concatenating them
together in one step seems to be the most efficient way. One probably
could
design such function, but time spent on the function performing the
task
only once is probably bigger than performing 250*3 reads.
I see inefficiency in writing each column into separate text file and
cop
design such function, but time spent on the function performing the
task
only once is probably bigger than performing 250*3 reads.
I see inefficiency in writing each column into separate text file and
coppying it back to Excel file.
Cheers
Petr
-Original Message-
From: Upton
t; To: PIKAL Petr ; Thomas Subia
> Cc: r-help@r-project.org
> Subject: RE: [R] readxl question
>
> From your example, it appears you are reading in the same excel file for
> each function to get a value. I would look at creating a function that
> extracts what you need from each
Center for Data Farming
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-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of PIKAL Petr
Sent: Wednesday, August 26, 2020 3:50 AM
To: Thomas Subia
Cc: r-help@r-project.org
Subject: Re: [R] readxl question
NPS
now "result.xls" is directly readable with Excel
Cheers
Petr
>
> -Original Message-
> From: R-help On Behalf Of Thomas Subia via
> R-help
> Sent: Saturday, August 22, 2020 6:25 AM
> To: r-help@r-project.org
> Subject: [R] readxl question
>
> Collea
Colleagues,
I have 250 Excel files in a directory. Each of those files has the same
layout. The problem is that the data in each Excel data is not in
rectangular form. I've been using readxl to extract the data which I need.
Each of my metrics are stored in a particular cell. For each metric,
Colleagues,
I have 250 Excel files in a directory. Each of those files has the same
layout. The problem is that the data in each Excel data is not in
rectangular form. I've been using readxl to extract the data which I need.
Each of my metrics are stored in a particular cell. For each metric,
Hi Thomas,
Perhaps this is what you are seeking:
my_read_excel<-function(filename) {
serials<-read_excel(filename,sheet="Flow Data",range=("c6"))
flow.data<-read_excel(filename,sheet="Flow Data",range=("c22:c70"))
dates<-read_excel(filename,sheet="Flow Data",range=("h14"))
Colleagues,
I am using readxl to extract a serial number and its associated data using the
following code.
library(readxl)
files <- list.files(pattern="*.xls", full.names = FALSE)
serials <- lapply(files, read_excel, sheet="Flow Data", range=("c6"))
flow.datum <- lapply(files, read_excel,
On Thu, 5 Dec 2019 15:39:56 +
Thomas Subia wrote:
> date <- lapply(files, read_excel, sheet="Sheet1", range=("B5"))
> date_df <- as.data.frame(date)
> trans_date <-t(date_df)
> mydates <- list(trans_date)
This feels a bit excessive for what looks like a one-dimensional string
vector. Why is
Colleagues,
I'm trying to extract a cell from all Excel files in a directory.
library(readxl)
files <- list.files(pattern="*.xls", full.names = FALSE)
date <- lapply(files, read_excel, sheet="Sheet1", range=("B5"))
date_df <- as.data.frame(date)
trans_date <-t(date_df)
mydates <-
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