I have been mainly working with .xlsb files(binary file type of xlsx) which I would like to read/write using R. Could you please let me know if there is any package that is available for this or do I need to create package on my own?
RODBC did not work too.
Try the excel.link package. The xl.read.file function allows rectangular data sets to be read-in, though there are other options available.
You also need to (install and) call the RDCOMClient package before running the first excel.link function.
e.g.,
read_xlsb <- function(x){
require("RDCOMClient")
message(paste0("Reading ", x, "...\n"))
df <- excel.link::xl.read.file(filename = x, header = TRUE,
xl.sheet = Worksheet_name)
df$filename <- x
df <- as.data.frame(df)
return(df)
}
The only annoynce I've found is that I can't override Excel's "save on close" functionality so these pop-ups need to be closed by hand.
BTW I think excel.link only works on Windows machines.
I have a dataset of a weighted network which has a graphml format. I used below function to read it in R using "igraph" package, but it did not get the data's weight. Any idea to help?
net1<-read.graph("text.graphml", format = "graphml")
Based on http://igraph.org/r/doc/read_graph.html, you might like to change it to
net1<-read.graph("text.graphml", format = "gml")
I have a data frame (panel form) in R with 194498 rows and 7 columns. I want to write it to an Excel file (.xlsx) using function res <- write.xlsx(df, output) but R goes in the coma (keeps showing stop sign on the top left of console) without making any change in the targeted file(output). Finally shows following:
Error in .jcheck(silent = FALSE) :
Java Exception <no description because toString() failed>.jcall(row[[ir]], "Lorg/apache/poi/ss/usermodel/Cell;", "createCell", as.integer(colIndex[ic] - 1))<S4 object of class "jobjRef">
I have loaded readxl and xlsx packages. Please suggest to fix it. Thanks.
Install and load package named 'WriteXLS' and try writing out your R object using function WriteXLS(). Make sure your R object is written in quotes like the one below "data".
# Store your data with 194498 rows and 7 columns in a data frame named 'data'
# Install package named WriteXLS
install.packages("WriteXLS")
# Loading package
library(WriteXLS)
# Writing out R object 'data' in an Excel file created namely data.xlsx
WriteXLS("data",ExcelFileName="data.xlsx",row.names=F,col.names=T)
Hope this helped.
This does not answer your question, but might be a solution to your problem.
Could save the file as a CSV instead like so:
write.csv(df , "df.csv")
open the CSV and then save as an Excel file.
I gave up on trying to import/export Excel files with R because of hassles like this.
In addition to Pete's answer I wouldn't recommend write.csv because it takes or can take minutes to load. I used fwrite() (from data.table library) and it did the same thing in about 1-2 secs.
The post author asked about large files. I dealt with a table about 2,3 million rows long and write.data (and frwrite) aren't able to write more than about 1 million rows. It just cuts the data away. So instead use write.table(Data, file="Data.txt"). You can open it in Excel and split the one column by your delimiter (use argument sep) and voila!
Thank you in advance for your're help. I am using R to analyse some data that is initially created in Matlab. I am using the package "R.Matlab" and it is fantastic for 1 file, but I am struggling to import multiple files.
The working script for a single file is as follows...
install.packages("R.matlab")
library(R.matlab)
x<-("folder_of_files")
path <- system.file("/home/ashley/Desktop/Save/2D Stream", package="R.matlab")
pathname <- file.path(x, "Test0000.mat")
data1 <- readMat(pathname)
And this works fantastic. The format of my files is 'Name_0000.mat' where between files the name is a constant and the 4 digits increase, but not necesserally by 1.
My attempt to load multiple files at once was along these lines...
for (i in 1:length(temp))
data1<-list()
{data1[[i]] <- readMat((get(paste(temp[i]))))}
And also in multiple other ways that included and excluded path and pathname from the loop, all of which give me the same error:
Error in get(paste(temp[i])) :
object 'Test0825.mat' not found
Where 0825 is my final file name. If you change the length of the loop it is always just the name of the final one.
