I want to be able to read and edit spatial SQlite tables that are downloaded from a server. These come compressed.
These zip files have a folder in them that contains information about the model that has been run as the name of the folder, and as such these can sometimes be quite long.
When this folder name gets too long, unziping the folder fails. I ultimately dont need to unzip the file. But i seem to get the same error when I use unz within readOGR.
I cant think of how to recreate a replicate able example but I can give an example of a path that works and one that doesnt.
Works:
"S:\3_Projects\CRC00001\4699-12103\scenario_initialised model\performance_assessment.sqlite"
4699-12103 is the zip file name
and "scenario_initialised model" is the offending subfolder
Fails:
""S:\3_Projects\CRC00001\4699-12129\scenario_tree_canopy_7, number_of_trees_0, roads_False, compliance_75, year_2030, nrz_cover_0.6, green_roofs_0\performance_assessment.sqlite""
4699-12103 is the zip file name
and "scenario_tree_canopy_7, number_of_trees_0, roads_False, compliance_75, year_2030, nrz_cover_0.6, green_roofs_0" is the offending subfolder
The code would work in a similar fashion to this.
list_zips <- list.files(pattern = "*.zip", recursive = TRUE, include.dirs = TRUE)
unzip(zipfile = paste(getwd(),"/",list_zips[i],sep = ""),
exdir=substr(paste(getwd(),"/",list_zips[i],sep = ""),1,nchar(paste(getwd(),"/",list_zips[i],sep = ""))-4))
But I would prefer to directly be able to load the spatial file in without unzipping. Such as:
sq_path <- unzip(list_zips[i], list=TRUE)[2,1]
temp <- unz(paste(getwd(),"/",list_zips[i],sep = ""),sq_path)
vectorImport <- readOGR(dsn=temp, layer="micro_climate_grid")
Any help would be appreciated! Tim
Related
I am trying to create objects from all files in working directory with name of the original file. I tried to go the following way, but couldn't solve appearing problems.
# - SETTING WD
getwd()
setwd("PATH TO THE FILE")
library(readxl)
# - CREATING OBJECTS
file_objects <- list.files()
xlsx_objects <- unlist(grep(".xlsx",file_objects,value = T))
for (i in xlsx_objects) {
xlsx_objects[i] <- read_xlsx(xlsx_objects[i], header = T)
}
I tried to paste [i]item from "xlsx_objects" with path to WD but it only created a list of files names from docs in WD.
I also find information, that read.csv can read only one file at the time, but I guess that it should be the case with for loop, right? It is reading only one file at the time.
Using lapply (as described in this forum) I was able to get the data in the environment, but argument header didn't work, I lost names of my docs in that object which does not have desired structure. I am though looking for having these files in separated objects without calling every document exclusively.
IIUC, you could do something like:
files = list.files("PATH TO THE FILE", full.names = T, pattern = 'xlsx')
list_files = map(files, readxl::read_excel)
(You can't use read.csv to read excel files)
Also I recommend reading about R Projects so you don't have to use setwd() ever again, which makes your code harder to reproduce down the pipeline
I am trying to find a way of loading shapefiles (.shp) from an online repository/folder/url directly into my global environment in R, for the purpose of making plots in ggplot2 using geom_sf. In the first instance I'm using my Google Drive to store these files but I'd ideally like to find a solution that works with any folder with a valid url and appropriate access rights.
So far I have tried a few options, the first 2 involving zipping the source folder on Google Drive where the shapefiles are stored and then downloading and unzipping in some way. Have included reproducable examples using a small test shapefile:
Using utils::download.file() to retrieve the compressed folder and unzipping using either base::system('unzip..') or zip::unzip() (loosely following this thread: Downloading County Shapefile from ONS):
# Create destination data folder (if there isn't one)
if(!dir.exists('data')) dir.create('data')
# Download the zipped file/folder
download.file("https://drive.google.com/file/d/1BYTCT_VL8EummlAsH1xWCd5rC4bZHDMh/view?usp=sharing", destfile = "data/test_shp.zip")
# Unzip folder using unzip (fails)
unzip(zipfile = "data/test_shp.zip", exdir = "data/test_shp", junkpaths = TRUE)
# Unzip folder using system (also fails)
system("unzip data/test_shp.zip")
If you can't run the above code then FYI the 2 error messages are:
Warning message:
In unzip(zipfile = "data/test_shp.zip", exdir = "data/test_shp", :
error 1 in extracting from zip file
AND
End-of-central-directory signature not found. Either this file is not
a zipfile, or it constitutes one disk of a multi-part archive. In the
latter case the central directory and zipfile comment will be found on
the last disk(s) of this archive.
unzip: cannot find zipfile directory in one of data/test_shp.zip or
data/test_shp.zip.zip, and cannot find data/test_shp.zip.ZIP, period.
