Hi there,
Does it exist where R can convert a numeric date (20090101) to a "proper"
date format? (Ideally dd-mm-)
Original data (in this case) is in .DAT format. I read the multi-column
data with the read.fwf function, where I specified the column width for the
eight digit date (example abo
Hi again,
Thanks for the responses. The latter solution does the trick!
I had tinkered around the numeric -> character route & tried as.Date a few
different ways, but needed guidance to the bullseye.
Thanks again!
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Hi there,
I wish to read a 9.6GB .DAT file into R (64-bit R on 64-bit Windows machine)
- to then delete a substantial number of rows & then convert to a .csv file.
Upon the first attempt the computer crashed (at some point last night).
I'm rerunning this now & am closely monitoring Processor/CPU/
Hi Jeff & Steve,
Thanks for your responses. After seven hours R/machine ran out of memory
(and thus ended). Currently the machine has 4GB RAM. I'm looking to
install more RAM tomorrow.
I will look into SQLLite3; thanks!
I've read that SQL would be a great program for data of this size (read-in
Hi Barry,
"You could do a similar thing in R by opening a text connection to
your file and reading one line at a time, writing the modified or
selected lines to a new file."
Great! I'm aware of this existing, but don't know the commands for R. I
have a variable [560,1] to use to pare down the
Hi Sarah,
Thanks for the SQL info! I'll look into these straightaway, along with the
notion of opening a text connection.
Thanks again!
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Hi there,
I am having trouble subsetting a data frame by a conditional via one column
(of many).
I read the file into R through "read.fwf," where I specified column widths.
Original data is .DAT. I then utilized "names" function to read in column
headings.
For one column, PRVDR_NUM, I wish to f
Hi Michael,
Thanks so much for your detailed reply!
I gained a better understanding of the read.fwf function, along with
ensuring I better note how these read-in functions convert variables, etc.
As well, your tip on removing "format" while converting the PRVDR_NUM
variable to numeric (from fac
Hi there,
I wish to merge a common variable between a list and a data.frame & return
rows via the data.frame where there is NO match. Here are some details:
The list, where the variable/col.name = CLAIM_NO
CLAIM_NO
20
83
1440
4439
7002
...
> dim(hrc78_clm_no)
[1] 66781
The data.frame, where
Hi Steve,
Thanks for replying. Here's a small piece of the data.frame:
> bestPartAreadmin[1:5,1:6]
DESY_SORT_KEY PRVDR_NUM CLM_THRU_DT CLAIM_NO
NCH_NEAR_LINE_REC_IDEN_CD NCH_CLM_TYPE_CD
1 10193 290003 20090323 20
Hi again,
I tried the sample code like this:
> merged_clmno <- subset(bestPartAreadmin, !CLAIM_NO %in% hrc78_clm_no)
> dim(merged_clmno)
[1] 1306893
Note that:
> dim(bestPartAreadmin)
[1] 1306893
So, no change between the original data.frame (bestPartAreadmin) & the
(should be) less-row
Hi there,
Thanks for your responses. I haven't used/heard of dput() before. I'm
looking it up & understanding how it works.
Thanks!
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Hi there,
I've tried the noted solutions:
"If you do `no <- unlist(hrc_78_clm_no`, do you get a character vector
of claim numbers you want to exclude? If so, then `subset(whatever,
!CLAIM_NO %in% no)` should work."
I converted the CLAIM_NO list to a character, with
> hrc78_clmno_char <- format
Hi again,
Petr, your solution worked!
Thanks everyone for your input. I'll look more into "setdiff."
Cheers!
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