I think the issue is that when it pastes the name it looks for that object, which as of yet does not exist so I need to have the pasted text in speach marks, yet I dont know how to do that.
Sorry this was such a long post....Many thanks
I am trying to learn R and want to bring in an SPSS file, which I can open in SPSS.
I have tried using read.spss from foreign and spss.get from Hmisc. Both error messages are the same.
Here is my code:
## install.packages("Hmisc")
library(foreign)
## change the working directory
getwd()
setwd('C:/Documents and Settings/BTIBERT/Desktop/')
## load in the file
## ?read.spss
asq <- read.spss('ASQ2010.sav', to.data.frame=T)
And the resulting error:
Error in read.spss("ASQ2010.sav", to.data.frame = T) : error
reading system-file header In addition: Warning message: In
read.spss("ASQ2010.sav", to.data.frame = T) : ASQ2010.sav: position
0: character `\000' (
Also, I tried saving out the SPSS file as a SPSS 7 .sav file (was previously using SPSS 18).
Warning messages: 1: In read.spss("ASQ2010_test.sav", to.data.frame =
T) : ASQ2010_test.sav: Unrecognized record type 7, subtype 14
encountered in system file 2: In read.spss("ASQ2010_test.sav",
to.data.frame = T) : ASQ2010_test.sav: Unrecognized record type 7,
subtype 18 encountered in system file
I had a similar issue and solved it following a hint in read.spss help.
Using package memisc instead, you can import a portable SPSS file like this:
data <- as.data.set(spss.portable.file("filename.por"))
Similarly, for .sav files:
data <- as.data.set(spss.system.file('filename.sav'))
although in this case I seem to miss some string values, while the portable import works seamlessly. The help page for spss.portable.file claims:
The importer mechanism is more flexible and extensible than read.spss and read.dta of package "foreign", as most of the parsing of the file headers is done in R. They are also adapted to load efficiently large data sets. Most importantly, importer objects support the labels, missing.values, and descriptions, provided by this package.
The read.spss seems to be outdated a little bit, so I used package called memisc.
To get this to work do this:
install.packages("memisc")
data <- as.data.set(spss.system.file('yourfile.sav'))
You may also try this:
setwd("C:/Users/rest of your path")
library(haven)
data <- read_sav("data.sav")
and if you want to read all files from one folder:
temp <- list.files(pattern = "*.sav")
read.all <- sapply(temp, read_sav)
I know this post is old, but I also had problems loading a Qualtrics SPSS file into R. R's read.spss code came from PSPP a long time ago, and hasn't been updated in a while. (And Hmisc's code uses read.spss(), too, so no luck there.)
The good news is that PSPP 0.6.1 should read the files fine, as long as you specify a "String Width" of "Short - 255 (SPSS 12.0 and earlier)" on the "Download Data" page in Qualtrics. Read it into PSPP, save a new copy, and you should be in business. Awkward, but free.
,
You can read SPSS file from R using above solutions or the one you are currently using. Just make sure that the command is fed with the file, that it can read properly. I had same error and the problem was, SPSS could not access that file. You should make sure the file path is correct, file is accessible and it is in correct format.
library(foreign)
asq <- read.spss('ASQ2010.sav', to.data.frame=TRUE)
As far as warning message is concerned, It does not affect the data. The record type 7 is used to store features in newer SPSS software to make older SPSS software able to read new data. But does not affect data. I have used this numerous times and data is not lost.
You can also read about this at http://r.789695.n4.nabble.com/read-spss-warning-message-Unrecognized-record-type-7-subtype-18-encountered-in-system-file-td3000775.html#a3007945
It looks like the R read.spss implementation is incomplete or broken. R2.10.1 does better than R2.8.1, however. It appears that R gets upset about custom attributes in a sav file even with 2.10.1 (The latest I have). R also may not understand the character encoding field in the file, and in particular it probably does not work with SPSS Unicode files.
