I have more than 300 stocks downloaded with getsymbols() and I have the name of this stocks in a vector, for example:
USA_STOCKS = c("AAL","AAPL","ADBE","ADI","ADP","ADSK","ALGN",
"ALXN","AMAT","AMGN","AMZN","ASML","ATVI","AVGO",
"BIDU","BIIB") # This is just an extract from 300
getSymbols(AAL) # this is just one of the 300 "getsymbols"
With that, I have a XTS object called AAL and a vector USA_TOCKS with all the name of the XTS Objets.
I would like to do:
AAL = na.omit(AAL)
But, instead of use the Object AAL, I want to refer the object using the name inside the vector. Something like this:
USA_STOCKS[1] = na.omit(USA_STOCKS[1])
Obviusly if i did this, I will change only the name of "AAL" inside the vector. But what I want is to refer the object AAL.
Hmm, still a bit unclear, but I think you want to do something like this:
library(quantmod)
USA_STOCKS = c("AAL","AAPL","ADBE")
# Put all requested quotes in big list
stocks_usa <- lapply(USA_STOCKS,
getSymbols,
from = "2018-10-01",
to = "2018-11-01",
auto.assign = F)
# set the names of the list
names(stocks_usa) <- USA_STOCKS
#reference AAL
head(stocks_usa$AAL)
AAL.Open AAL.High AAL.Low AAL.Close AAL.Volume AAL.Adjusted
2018-10-01 41.41 41.75 39.60 39.61 7210700 39.50097
2018-10-02 39.60 39.60 38.40 38.50 7625000 38.39403
2018-10-03 38.70 39.26 38.42 38.80 6370300 38.69320
2018-10-04 38.80 39.01 37.48 37.92 5916500 37.81562
2018-10-05 37.93 38.13 36.21 36.44 9127000 36.33969
2018-10-08 36.44 36.85 35.60 35.90 7879300 35.80119
# more referencing
stocks_usa$AAL <- na.omit(stocks_usa$AAL)
Related
quantmode newbie here,
My end goal is to have a CSV file including monthly stock prices, I've downloaded the data using getSymbols using this code:
Symbols <- c("DIS", "TSLA","ATVI", "MSFT", "FB", "ABT","AAPL","AMZN",
"BAC","NFLX","ADBE","WMT","SRE","T","MS")
Data <- new.env()
getSymbols(c("^GSPC",Symbols),from="2015-01-01",to="2020-12-01"
,periodicity="monthly",
env=Data)
the line above works fine, now I need to create a data frame that only includes the adjusted prices for all the symbols with a data column ofc,
any help, please? :)
Desired output would be something similar to this
enter image description here
Another straightforward way to get your monthly data:
tickers <- c('AMZN','FB','GOOG','AAPL')
getSymbols(tickers,periodicity="monthly")
head(do.call("merge.xts",c(lapply(mget(tickers),"[",,6),all=FALSE)),3)
AMZN.Adjusted FB.Adjusted GOOG.Adjusted AAPL.Adjusted
2012-06-01 228.35 31.10 288.9519 17.96558
2012-07-01 233.30 21.71 315.3032 18.78880
2012-08-01 248.27 18.06 341.2658 20.46477
Note the logical argument all = FALSE is the equivalent of an innerjoin and you get data when all of your stocks have prices. all = TRUE fills data which is not available with NAs (outerjoin).
