search for: shivamsingh

Hi, I am relatively new to R. Have scourged the help files and the www but havent been able to get a solution. I have around 250 csv files, one file for each date. They have columns of all types, numeric, string etc. The name of each file is the date in the form of 'yyyymmdd'. There is no column within the file which helps me identify the date on which the file was generated, only the

Hi All, I have a query about time based sequences. I know such questions have been asked a lot on forums, but I couldnt find the exact thing that I was looking for. I want to create a time-based sequence which will mimic the trading window AND would span multiple days. Something like below: "2011-01-03 09:15:00 IST" "2011-01-03 09:15:01 IST" .... .... .... "2011-01-03

Hi All, I am having trouble executing SQL statements on a few dataframes, but the funny thing is that I am able to execute the statement on some other dataframes. To test, I have 2 very small dataframes (6 rows and some columns). One is 'lessliq', the dput is given below. > dput(head(lessliq)) structure(list(V1 = c(50464677L, 50464846L, 50432581L, 50426614L, 50504329L, 50504735L), V2

Hi, I have a query about sqldf, and dates in general. I couldnt find much on the net or on the forums, hence I am here. Here is the issue: I want to write a function that accepts 3 arguments: date1, date2 and a dataframe, say 'df'. Within the function, I want to populate a temp dataframe which essentially contains the output of the query "select * from df where DATE between date1

Hi, I had a query regarding which object, a list or a dataframe, consumes more R memory. Let me clarify this: For example, I have a df of 6 rows and 12 columns, say 'test'. I do object.size() and find it uses 3.3 KB of memory. I run a loop and make a list, say 'testlist', of 6 elements, each element being the above mentioned df 'test'. The size of this list is 19.9 KB,

Dear All, I need to sum a column from another dataframe based on the row values of one dataframe. I am stuck in a loop trying to accomplish it and at current speed it will take more than 80 hours to complete. Needless to say I am looking for a more elegant/quicker solution. Really need some help here. Here is the issue: I have a dataframe CALL (the dput of head is given below) which has close to

Hi All, This question may not belong here, but I asked this on the R-SIG-FINANCE list and so far have not got any reply, so was hoping someone here may help. I have a basic query about TSRV and was hoping you all can shed some light on the issue. I have 22500 records for each day. So if I take the slow frequency as 5 mins I can have 75 subgrids. An estimate of the 5-minute realized volatility