with the help of below code, I am able to get stocks information on a daily basis. But is there a way to get it on a minute basis. Please help
symbols <- c("GODREJIND.NS", "ASHOKLEY.NS")
sd <- as.Date("2019-10-25")
ed <- as.Date("2019-10-31")
tq_get(symbols,
from = sd,
to = ed )
In your data if date is "YYYY-MM-dd HH:MM:SS" format then you can extract minutewise data using below code.
df$MINUTES_sd <- minutes(df$sd)
df$MINUTES_ed <- minutes(df$ed)
Similarly you can extract year,month,day,hour from data to further analysis of your data set.
For example:
df <- data.frame(symbol=c("GODREJIND.NS", "ASHOKLEY.NS"),sd="2019-10-
25",ed='2019-10-31')
df$YEAR_sd <- year(df$sd)
df$MONTH_sd <- month(df$sd)
df$DAY_sd <- day(df$sd)
df$YEAR_ed <- year(df$ed)
df$MONTH_ed <- month(df$ed)
df$DAY_ed <- day(df$ed)
Related
enter image description hereI try to export the data (which I got by coding from Yahoo). I can export data, but the date part does not go through, only the value part goes through. How can I export the date and value together to excel.
#Code:
library(tseries)
library(prophet)
library(tidyverse)
library(writexl)
library(readxl)
#determine date
start = "2013-01-01"
end = "2021-05-25"
#get the data from sources
TL <- get.hist.quote(instrument = "TRYUSD=X",
start = start,
end = end,
quote = "Close",
compression = "d")
#change the format of the dataset
y <- data.frame(TL)
#convert dataframe to excel document
write_xlsx(y,"C:/Users/hay/OneDrive/Desktop/Turkish Lira Forecast/TL.xlsx")#Load the dataset
#upload the dataset from excel file
bitcoin <- read_excel("C:/Users/hay/OneDrive/Desktop/bitcoin.xlsx")
View(bitcoin)
#call the prophet function to fit the model
model <- prophet(TL)
future <- make_future_dataframe(model, periods = 365)
tail(future)
#forecast
forecast <- predict(model, future)
tail(forecast[c('ds', 'yhat', 'yhat_lower', 'yhat_upper')])
#plot the model estimates
dyplot.prophet(model, forecast)
prophet_plot_components(model, forecast)
We can use
library(dplyr)
library(tibble)
y %>%
rownames_to_column('Date') %>%
writexl::write_xlsx("data.xlsx")
The date part can be extracted from the rownames -
y$Date <- rownames(y)
writexl::write_xlsx(y,"data.xlsx")
I am trying to complete a problem that pulls from two data sets that need to be combined into one data set. To get to this point, I need to rbind both data sets by the year-month information. Unfortunately, the first data set needs to be tallied by year-month info, and I can't seem to figure out how to change the date so I can have month-year info rather than month-day-year info.
This is data on avalanches and I need to write code totally the number of avalanches each moth for the Snow Season, defined as Dec-Mar. How do I do that?
I keep trying to convert the format of the date to month-year but after I change it with
as.Date(avalancheslc$Date, format="%y-%m")
all the values for Date turn to NA's....help!
# write the webscraper
library(XML)
library(RCurl)
avalanche<-data.frame()
avalanche.url<-"https://utahavalanchecenter.org/observations?page="
all.pages<-0:202
for(page in all.pages){
this.url<-paste(avalanche.url, page, sep=" ")
this.webpage<-htmlParse(getURL(this.url))
thispage.avalanche<-readHTMLTable(this.webpage, which=1, header=T)
avalanche<-rbind(avalanche,thispage.avalanche)
}
# subset the data to the Salt Lake Region
avalancheslc<-subset(avalanche, Region=="Salt Lake")
str(avalancheslc)
avalancheslc$monthyear<-format(as.Date(avalancheslc$Date),"%Y-%m")
# How can I tally the number of avalanches?
The final output of my dataset should be something like:
date avalanches
2000-1 18
2000-2 4
2000-3 10
2000-12 12
2001-1 52
This should work (I tried it on only 1 page, not all 203). Note the use of the option stringsAsFactors = F in the readHTMLTable function, and the need to add names because 1 column does not automatically get one.