To write the file you can use:
write.zoo(monthlyPrices,file = 'filename.csv',sep=',',quote=FALSE)
First get your data from the environment:
require(quantmod)
# your code
dat <- mget(ls(Data), env=Data)
Then draw the data from the Objects:
newdat <- as.data.frame(sapply( names(dat), function(x) coredata(dat[[x]])[,1] ))
Note that this takes the Opening values (see: dat[[x]])[,1]), the Objects have more, e.g.:
names(dat[["AAPL"]])
[1] "AAPL.Open" "AAPL.High" "AAPL.Low" "AAPL.Close"
[5] "AAPL.Volume" "AAPL.Adjusted"
Last, get the dates (assumes symmetric dates for all symbols):
rownames(newdat) <- index(dat[["AAPL"]])
# OR, more universal, by extracting from the complete list:
rownames(newdat) <-
as.data.frame( sapply( names(dat), function(x) as.character(index(dat[[x]])) ) )[,1]
head(newdat, 3)
AAPL ABT ADBE AMZN ATVI BAC DIS FB GSPC MS
2015-01-01 27.8475 45.25 72.70 312.58 20.24 17.99 94.91 78.58 2058.90 39.05
2015-02-01 29.5125 44.93 70.44 350.05 20.90 15.27 91.30 76.11 1996.67 33.96
2015-03-01 32.3125 47.34 79.14 380.85 23.32 15.79 104.35 79.00 2105.23 35.64
MSFT NFLX SRE T TSLA WMT
2015-01-01 46.66 49.15143 111.78 33.59 44.574 86.27
2015-02-01 40.59 62.84286 112.38 33.31 40.794 84.79
2015-03-01 43.67 67.71429 108.20 34.56 40.540 83.93
Writing the csv:
write.csv(newdat, "file.csv")
I am looking for a way to rename the columns of several objects with a for loop or other method in R. Ultimately, I want to be able to bind the rows of each Stock object into one large data frame, but cannot due to differing column names. Example below:
AAPL <-
Date AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume AAPL.Adjusted Stock pct_change
2020-05-14 304.51 309.79 301.53 309.54 39732300 309.54 AAPL 0.61
2020-05-15 300.35 307.90 300.21 307.71 41561200 307.71 AAPL -0.59
GOOG <-
Date GOOG.Open GOOG.High GOOG.Low GOOG.Close GOOG.Volume GOOG.Adjusted Stock pct_change
2020-05-14 1335.02 1357.420 1323.910 1356.13 1603100 1356.13 GOOG 0.50
2020-05-15 1350.00 1374.480 1339.000 1373.19 1705700 1373.19 GOOG 1.26
For this example I have 2 objects (AAPL and GOOG), but realistically I would be working with many more. Can I create a for loop to iterate through each object, and rename the 2nd column of each to "Open", 3rd column to "High", 4th column to "Low",.... etc so I can then bind all these objects together?
I already have a column named "Stock", so I do not need the Ticker part of the column name.
Using quantmod we can read a set of stock ticker symbols, clean their names & rbind() into a single data frame.
There are three key features illustrated within this answer, including:
Use of get() to access the objects written by quantmod::getSymbols() once they are loaded into memory.
Use of the symbol names passed into lapply() to add a symbol column to each data frame.
Conversion of the dates stored as row names in the xts objects written by getSymbols() to a data frame column.
First, we'll use getSymbols() to read data from yahoo.com.
library(quantmod)
from.dat <- as.Date("12/02/19",format="%m/%d/%y")
to.dat <- as.Date("12/06/19",format="%m/%d/%y")
theSymbols <- c("AAPL","AXP","BA","CAT","CSCO","CVX","XOM","GS","HD","IBM",
"INTC","JNJ","KO","JPM","MCD","MMM","MRK","MSFT","NKE","PFE","PG",
"TRV","UNH","UTX","VZ","V","WBA","WMT","DIS","DOW")
getSymbols(theSymbols,from=from.dat,to=to.dat,src="yahoo")
# since quantmod::getSymbols() writes named data frames, need to use
# get() with the symbol names to access each data frame
head(get(theSymbols[[1]]))
> head(get(theSymbols[[1]]))
AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume AAPL.Adjusted
2019-12-02 267.27 268.25 263.45 264.16 23621800 262.8231
2019-12-03 258.31 259.53 256.29 259.45 28607600 258.1370
2019-12-04 261.07 263.31 260.68 261.74 16795400 260.4153
2019-12-05 263.79 265.89 262.73 265.58 18606100 264.2359
Having illustrated how to access the symbol objects in the global environment, we'll use lapply() to extract the dates from the row names, clean the column headings, and write the symbol name as a column for each symbol's data object.
# convert to list
symbolData <- lapply(theSymbols,function(x){
y <- as.data.frame(get(x))
colnames(y) <- c("open","high","low","close","volume","adjusted")
y$date <- rownames(y)
y$symbol <- x
y
})
Finally, we convert the list of data frames to a single data frame.
