I have to convert .xls or .xlxs file to .csv file without using plugins or tools using Unix Command
Is their any way to do this ?
I Tried to do like this below ...But not working
Change the characterSet code from .xls file to UTF-8 encoding
Then create file again with extension change
cp temp.xls temp.csv
It is possible, but you need to realise that an *.xls file is a zipped directory structure (just unzip such a file, using Winzip or 7-zip). The unzipping can also be done using UNIX commands.
But what then? The directory structure is quite complicated to understand, and in order to create a script or a program which can do this (without using any external tools) is a tremendous work, so I'd propose you, either to use external tools anyway, or to make sure the files you receive already are CSV format.
Related
i'am currently trying to unzip some specific files within a ARR file. This ARR file is within a tar.gz file.
Is it possible to unzip these files without a intermediate step/One liner. Its important that the first tar.gz will not be unpacked.
Thanks!
you can try something like:
gzip -dc input_file.tar.gz|tar xf - path/to/file/you/want/to/extract
This decompress and untar the archive in memory and have advantage of run faster.
I can't get write.csv or write.table to work in the r editor of BlueSky Statistics.
I usually just use this format in RStudio and it works perfectly.
write.csv(df, "zzz.csv")
Any hints?"
The default install location for BlueSky Statistics is 'C:\Program Files', where by default, there is no write permission (for creating or deleting files). Also, saving a file in the install location is not safe, as the file may get lost/deleted when the application is uninstalled. So it is always good to save your file(s) in your own folder(s) where you also have write permission.
In short, try to provide a writable location/path in write.csv() or other similar functions/commands.
See example below:
To save your file to the Desktop folder.
write.csv(df, "C:/Users/<YourUsername>/Desktop/zzz.csv")
Note: use forward slash(/) as a path separator.
On a mac using iCloud file optimization, large files that are seldom used are uploaded to iCloud and only a small pointer file is left. When I look for the file in Finder, I see the file name and to the left is an icon that indicates that the file is in the cloud. To access the file, I click on the icon and the file is downloaded. With the file.exist command, R returns FALSE for the existence of the file. But after some research I found that the file link is stored in a directory below ~/Library/Mobile\ Documents/com~apple~CloudDocsand the file name is changed to xxx.icloud where xxx is the original file name.
Here's an example of the path to a a directory that holds a .icloud file from a shell in my mac
/Users/gcn/Library/Mobile Documents/com~apple~CloudDocs/Documents/workspace/nutmod/data-raw/NutrientData
I can query for the existence of the file with exists(xxx.icloud). But how do I tell my mac to download the iCloud file and then read it in? Using something like read.table or read.csv doesn't work because the pointer file is not csv.
You can read a csv file directly from a iCloud folder on the Mac by using the path to that folder. Get the path by finding it in the finder. Then right click on the filename at the bottom of the finder window where it shows all the folders leading to the file and choose: Copy "YourFile" as Pathname.
That path will look something like this:
"/Users/NAME/Library/Mobile
Documents/com~apple~CloudDoc/Docs/YourFile.csv"
Use that in your read code:
iCloudDat <- read_csv("/Users/NAME/Library/Mobile Documents/com~apple~CloudDocs/Documents/YourFileName.csv")
That should work.
If the extension isn't .txt or .csv read.table and read.csv won't work.
you have to download the file and extract the tables to a readable format.
you can download the file using download.file() which is is the utils basic library.
I have couple of .csv files in C:\Users\USER_NAME\Documents which are more than 2 GB in size. I want to use Apache Spark to read the data out of them in R. I am using Microsoft R Open 3.3.1 with Spark 2.0.1.
I am stuck with reading the .csv files with the function spark_read_csv(...) defined in Sparklyr package. It is asking for a file path which starts with file://. I want to know the proper file path for my case starting with file:// and ends with the file name which are in .../Documents directory.
I had a similar problem. In my case it was necessary for the .csv file to be put into the hdfs file system before calling it with spark_read_csv.
I think you probably have a similar problem.
If your cluster is also running with hdfs you need to use:
hdfs dfs -put
Best,
Felix
I have a number of zip files located in a single folder eg:
file1.gz
file2.gz
file3.gz
file4.gz
I'm looking for a way of automatically unzipping these using a batch job to a similarly named folder structure so for example the contents of file1.gz will drop into a folder named file1.
I have been told that 7zip would address my issue but can't figure out how to go about it.
Any help is greatly appreciated.
Which OS are you using? This is something you'd do using the shell's capabilities, you could write
for A in *.gz ; do gunzip $A ; done
I'm using gunzip here, because .gz is actually gzip, But you can use the 7zip CLI tool as well, of course. If you're on Windows, then I recommend installing a real shell (the standard cmd.exe can not really be considered a shell IMHO).