library(XML)
library(RCurl)
library(dplyr)
avalanche <- data.frame()
avalanche.url <- "https://utahavalanchecenter.org/observations?page="
all.pages <- 0:202
for(page in all.pages){
this.url <- paste(avalanche.url, page, sep=" ")
this.webpage <- htmlParse(getURL(this.url))
thispage.avalanche <- readHTMLTable(this.webpage, which = 1, header = T,
stringsAsFactors = F)
names(thispage.avalanche) <- c('Date','Region','Location','Observer')
avalanche <- rbind(avalanche,thispage.avalanche)
}
avalancheslc <- subset(avalanche, Region == "Salt Lake")
str(avalancheslc)
avalancheslc <- mutate(avalancheslc, Date = as.Date(Date, format = "%m/%d/%Y"),
monthyear = paste(year(Date), month(Date), sep = "-"))
it is possible to use the package dygraphs with my data in the format day:
Day KP1 KP2 KP3
02.01.2007 12345 54564 5156156
03.01.2007
I have tried a lot to convert the day to format for dygraphs, but it doesn't work. For example this one:
Data$Day <- strptime(myData2[,1],format="%d.%m.%Y")
Data <- xts(Data[,1], order.by = myData[,1])
My question is: Is it possible to use dygraphs for data which is in the day-format?
Thank a. Greets R007
Are you looking for this:
Data <- read.table(text="
Day KP1 KP2 KP3
02.01.2007 12345 54564 5156156
03.01.2007 10346 50565 5156140
04.01.2007 9346 44565 5156140",
header = TRUE)
Data$Day <- strptime(Data[,1],format="%d.%m.%Y")
Data <- xts(Data[,2:4], order.by = Data[,1])
dygraph(data=Data)
I would like to download daily data from yahoo for the S&P 500, the DJIA, and 30-year T-Bonds, map the data to the proper time zone, and merge them with my own data. I have several questions.
My first problem is getting the tickers right. From yahoo's website, it looks like the tickers are: ^GSPC, ^DJI, and ^TYX. However, ^DJI fails. Any idea why?
My second problem is that I would like to constrain the time zone to GMT (I would like to ensure that all my data is on the same clock, GMT seems like a neutral choice), but I couldn' get it to work.
My third problem is that I would like to merge the yahoo data with my own data, obtained by other means and available in a different format. It is also daily data.
Here is my attempt at constraining the data to the GMT time zone. Executed at the top of my R script.
Sys.setenv(TZ = "GMT")
# > Sys.getenv("TZ")
# [1] "GMT"
# the TZ variable is properly set
# but does not affect the time zone in zoo objects, why?
Here is my code to get the yahoo data:
library("tseries")
library("xts")
date.start <- "1999-12-31"
date.end <- "2013-01-01"
# tickers <- c("GSPC","TYX","DJI")
# DJI Fails, why?
# http://finance.yahoo.com/q?s=%5EDJI
tickers <- c("GSPC","TYX") # proceed without DJI
z <- zoo()
index(z) <- as.Date(format(time(z)),tz="")
for ( i in 1:length(tickers) )
{
cat("Downloading ", i, " out of ", length(tickers) , "\n")
x <- try(get.hist.quote(
instrument = paste0("^",tickers[i])
, start = date.start
, end = date.end
, quote = "AdjClose"
, provider = "yahoo"
, origin = "1970-01-01"
, compression = "d"
, retclass = "zoo"
, quiet = FALSE )
, silent = FALSE )
print(x[1:4]) # check that it's not empty
colnames(x) <- tickers[i]
z <- try( merge(z,x), silent = TRUE )
}
Here is the dput(head(df)) of my dataset:
df <- structure(list(A = c(-0.011489000171423, -0.00020300000323914,
0.0430639982223511, 0.0201549995690584, 0.0372899994254112, -0.0183669999241829
), B = c(0.00110999995376915, -0.000153000000864267, 0.0497750006616116,
0.0337960012257099, 0.014121999964118, 0.0127800004556775), date = c(9861,
9862, 9863, 9866, 9867, 9868)), .Names = c("A", "B", "date"
), row.names = c("0001-01-01", "0002-01-01", "0003-01-01", "0004-01-01",
"0005-01-01", "0006-01-01"), class = "data.frame")
I'd like to merge the data in df with the data in z. I can't seem to get it to work.
I am new to R and very much open to your advice about efficiency, best practice, etc.. Thanks.
