Ms Marija,
Would you happen to know which program created it? If not, you can try the
Unix file command, if you have access to that. -- H
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Too little information to tell. I googled the file name though and pages about
genetics came up... perhaps you should ask in the Bioconductor support area.
On January 31, 2020 3:02:16 PM PST, Ana Marija
wrote:
>Hello,
>
>I have a database DGN-WB_0.5.db is there is a way to explore its
>content
> On Jan 31, 2020, at 1:04 AM, Emmanuel Levy wrote:
>
> Hi,
>
> I'd like to use the Netflix challenge data and just can't figure out how to
> efficiently "scan" the files.
> https://www.kaggle.com/netflix-inc/netflix-prize-data
>
> The files have two types of row, either an *ID* e.g., "1:"
Hello,
I have a database DGN-WB_0.5.db is there is a way to explore its
content in R? I don't know anything about this data base.
Thanks
Ana
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Hi All,
Thanks so much for your inputs, it's so nice to have such a helpful
community -- I wrote some kind of mix between the different replies, I copy
my final code below.
All the best,
Emmanuel
mat = read.csv("~/format_test.csv", fill=TRUE, header=FALSE, as.is=TRUE)
first.col.idx =
On Fri, 31 Jan 2020 18:06:00 +
Ioanna Ioannou wrote:
> I want to extract e.g., the country from all these files. How can i
> add NA for the files for which the country is not mentioned?
I am starting from the beginning, since I don't know what you have
tried and where exactly you are stuck.
It worked, initially I made some mistake.
Thanks a lot. Trying to read basics of R.
Puja
On Fri, Jan 31, 2020 at 1:06 PM pooja sinha wrote:
> Thanks but it gives error "incorrect number of dimensions".
>
>
> Best,
> Puja
>
> On Fri, Jan 31, 2020 at 11:37 AM K. Elo wrote:
>
>> Hi!
>>
>> To
Thanks but it gives error "incorrect number of dimensions".
Best,
Puja
On Fri, Jan 31, 2020 at 11:37 AM K. Elo wrote:
> Hi!
>
> To extract full rows, use:
>
> df[ ( (df$Value>=0.2 & df$Value<=0.4) | df$Value>=0.7 ), ]
>
>
> But it is also a good idea to start reading some introductory
>
Hello everyone,
Once again i am a bit stack. I have over 200 json files with information. I
managed to manipulate them and their format is rather difficult as shown below.
Unfortunately, not all these files contain the same fields. I want to extract
e.g., the country from all these files. How
Hi!
To extract full rows, use:
df[ ( (df$Value>=0.2 & df$Value<=0.4) | df$Value>=0.7 ), ]
But it is also a good idea to start reading some introductory
tutorials. These are basic things you can find in all tutorials :-)
Best,
Kimmo
pe, 2020-01-31 kello 10:50 -0500, pooja sinha kirjoitti:
>
Time to study some tutorials and do your own work, don't you think? There
are many good tutorials on the web.
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On
With the *data.table* package, *R* can use *fread* as follows:
> grab<- function(file)
> {
> fin<- fread(file=file,
> sep=NULL,
> dec=".",
> quote="", nrows=Inf, header=FALSE,
> stringsAsFactors=FALSE, verbose=FALSE,
> col.names=c("record"),
> check.names=FALSE, fill=FALSE,
Thanks for providing the code but I also needed the output sheet in
.csv format with all the four columns corresponding to the value (Chrom,
Start_pos, End_pos & Value ranging from what I specified earlier).
Puja
On Fri, Jan 31, 2020 at 10:23 AM K. Elo wrote:
> Hi!
>
> Oh, sorry, one "s" too
Hi!
Oh, sorry, one "s" too much in my code. Here the correct one:
df$Value[ (df$Value>=0.2 & df$Value<=0.4) | df$Value>=0.7 ]
Best,
Kimmo
pe, 2020-01-31 kello 17:12 +0200, K. Elo kirjoitti:
> Hi!
>
> Let's assume your data is stored in a data frame called 'df'. So this
> code should do the
Hi!
Let's assume your data is stored in a data frame called 'df'. So this
code should do the job:
df$Value[ (df$Value>=0.2 & df$Values<=0.4) | df$Value>=0.7 ]
Best,
Kimmo
pe, 2020-01-31 kello 09:21 -0500, pooja sinha kirjoitti:
> Hi All,
>
> I have a .csv file with four columns (Chrom,
Welcome to R!
You could try using findInterval() which will quickly determine into
which interval your values belong.
# your break points define the intervals
brks <- c( 0.2, 0.4, 0.7)
# make an example data frame
n <- 100
x <- data.frame(
x = seq_len(n),
y = runif(n, min = 0, max = 1))
#
Hi All,
I have a .csv file with four columns (Chrom, Start_pos, End_pos & Value).
The value column range from 0 to 1.0 having more than 2.8 million rows. I
need to write a code from which I can extract the values from 0.2-0.4 &
0.7-1.0. Could anyone help me in writing the code because I am new to
I am sure Rainer's approach is good and I know my R programming is truly
terrible but here's a crude script in base R that does what you want
# rawDat <- readLines(con = "netflix.dat")
fil <- tempfile(fileext = ".dat")
cat("*1:*
value1,value2, value3
value1,value2, value3
value1,value2, value3
I did something similar yesterday…
Use readLine() to read at in and identify the “*1:*, … with a regex. Than you
have your dividers. In a second step, use read.csv(skip = …, Ncollumns = …) to
read the enclosed blocks, and last, combine them accordingly.
This is written without an R
Hi,
I'd like to use the Netflix challenge data and just can't figure out how to
efficiently "scan" the files.
https://www.kaggle.com/netflix-inc/netflix-prize-data
The files have two types of row, either an *ID* e.g., "1:" , "2:", etc. or
3 values associated to each ID:
The format is as
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