#combine to single data frame
combinedData <- do.call(rbind,symbolData)
rownames(combinedData) <- 1:nrow(combinedData)
...and the output:
> nrow(combinedData)
[1] 120
> head(combinedData)
open high low close volume adjusted date symbol
1 267.27 268.25 263.45 264.16 23621800 262.8231 2019-12-02 AAPL
2 258.31 259.53 256.29 259.45 28607600 258.1370 2019-12-03 AAPL
3 261.07 263.31 260.68 261.74 16795400 260.4153 2019-12-04 AAPL
4 263.79 265.89 262.73 265.58 18606100 264.2359 2019-12-05 AAPL
5 120.31 120.36 117.07 117.26 5538200 116.2095 2019-12-02 AXP
6 116.04 116.75 114.65 116.57 3792300 115.5256 2019-12-03 AXP
>
If you can guarantee the order of these columns this should do it:
for(df in list(AAPL, GOOG))
colnames(df) <- c("Date", "Open", "High", "Low", "Close", "Volume", "Adjusted", "Stock", "pct_change")
With lapply, we can loop over the list and remove the prefix in the column names with sub. This can be done without any external packages
lst1 <- lapply(list(AAPL, GOOG), function(x) {
colnames(x) <- sub(".*\\.", "", colnames(x))
x})
I am trying to download some stocks data but the quantmod functions don't seem to work. For example:
getSymbols.yahoo("F",env= globalenv(), return.class = 'xts',
from = "2017-01-01",
to = Sys.Date())
[1] "F"
The package is upadated, as well as the local date set = Sys.setlocale("LC_TIME", "C"). I also tried with getSymbols.google but it doesn't work neither and to change the return class.
getSymbols() currently (as-of 0.4-10) loads the data into an environment, just like the load() function. In quantmod 0.5-0, it will return the data, like read.table() and most other functions.
If you want getSymbols() to return the data, you can set auto.assign = FALSE.
Data <- getSymbols("F", from = "2017-01-01", to = Sys.Date(), auto.assign = FALSE)
Also note that you should not call getSymbols.yahoo() directly (as it says in ?getSymbols.yahoo).
That's correct. Now if you want to see the historical data just type F:
> head(F)
F.Open F.High F.Low F.Close F.Volume F.Adjusted
2017-01-03 12.20 12.60 12.13 12.59 40510800 12.22555
2017-01-04 12.77 13.27 12.74 13.17 77638100 12.78876
2017-01-05 13.21 13.22 12.63 12.77 75628400 12.40034
2017-01-06 12.80 12.84 12.64 12.76 40315900 12.39063
2017-01-09 12.79 12.86 12.63 12.63 39183400 12.26440
2017-01-10 12.70 13.02 12.66 12.85 58703500 12.47803
I have a text file with close data that I am trying to convert to XTS format.
I am able to call it into R, but cannot figure out a way to convert this data to XTS format. Below is the sample data I am working with.
05/31/2017,32.78,FCOM
05/30/2017,32.72,FCOM
05/26/2017,32.56,FCOM
05/25/2017,32.57,FCOM
05/24/2017,32.47,FCOM
05/31/2017,35.63,FDIS
05/30/2017,35.71,FDIS
05/26/2017,35.67,FDIS
05/25/2017,35.54,FDIS
05/24/2017,35.23,FDIS
05/31/2017,18.17,FENY
05/30/2017,18.26,FENY
05/26/2017,18.53,FENY
05/25/2017,18.51,FENY
05/24/2017,18.90,FENY
05/31/2017,36.52,FHLC
05/30/2017,36.40,FHLC
05/26/2017,36.50,FHLC
05/25/2017,36.62,FHLC
05/24/2017,36.41,FHLC
05/31/2017,34.28,FIDU
05/30/2017,34.34,FIDU
05/26/2017,34.33,FIDU
05/25/2017,34.31,FIDU
05/24/2017,34.17,FIDU
05/31/2017,30.56,FMAT
05/30/2017,30.66,FMAT
05/26/2017,30.68,FMAT
05/25/2017,30.62,FMAT
05/24/2017,30.70,FMAT
05/31/2017,34.26,FNCL
05/30/2017,34.60,FNCL
05/26/2017,34.86,FNCL
05/25/2017,34.90,FNCL
05/24/2017,34.85,FNCL
05/31/2017,23.96,FREL
05/30/2017,23.96,FREL
05/26/2017,24.02,FREL
05/25/2017,24.21,FREL
05/24/2017,24.16,FREL
Thank you in advance for any assistance you can provide me with!