EDIT: SOLUTIONS
On the first problem: following GSee's suggestions, the Dow Jones Industrial Average data may be downloaded with the quantmod package: thus, instead of the "^DJI" ticker, which is no longer available from yahoo, use the "DJIA" ticker. Note that there is no caret in the "DJIA" ticker.
On the second problem, Joshua Ulrich points out in the comments that "Dates don't have timezones because days don't have a time component."
On the third problem: The data frame appears to have corrupted dates, as pointed out by agstudy in the comments.
My solutions rely on the quantmod package and the attached zoo/xts packages:
library(quantmod)
Here is the code I have used to get proper dates from my csv file:
toDate <- function(x){ as.Date(as.character(x), format("%Y%m%d")) }
dtz <- read.zoo("myData.csv"
, header = TRUE
, sep = ","
, FUN = toDate
)
dtx <- as.xts(dtz)
The dates in the csv file were stored in a single column in the format "19861231". The key to getting correct dates was to wrap the date in "as.character()". Part of this code was inspired from R - Stock market data from csv to xts. I also found the zoo/xts manuals helpful.
I then extract the date range from this dataset:
date.start <- start(dtx)
date.end <- end(dtx)
I will use those dates with quantmod's getSymbols function so that the other data I download will cover the same period.
Here is the code I have used to get all three tickers.
tickers <- c("^GSPC","^TYX","DJIA")
data <- new.env() # the data environment will store the data
do.call(cbind, lapply( tickers
, getSymbols
, from = date.start
, to = date.end
, env = data # data saved inside an environment
)
)
ls(data) # see what's inside the data environment
data$GSPC # access a particular ticker
Also note, as GSee pointed out in the comments, that the option auto.assign=FALSE cannot be used in conjunction with the option env=data (otherwise the download fails).
A big thank you for your help.
Yahoo doesn't provide historical data for ^DJI. Currently, it looks like you can get the same data by using the ticker "DJIA", but your mileage may vary.
It does work in this case because you're only dealing with Dates
the df object your provided is yearly data beginning in the year 0001. So, that's probably not what you wanted.
Here's how I would fetch and merge those series (or use an environment and only make one call to getSymbols)
library(quantmod)
do.call(cbind, lapply(c("^GSPC", "^TYX"), getSymbols, auto.assign=FALSE))
This is a newbie question in R. I am downloading yahoo finance monthly stock price data using R where the ticker names are read from a text file. I am using a loop to read the ticker names to download the data and putting them in a list. My problem is some ticker names may not be correct thus my code stops when it encounters this case. I want the following.
skip the ticker name if it is not correct.
Each element in the list is a dataframe. I want the ticker names to be appended to variable names in element dataframes.
I need an efficient way to create a dataframe that has the closing prices as variables.
Here is the sample code for the simplified version of my problem.
library(tseries)
tckk <- c("MSFT", "C", "VIA/B", "MMM") # ticker names defined
numtk <- length(tckk);
ustart <- "2000-12-30";
uend <- "2007-12-30" # start and end date
all_dat <- list(); # empty list to fill in the data
for(i in 1:numtk)
{
all_dat[[i]] <- xxx <- get.hist.quote(instrument = tckk[i], start=ustart, end=uend, quote = c("Open", "High", "Low", "Close"), provider = "yahoo", compression = "m")
}
The code stops at the third entry but I want to skip this ticker and move on to "MMM". I have heard about Trycatch() function but do not know how to use it.
As per question 2, I want the variable names for the first element of the list to be "MSFTopen", "MSFThigh", "MSFTlow", and "MSFTclose". Is there a better to way to do it apart from using a combination of loop and paste() function.
Finally, for question 3, I need a dataframe with three columns corresponding to closing prices. Again, I am trying to avoid a loop here.
Thank you.
Your best bet is to use quantmod and store the results as a time series (in this case, it will be xts):
library(quantmod)
library(plyr)
symbols <- c("MSFT","C","VIA/B","MMM")
#1
l_ply(symbols, function(sym) try(getSymbols(sym)))
symbols <- symbols[symbols %in% ls()]
#2
sym.list <- llply(symbols, get)
#3
data <- xts()
for(i in seq_along(symbols)) {
symbol <- symbols[i]
data <- merge(data, get(symbol)[,paste(symbol, "Close", sep=".")])
