.18 1581.28 1630.74   1630.74 76447250000