Use the split argument to read.zoo to indicate which column contains the data that should be used to create columns.
x <- read.zoo(text = "05/31/2017,32.78,FCOM
05/30/2017,32.72,FCOM
05/26/2017,32.56,FCOM
05/25/2017,32.57,FCOM
05/24/2017,32.47,FCOM
05/31/2017,35.63,FDIS
05/30/2017,35.71,FDIS
05/26/2017,35.67,FDIS
05/25/2017,35.54,FDIS
05/24/2018,35.23,FDIS
05/31/2017,18.17,FENY
05/30/2017,18.26,FENY
05/26/2017,18.53,FENY
05/25/2017,18.51,FENY
05/24/2017,18.90,FENY
05/31/2017,36.52,FHLC
05/30/2017,36.40,FHLC
05/26/2017,36.50,FHLC
05/25/2017,36.62,FHLC
05/24/2017,36.41,FHLC
05/31/2017,34.28,FIDU
05/30/2017,34.34,FIDU
05/26/2017,34.33,FIDU
05/25/2017,34.31,FIDU
05/24/2017,34.17,FIDU
05/31/2017,30.56,FMAT
05/30/2017,30.66,FMAT
05/26/2017,30.68,FMAT
05/25/2017,30.62,FMAT
05/24/2017,30.70,FMAT
05/31/2017,34.26,FNCL
05/30/2017,34.60,FNCL
05/26/2017,34.86,FNCL
05/25/2017,34.90,FNCL
05/24/2017,34.85,FNCL
05/31/2017,23.96,FREL
05/30/2017,23.96,FREL
05/26/2017,24.02,FREL
05/25/2017,24.21,FREL
05/24/2017,24.16,FREL", sep = ",", format = "%m/%d/%Y", split = 3)
Setting split = 3 tells read.zoo to use the 3rd column in the file to create columns. Then x is a zoo object:
R> x
FCOM FDIS FENY FHLC FIDU FMAT FNCL FREL
2017-05-24 32.47 35.23 18.90 36.41 34.17 30.70 34.85 24.16
2017-05-25 32.57 35.54 18.51 36.62 34.31 30.62 34.90 24.21
2017-05-26 32.56 35.67 18.53 36.50 34.33 30.68 34.86 24.02
2017-05-30 32.72 35.71 18.26 36.40 34.34 30.66 34.60 23.96
2017-05-31 32.78 35.63 18.17 36.52 34.28 30.56 34.26 23.96
You can convert x to xts using x <- as.xts(x).
I am downloading some data using R package tseries,
require('tseries')
tickers<- c('JPM','AAPL','MSFT','FB','GE');
prices = matrix(NA,nrow=40,ncol=6)
startdate<-'2015-02-02'
enddate<-'2015-03-30'# 40 rows dim()
for(i in 1:5){
prices[,i]<-get.hist.quote(
instrument=tickers[i],
start=startdate,
end=enddate,
quote='AdjClose',
provider='yahoo')
}
colnames(prices)<-c('JPM','AAPL','MSFT','FB','GE');
I want to construct a matrix saving the adjclose price and date information, but I don't know how to access the zoo date column, say when I construct a zoo object using get.hist.quote(), I can view the object like this
But when I save them to matrix, the date column is missing
Here Map applied to get.hist.quote will create a zoo object for each ticker. Then we use zoo's multiway merge.zoo to merge them all together creating a final zoo object prices:
prices <- do.call(merge,
Map(get.hist.quote, tickers,
start=startdate,
end=enddate,
quote='AdjClose',
provider='yahoo')
)
I would probably keep all the series in a zoo object. This can be done like in the following code, thereby also avoiding your for-loop etc. You can always convert this object to a matrix by as.matrix() afterwards.
prices <-lapply(tickers, get.hist.quote, start=startdate, end=enddate, quote='AdjClose')
prices <- Reduce(cbind, prices)
names(prices) <- tickers
prices <- as.matrix(prices)
head(prices)
JPM AAPL MSFT FB GE
2015-02-02 55.10 118.16 40.99 74.99 23.99
2015-02-03 56.35 118.18 41.31 75.40 24.25
2015-02-04 56.01 119.09 41.54 75.63 23.94
2015-02-05 56.40 119.94 42.15 75.61 24.28
2015-02-06 57.51 118.93 42.11 74.47 24.30
2015-02-09 57.44 119.72 42.06 74.44 24.42