}
This also a little late...If you want to grab data with just R's base functions without dealing with any add-on packages, just use the function read.csv(URL), where the URL is a string pointing to the right place at Yahoo. The data will be pulled in as a dataframe, and you will need to convert the 'Date' from a string to a Date type in order for any plots to look nice. Simple code snippet is below.
URL <- "http://ichart.finance.yahoo.com/table.csv?s=SPY"
dat <- read.csv(URL)
dat$Date <- as.Date(dat$Date, "%Y-%m-%d")
Using R's base functions may give you more control over the data manipulation.
I'm a little late to the party, but I think this will be very helpful to other late comers.
The stockSymbols function in TTR fetches instrument symbols from nasdaq.com, and adjusts the symbols to be compatible with Yahoo! Finance. It currently returns ~6,500 symbols for AMEX, NYSE, and NASDAQ. You could also take a look at the code in stockSymbols that adjusts tickers to be compatible with Yahoo! Finance to possibly adjust some of the tickers in your file.
NOTE: stockSymbols in the version of TTR on CRAN is broken due to a change on nasdaq.com, but it is fixed in the R-forge version of TTR.
I do it like this, because I need to have the historic pricelist and a daily update file in order to run other packages:
library(fImport)
fecha1<-"03/01/2009"
fecha2<-"02/02/2010"
Sys.time()
y <- format(Sys.time(), "%y")
m <- format(Sys.time(), "%m")
d <- format(Sys.time(), "%d")
fecha3 <- paste(c(m,"/",d,"/","20",y), collapse="")
write.table(yahooSeries("GCI", from=fecha1, to=fecha2), file = "GCI.txt", sep="\t", quote = FALSE, eol="\r\n", row.names = TRUE)
write.table(yahooSeries("GCI", from=fecha2, to=fecha3), file = "GCIupdate.txt", sep="\t", quote = FALSE, eol="\r\n", row.names = TRUE)
GCI <- read.table("GCI.txt")
GCI1 <- read.table("GCIupdate.txt")
GCI <- rbind(GCI1, GCI)
GCI <- unique(GCI)
write.table(GCI, file = "GCI.txt", sep="\t", quote = FALSE, eol="\r\n", row.names = TRUE)
If your ultimate goal is to get the data.frame of three columns of closing prices, then the new package tidyquant may be better suited for this.
library(tidyquant)
symbols <- c("MSFT", "C", "VIA/B", "MMM")
# Download data in tidy format.
# Will remove VIA/B and warn you.
data <- tq_get(symbols)
# Ticker symbols as column names for closing prices
data %>%
select(.symbol, date, close) %>%
spread(key = .symbol, value = close)
This will scale to any number of stocks, so the file of 1000 tickers should work just fine!
Slightly modified from the above solutions... (thanks Shane and Stotastic)
symbols <- c("MSFT", "C", "MMM")
# 1. retrieve data
for(i in seq_along(symbols)) {
URL <- paste0("http://ichart.finance.yahoo.com/table.csv?s=", symbols[i])
dat <- read.csv(URL)
dat$Date <- as.Date(dat$Date, "%Y-%m-%d")
assign(paste0(symbols[i]," _data"), dat)
dat <- NULL
}
Unfortunately, URL "ichart.finance.yahoo.com" is dead and not working now. As I know, Yahoo closed it and it seems it will not be opened.
Several days ago I found nice alternative (https://eodhistoricaldata.com/) with an API very similar to Yahoo Finance.
Basically, for R-script described above you just need to change this part:
URL <- paste0("ichart.finance.yahoo.com/table.csv?s=", symbols[i])
to this:
URL <- paste0("eodhistoricaldata.com/api/table.csv?s=", symbols[i])
Then add an API key and it will work in the same way as before. I saved a lot of time for my R-scripts on it.
Maybe give the BatchGetSymbols library a try. What I like about it over quantmod is that you can specify a time period for your data.
library(BatchGetSymbols)
# set dates
first.date <- Sys.Date() - 60
last.date <- Sys.Date()
freq.data <- 'daily'
# set tickers
tickers <- c('FB','MMM','PETR4.SA','abcdef')
l.out <- BatchGetSymbols(tickers = tickers,
first.date = first.date,
last.date = last.date,
freq.data = freq.data,
cache.folder = file.path(tempdir(),
'BGS_Cache') ) # cache in tempdir()