Good afternoon,
I’m currently working in R and importing data sets that have .xlsx format.
I use standard function read_excel.
For example:
MCC_1 <- read_excel("MCC_1.xlsx", guess_max = 500000, n_max = 500000)
Most of my files were imported correctly, however suddenly I faced with an error.
It is said: Error: expected ' or "
In a Traceback section I see this:
class = c("rapidxml::parse_error", "C++Error", "error", "condition")
Could you give me any ideas or even solutions of how to overcome it?
Thank you in advance!
Found a solution by myself!
All you have to do is to create a copy of your excel file to a new file. The problem stated appears when R is trying to read .xlsx files that were made automatically - for example during data unloading procedure from specific databases.
I've been using mapshot a lot to send interactive maps of data but recently, although I can make the maps I want with mapview, I can't save them.
Example:
map<- mapview(mapdata, zcol = "columnofinterest", burst = TRUE)
mapshot(map, url = paste0(getwd(), "/whatIwanttocallmymap.html"))
File whatIwanttocallmymap_files/PopupTable-0.0.1/popup.css not found in resource path
Error: pandoc document conversion failed with error 99
I'm afraid I've messed something up in how I get packages. folders with package names are turning up in the area I've set as my wd instead of in my library for R
Thank you for any help/suggestions you might have
I have dug into rlist and purrr and found them to be quite helpful in working with lists of pre-structured data. I tried to solve the problems arising on my one to improve my coding skills - so thanks to the community of helping out! However, I reached a dead-end now:
I want to write a code which is needed to be written in a way, that we throw our excel files in xlsm format to the folder an r does the rest.
I Import my data using:
vec.files<-list.files(pattern=".xlsm")
vec.numbers<- gsub("\\.xlsm","",vec.files)
list.alldata <- lapply(vec.files, read_excel, sheet="XYZ")
names(list.alldata) <- vec.numbers
The data we call is a combination of charaters, Dates (...).
When I try to use the rlist-package everything works fine until I try to use to filter on names, which were in the excel file not a fixed entry (e.g. Measurable 1), but a reference to another field (e.g. =Table1!A1, or an Reference).
If I try to call a false element I get this failure:
list.map(list.alldata, NameWhichWasAReferenceToAnotherFieldBefore)
Fehler in eval(.expr, .evalwith(.data), environment()) :
Objekt 'Namewhichwasareferencetoanotherfieldbefore' nicht gefunden
I am quite surprised, as if I call
names(list.alldata[[1]])
I get a vector with the correct entries / names.
As I identified the read_excel() as the problem causing reason I tried to add col_names=True, but did not help. Also col_names=False calls the correct arguments into the dataset.
I assume, that exporting the data as a .csv would help, but this is not an option. Can this be easily done by r in a pree-loop?
In my concept of working assessing the data by the names is essential and there is no work around so I really appreciate your help!
I am trying to use XLConnect to load in a series of excel workbooks that I have. Using the code:
BASZ <- loadWorkbook("BASZ.xlsx", create = TRUE)
works every time, and gives me a formal class workbook. However when I go to read in the worksheet I wish to use:
data <- readWorksheet("BASZ", sheet = "Sheet1")
I always get the same arguement:
"Error: IllegalArgumentException (Java): Sheet index (-1) is out of range (no sheets")
Just yesterday this code worked, im new to this and wondering why this continues to occur. Furthermore; it doesn't matter which excel workbook I try to load, the same error occurs when trying to read in the specific sheet I want to work with. It must be a syntax issue or something im doing wrong right? I fail to understand why it would work, then I close out Studio, then the next day it won't...?
If you have already loaded the excel file using loadWorkbook(), you can use the function readWorksheet() to read individual sheets. You would only use readWorksheetFromFile() if you had not previously loaded the file. So your code should read:
BASZ <- loadWorkbook("BASZ.xlsx", create = TRUE)
data <- readWorksheet(BASZ, sheet = "Sheet1")
Note that in the second line, the first argument is the variable BASZ, not a quoted string.
Okay so just in case someone else makes the same mistake as me; you have to be working within the directory your xlsx file is in.
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.