I want to export a dataset in the MASS package to SPSS for further investigation. I'm looking for the EuStockMarkets data set in the package.
As described in http://www.statmethods.net/input/exportingdata.html, I did:
library(foreign)
write.foreign(EuStockMarkets, "c:/mydata.txt", "c:/mydata.sps", package="SPSS")
I got a text file but the sps file is not a valid SPSS file. I'm really looking for a way to export the dataset to something that a SPSS can open.
As Thomas has mentioned in the comments, write.foreign doesn't generate native SPSS datafiles (.sav). What it does generate is the data in a comma delimited format (the .txt file) and a basic syntax file for reading that data into SPSS (the .sps file). The EuStockMarkets data object class is multivariate time series (mts) so when it's exported the metadata is lost and the resulting .sps file, lacking variable names, throws an error when you try to run it in SPSS. To get around this you can export it as a data frame instead:
write.foreign(as.data.frame(EuStockMarkets), "c:/mydata.txt", "c:/mydata.sps", package="SPSS")
Now you just need to open mydata.sps as a syntax file (NOT as a datafile) in SPSS and run it to read in the datafile.
Rather than exporting it, use the STATS GET R extension command. It will take a specified data frame from an R workspace/dataset and convert it into a Statistics dataset. You need the R Essentials for Statistics and the extension command, which are available via the SPSS Community site (www.ibm.com/developerworks/spssdevcentral)
I'm not trying to answer a question that has been answered. I just think there is something else to complement for other users looking for this.
On your SPSS window, you just need to find the first line of code and edit it. It should be something like this:
"file-name.txt"
You need to find the folder path where you're keeping your file:
"C:\Users\DELL\Google Drive\Folder-With-Your-File"
Then you just need to add this path to your file's name:
"C:\Users\DELL\Google Drive\Folder-With-Your-File\file-name.txt"
Otherwise SPSS will not recognize the .txt file.
Sorry if I'm repeating some information here, I just wanted to make it easier to understand.
I suppose that EuStockMarkets is a (labelled) data frame.
This should work and even keep the variable and value labels:
require(sjlabelled)
write_spss(EuStockMarkets, "mydata.sav")
Or you try rio:
rio::export(EuStockMarkets, "mydata.sav")
Related
I am using openxlsx in order to write the outputs of my data.
I have used the following code to read my data using readxl.
df1=read_excel("C:/my_data.xlsx",skip=2);
Now I want to write the output and keep the original Excel file using any possible package. I have used the following codes, but it does not keep the original Excel file. Can we do it it in R packages?
write.xlsx(df1, 'C:/mydata.xlsx',skip=2)
Given your code, you should nhave two different data files in your working directory:
"my_data.xlsx" (the one that you loaded), and "mydata.xlsx" (the one that you created through R). R shouldn't overwrite your files if you give them different names.
If there's only one file, are you sure you didn't use the same name for both files? If so, then everything should work fine if you give the files different names (e.g. "my_file1.xlsx" and "my_file2.xlsx")!
Also, in general, it's a good idea to give data files an informative name so that you don't accidentally delete/overwrite files that you need. For example, if the original excel data is you raw data, consider naming it "data_raw.xlsx", and make sure that you only read it, and whenever you make some changes to it, save it under a different name (e.g. "data_processed1.xlsx").
You can also save data files in the native R format .rds using the save_rds() function, this is especially helpful if you want to keep special attributes of variables such as factors, etc...
Hope this helps!
I define a DataFrame named data and want to write it into .csv file. I used writetable("result_data.csv", data) but it doesn't work.
This is the dataframe
error details
To write a data frame to a disk you should use the CSV.jl package like this (also make sure that you have write right to the directory you want to save the file on Juliabox):
using CSV
CSV.write("result_data.csv", data)
If this fails then please report back in the comment I will investigate it further.