You might try opening the file in SPSS, deleting any custom attributes, and resaving the file.
You can see whether there are custom attributes with the SPSS command
display attributes.
If so, delete them (see VARIABLE ATTRIBUTE and DATAFILE ATTRIBUTE commands), and try again.
HTH,
Jon Peck
If you have access to SPSS, save file as .csv, hence import it with read.csv or read.table. I can't recall any problem with .sav file importing. So far it was working like a charm both with read.spss and spss.get. I reckon that spss.get will not give different results, since it depends on foreign::read.spss
Can you provide some info on SPSS/R/Hmisc/foreign version?
Another solution not mentioned here is to read SPSS data in R via ODBC. You need:
IBM SPSS Statistics Data File Driver. Standalone driver is enough.
Import SPSS data using RODBC package in R.
See the example here. However I have to admit that, there could be problems with very big data files.
For me it works well using memisc!
install.packages("memisc")
load('memisc')
Daten.Februar <-as.data.set(spss.system.file("NPS_Februar_15_Daten.sav"))
names(Daten.Februar)
I agree with #SDahm that the haven package would be the way to go. I myself have struggled a bit with string values when starting to use it, so I thought I'd share my approach on that here, too.
The "semantics" vignette has some useful information on this topic.
library(tidyverse)
library(haven)
# Some interesting information in here
vignette('semantics')
# Get data from spss file
df <- read_sav(path_to_file)
# get value labels
df <- map_df(.x = df, .f = function(x) {
if (class(x) == 'labelled') as_factor(x)
else x})
# get column names
colnames(df) <- map(.x = spss_file, .f = function(x) {attr(x, 'label')})
There is no such problem with packages you are using. The only requirement for read a spss file is to put the file into a PORTABLE format file. I mean, spss file have *.sav extension. You need to transform your spss file in a portable document that uses *.por extension.
There is more info in http://www.statmethods.net/input/importingdata.html
In my case this warning was combined with a appearance of a new variable before first column of my data with values -100, 2, 2, 2, ..., a shift in the correspondence between labels and values and the deletion of the last variable. A solution that worked was (using SPSS) to create a new dump variable in the last column of the file, fill it with random values and execute the following code:
(filename is the path to the sav file and in my case the original SPSS file had 62 columns, thus 63 with the additional dumb variable)
library(memisc)
data <- as.data.set(spss.system.file(filename))
copyofdata = data
for(i in 2:63){
names(data)[i] <- names(copyofdata)[i-1]
}
data[[1]] <- NULL
newcopyofdata = data
for(i in 2:62){
labels(data[[i]]) <- labels(newcopyofdata[[i-1]])
}
labels(data[[1]]) <- NULL
Hope the above code will help someone else.
Turn your UNICODE in SPSS off
Open SPSS without any data open and run the code below in your syntax editor
SET UNICODE OFF.
Open the data set and resave it to remove the Unicode
read.spss('yourdata.sav', to.data.frame=T) works correctly then
I just came came across an SPSS file that I couldn't get open using haven, foreign, or memisc, but readspss::read.por did the trick for me:
download.file("http://www.tcd.ie/Political_Science/elections/IMSgeneral92.zip",
"IMSgeneral92.zip")
unzip("IMSgeneral92.zip", exdir = "IMSgeneral92")
# rio, haven, foreign, memisc pkgs don't work on this file! But readspss does:
if(!require(readspss)) remotes::install_git("https://github.com/JanMarvin/readspss.git")
ims92 <- readspss::read.por("IMSgeneral92/IMS_Nov7 92.por", convert.factors = FALSE)
Nice! Thanks, #JanMarvin!
1)
I've found the program, stat-transfer, useful for importing spss and stata files into R.
It resolves the issue you mention by converting spss to R dataset. Also very useful for subsetting super large datasets into smaller portions consumable by R. Not free, but a very useful tool for working with datasets from different programs -- especially if you don't have access to them.
2)
Memisc package also has an spss function worth trying.