I'm trying to open an Excel CSV file within R Studio but I get this error:
Error Is this a valid CSV file? embedded nul in the string: 'C\0a\0m\0p\0a\0g\0n\0e\0_\0N\0o\0C\0a\0r\0a\0v\0a\0g\0g\0i\0o\0_\0C\0o\0s\0t\0o\0>\00'
the file is generated automatically by the Google Ads platform as Excel csv and it works normally with Excel but in order to open it on R Studio I have to convert it as .xlsx
is there a way to bypass this or to convert the file without opening it?
otherwise the script which is based upon this file needs a manual passage to convert the source file
What function are you using to open it? Check your file and see if you have other commas within a column value; this may confuse the function. Also, it is worth trying to use the "Import dataset" option in the environment window within Rstudio. Try to use the readr option and adjust your import options until you have it correct. Check the package RAdwords maybe you can extract your Google Ads information without the CSV exporting step.
I'm using Julia on Macbook and am having trouble importing an excel file to it.
This is what I've used but it won't work.
using XLSX
#set datafile's location
cd("/Users/myname/Desktop/cpsmar.xlsx")
xf = XLSX.readxlsx("cpsmar.xlsx")
How can I fix this?
I have a requirement where I have to import an .xls file which is saved as .*htm, .*html.
How do we load this inside R in a data frame. The data is present in Sheet1 starting from Row Number 5. I have been struggling with this by trying to load it using xlsx package and readxl package. But neither of them worked, because the native format of the file is different.
I can't edit and re-save the file manually as .xlsx, as it cannot be automated.
Also to note, saved it as a .xlsx file and it works fine. But that's not what I need.
Kindly help me with this.
Try the openxlsx package and its function read.xlsx. If that doesn't work, you could programmatically rename the file as described for example here, and then open it using one of these excel packages.
Your file could be in xls format instead of xlsx, have you tried read_xls() function from readxl? Or it could also be in text format, in this case read.table() or fread() from data.tableshould work. The fact that it works after saving the file in xlsx strongly suggests that it is not formatted as an xlsx to begin with.
Hope this helps.
I tried to read doc file using readdoc() but when doc file consist of tables, it will not able read it properly.
Therefore I want to convert doc file to docx file so that I can extract tables using docxtractr package availabe in R.
I want to convert .doc file to .docx file using R code.
I have a set of SAS data sets and I want to open it using Excel or R. I don't have a SAS software with me so i can't use the export option in it. Is there any converter that converts from SAS7BDAT to excel?
Thanks
I help develop the Colectica for Excel addin, which opens SAS data files in Excel. No SAS software or ODBC configurations are required. The addin directly reads the SAS file and then inserts the data and metadata into your worksheet.
Imports SAS .sas7bdat data and column names
Imports SAS .sas7bcat formats and value labels when avalaible
The Excel addin is downloadable from http://www.colectica.com/software/colecticaforexcel
Documentation is available in the user manual.
You could use SAS add in for Microsoft office to open the SAS dataset in Excel. Not sure if it is free though.
http://support.sas.com/software/products/addin/
As Reese suggested you can use - SAS Universal Viewer , its free!!
Here is the link :-
https://support.sas.com/downloads/browse.htm?fil=&cat=74
Or you can download SAS University Edition, which is also free, it is more than just a viewer, you can write and execute programs in here.
http://www.sas.com/en_us/software/university-edition/download-software.html
Here a quick-and-dirty python five-liner to convert a .xpt file to .csv
import pandas as pd
FILE_PATH = "(directory containing file)"
FILE = "ABC" # filename itself (without suffix)
# Note: might need to substitute the column name of the index (in quotes) for "None" here
df = pd.read_sas(FILE_PATH + FILE + '.XPT', index=None)
df.to_csv(FILE_PATH + FILE + '.csv')
Hopefully this might help someone
I came across the same "need" and after some research here and there, I found a nice and easy way with R and the latest version of RStudio (as per 2020 June date - the FREE one). Using it, you can open various formats of files and RStudio generates for you the R script it ran behind. You can use this as a starting point, in order to have the .sas7bdat file opened, and then do the conversion step.
Steps to follow in order to import the file using the RStudio "visual" way: Evironment tab -> Import Dataset -> From SAS...
It will ask you to import the haven library. After the installation you will have a tab with the preview of the data within the file and also the R script ran behind which will look like this:
library(haven)
aux <- read_sas("//PATH_ON_YOUR_MACHINE_TO_FILE/actual_file.sas7bdat", NULL)
View(aux)
Notice the NULL there, it has the purpose of converting empty strings to NULL.
But wait, we also need to convert it to a .csv file in order to have the final job done. For this you simply add below those lines from above the following:
write.csv(aux, "actual_file.csv")
Which will produce within the same folder with the original SAS file, the desired .CSV one. If you want to have ";" as separator instead on "," use write.csv2(aux, "actual_file.csv"). Anyway Strings are enclosed by " " so it should be fine.