I got the output file from a spectrometer which is supposed to be a series of decimals numbers. The file looks like this:
™pQH1JHxþFH$ÏFH÷~EHa×BHäBHßdBH.#H²Ï=HL=HŒÚ<Hê‰:HP:Hoõ9H¢Ž6Hº7H¨Y5H ?1H½¶.Hø²0HøŽ2H8æ.H.î,HŒt/H&1H͸0Hí.Hvî,H$ª+HµX+HCý*H·W+H!º+HP+HfØ(Hû'H†Ù'H|U(HQ`)Hn*H
})H'Hó%HÂ%H¶¨&H&H|•&H\
I have been reading a lot without getting to the solution. My silly question is: is that a ENVI or ASCII file? Or? How can I see the numbers I need do to use? I tried some online converters without being successful.
The starting point would be to get these numbers to develop a R code to make graphs. Thanks a lot for your time.
This looks like you opened the binary file of the mass spectrometer. Almost all vendors keep their format a secret. The only way to do this is to export it to an open format. Most vendors supply some kind of data analysis software and there are often export functions present. Most general open data formats are mzXML and mzML.
For converting have a look at the msconvert program from ProteoWizard.
If you have converted the data one of the packages in R where you can start with is XCMS.
In the past I have used the excellent SAScii package in R to read in this type of data: {.dat fixed-column data file + the corresponding .sas "syntax" file}. I want to be quite precise about that because there is no end of ambiguity surrounding phrases like "SAS file". These .dat files contain only integers, and the .sas files specify both the way to parse the columns and the way the integers represent the values in the actual data (this feature is sometimes called the "codebook".) I have found very good data in that format (i.e. in the form of the pair of files {.dat, .sas}) from places like Minnesota Population Center's IPUMS https://usa.ipums.org/usa/, and built up a lot of tools to analyze it using R and SAScii.
Now I have access to SAS itself, and but would still like to re-use some of my tools and techniques. However I can find no reference in SAS to data like that {fixed-column data in .dat, syntax file in .sas}. Has that format been entirely superseded within SAS (perhaps by the SAS7BDAT format)? Or perhaps the {.dat,.sas} format was never used within SAS?? The reason I ask is, now that I have access to SAS and so much data in SAS7BDAT format, I would like to be able to export some of it in {.dat, .sas} format for use with my own tools.
Thanks very much, and cheers - Ed
I don't think this is something built into SAS. You could, however, write such a program pretty easily.
First off, Chris Hemidinger has written something that basically does this (it creates datalines, not .dat file, but that shouldn't be too hard to modify if you know .NET and/or to modify the R module to accept). That is discussed and available here. The title of the post is "Turn your data set into a data step program". This is roughly equivalent to the SQL Server task that creates "Create Table" code out of a table. This would only work in Enterprise Guide, although you should be able to do roughly the same thing in a standalone .NET program.
Second, you can easily write something like this in Base SAS. Creating the datalines is easy, numerous ways to write out to a file.
For a CSV, for example, you can do this.
ods csv file="c:\temp\mydata.csv";
proc print data=mydata;
run;
ods csv close;
If you're going to write a flat file, you might as well make the input/output .sas first - after all it can be almost the same code. You can query dictionary.columns to generate the code, both the input and output code. Create a table with the variable names, lengths, and formats for each variable, then process it in a data step advancing the start variable by the length of each variable (so it moves to the next position after the last one finished). If you need formats for your R project, then proc format cntlout=<datasetname> will generate a dataset that contains those formatted value translations, and you can write that out in whatever format you need as well.
How can I read and write the following file using R ?
https://www.dropbox.com/s/vlnrlxjs7f977zz/3B42_daily.2012.11.23.7.nc
In other words, I would like to read the "3B42_daily.2012.11.23.7.nc" file and write with the same structure that it is written.
Best regards
Package ncdf have functions to do this. You should also read other Q&A on this site tagged with netcdf and r.
Basically to read a netcdf file:
library(ncdf)
a <- open.ncdf('your/path/to/your/file.nc') #that opens a connection to the file
Then function get.var.ncdf helps you extract the data, variable by variable.
The process to write one is described in this Q&A.
The idea is to create dimensions first using dim.def.ncdf then the variables with var.def.ncdf and finally the file itself using create.ncdf.