xts

问题 I have the server logs for a months worth of traffic. Partial example below "UploadDateGMT","UserFileSize","TotalBusinessUnits" "2012-01-01 00:00:38","1223","1" "2012-01-01 00:01:16","1302","1" "2012-01-01 00:08:10","1302","1" I would like to convert this into a data set where I have a count of how many bytes of submissions there were in each five minute window on a rolling basis. (i.e. 0-5, 1-6, 2-7, etc.) From this, I could extract maximum load, 95% load, make pretty graphs of load, etc.

问题 I have a data.frame like below soc_sec group_count total_creds group_start group_end (chr) (int) (dbl) (date) (date) 1 AA2105480 5 14.0 2005-01-09 2005-05-16 2 AA2105480 7 17.0 2004-08-26 2004-12-10 3 AB4378973 1 0.0 2004-01-21 2004-05-07 4 AB4990257 2 1.0 2014-09-01 2014-12-14 5 AB7777777 5 12.0 2004-01-21 2005-03-22 6 AB7777777 6 15.0 2004-08-26 2004-12-10 7 AB7777777 5 15.0 2005-01-09 2005-05-12 8 AC4285291 2 3.0 2014-09-01 2014-12-14 9 AC4285291 1 3.0 2015-01-12 2015-04-15 10 AC6039874 9

问题 I'm using the quantmod package. I've got a vector of tickers like this : c("AAPL","GOOG","IBM","GS","AMZN","GE") and I want to create a function to calculate the EBIT margin of a stock (= operating income / total revenue). So for a given stock, I use the following piece of code which only works for GE (provided a ".f" is added a the end of the ticker) : require(quantmod) getFinancials("GE",period="A") ebit.margin <- function(stock.ticker.f){ return(stock.ticker$IS$A["Operating Income",]/stock

问题 How do I use the apply family of functions, say apply.daily to a multivariate XTS? So for example: Time,a,b ... 2012-02-11 16:21:24 4.7258 7.7258 2012-02-11 16:26:25 4.9096 12.3796 2012-02-11 16:31:25 4.7904 2.2204 ... How would I use apply.daily and mean to the entire matrix by column. So the result would be a single time stamp for the day, the mean of a for the next column, and the mean of b for the column after that. I would like to do this for arbitrary number columns (the amount of

问题 I'm using xtsExtra to plot two xts objects. Consider the following call to plot.xts: plot.xts(merge(a,b),screens=c(1,2)) which is used to plot the xts objects a and b in two separate panels. How do I control the spacing of the y-axes? Specifically, I'm running into the problem where the y-axis labels come too close or even overlap. Ideally, I would like to specify a minimum padding which is to be maintained between the two y-axis labels. Any help is appreciated! EDIT: A reproducible example:

问题 Hi I'm looking to roll up minutely data in a data.table to 5 minutely (or 10 minutely) horizon. I know this is easily done via using xts and the to.minutes5 function, but I prefer not to use xts in this instance as the data set is rather large. Is there an easy way to do this in data.table ? Data example : In this example the period between 21.30 to 21.34 (both inclusive) would have just one row with t = 21.30, open = 0.88703 , high = 0.88799 , low = 0.88702 , close = 0.88798, volume = 43

问题 How do I subset an xts object to only include weekdays (Mon-Fri, with Saturday and Sunday excluded)? 回答1: Here's what I'd do: library(xts) data(sample_matrix) sample.xts <- as.xts(sample_matrix, descr='my new xts object') x <- sample.xts['2007'] x[!weekdays(index(x)) %in% c("Saturday", "Sunday")] EDIT : Joshua Ulrich in comments points out a better solution using .indexwday() , one of a family of built-in accessor functions for extracting pieces of the index of xts class objects. Also, like

问题 I've written a function to grab and parse news data from Google for a given stock symbol, but I'm sure there are ways it could be improved. For starters, my function returns an object in the GMT timezone, rather than the user's current timezone, and it fails if passed a number greater than 299 (probably because google only returns 300 stories per stock). This is somewhat in response to my own question on stack overflow, and relies heavily on this blog post. tl;dr: how can I improve this

问题 library(xts) data <- data.frame(year_week = c("2016-46", "2016-47", "2016-48"), satisfaction = c(0.25, 0.45, 0.58)) data = xts(data[-1], order.by = as.POSIXct(data$year_week, format = "%Y-%W")) I want to create an xts object from the data.frame data where the dates keep the format year-week. When I am running the code the columns take the form 2016-12-05 which is incorrect and far from what I am trying to achieve. 回答1: This is a variant on a quasi-FAQ on 'by can one not parse year and month

问题 I have a multi-day XTS object, and I am trying to create an indicator that once true, remains true for the rest of the day. The approach I am trying (but its not working) is combining the na.locf function with the apply daily: output <- apply.daily(x, na.locf) Reproducible code: y <- as.xts(c(NA,NA,1,NA,NA,NA,NA,NA,NA),as.POSIXct(c( "2010-01-05 00:00:00", "2010-01-05 00:04:00", "2010-01-05 00:08:00", "2010-01-05 00:12:00", "2010-01-05 00:16:00", "2010-01-05 00:20:00", "2010-01-06 00:00:00",