Worth noting here that I can't even manually unzip this folder outside R so I think there's something going wrong with the download.file() step.
Using the googledrive package:
# Create destination data folder (if there isn't one)
if(!dir.exists('data')) dir.create('data')
# Specify googledrive url:
test_shp = drive_get(as_id("https://drive.google.com/file/d/1BYTCT_VL8EummlAsH1xWCd5rC4bZHDMh/view?usp=sharing"))
# Download zipped folder
drive_download(test_shp, path = "data/test_shp.zip")
# Unzip folder
zip::unzip(zipfile = "data/test_shp.zip", exdir = "data/test_shp", junkpaths = TRUE)
# Load test.shp
test_shp <- read_sf("data/test_shp/test.shp")
And that works!
...Except it's still a hacky workaround, which requires me to zip, download, unzip and then use a separate function (such as sf::read_sf or st_read) to read in the data into my global environment. And, as it's using the googledrive package it's only going to work for files stored in this system (not OneDrive, DropBox and other urls).
I've also tried sf::read_sf, st_read and fastshp::read.shp directly on the folder url but those approaches all fail as one might expect.
So, my question: is there a workflow for reading shapefiles stored online directly into R or should I stop looking? If there is not, but there is a way of expanding my above solution (2) beyond googledrive, I'd appreciate any tips on that too!
Note: I should also add that I have deliberately ignored any option requiring the package rgdal due to its imminient permanent retirement and so am looking for options that are at least somewhat future-proof (I understand all packages drop off the map at some point). Thanks in advance!
I ran into a similar problem recently, having to read in shapefiles directly from Dropbox into R.
As a result, this solution only applies for the case of Dropbox.
The first thing you will need to do is create a refreshable token for Dropbox using rdrop2, given recent changes from Dropbox that limit single token use to 4 hours. You can follow this SO post.
Once you have set up your refreshable token, identify all the files in your spatial data folder on Dropbox using:
shp_files_on_db<- drop_dir("Dropbox path/to your/spatial data/", dtoken = refreshable_token) %>%
filter(str_detect(name, "adm2"))
My 'spatial data' folder contained two sets of shapefiles – adm1 and adm 2. I used the above code to choose only those associated with adm2.
Then create a vector of the names of the shp, csv, shx, dbf, cpg files in the 'spatial data' folder, as follows:
shp_filenames<- shp_files_on_db$name
I choose to read in shapefiles into a temporary directory, avoiding the need to have to store the files on my disk – also useful in a Shiny implementation. I create this temporary directory as follows:
# create a new directory under tempdir
dir.create(dir1 <- file.path(tempdir(), "testdir"))
#If needed later on, you can delete this temporary directory
unlink(dir1, recursive = T)
#And test that it no longer exists
dir.exists(dir1)
Now download the Dropbox files to this temporary directory:
for (i in 1: length(shp_filenames)){
drop_download(paste0("Dropbox path/to your/spatial data/",shp_filenames[i]),
dtoken = refreshable_token,
local_path = dir1)
}
And finally, read in your shapefile as follows:
#path to the shapefile in the temporary directory
path1_shp<- paste0(dir1, "/myfile_adm2.shp")
#reading in the shapefile using the sf package - a recommended replacement for rgdal
shp1a <- st_read(path1_shp)
I am working under some unfortunate circumstances, and need to read in a csv file from within 2 zip folders. What I mean by this is that the file path looks something like this:
//path/folder1.zip/folder2.zip/wanttoread.csv
I tried mimicking the slick work of this problem found here: Extract certain files from .zip , but have had no luck so far. Specifically, when I ran something similar on my end, I got an error message reading
Error in fread(x, sep = ",", header = TRUE, stringsAsFactors = FALSE) :
embedded nul in string:
followed by a bunch of encoded nonsense.
Any ideas on how to handle this problem? Thanks in advance!
Here's an approach using tempdir():
temp<-tempdir(check = TRUE) #Create temporary directory to extract into
unzip("folder1.zip",exdir = temp) #Unzip outer archive to temp directory
unzip(file.path(temp,"folder2.zip"), #Use file.path to generate the path to the inner archive
exdir = file.path(temp,"temp2")) #Extract to a subfolder inside temp
#This covers the case when the outer archive might also have a file named wanttoread.csv
list.files(file.path(temp,"temp2")) #We can see the .csv file is now there
#[1] "wanttoread.csv"
read.csv(file.path(temp,"temp2","wanttoread.csv")) #Read it in
# Var1 Var2
#1 Hello obewanjacobi
I have tried looking at File extension renaming in R and using the script without any luck. My question is very much the same.
I have a bunch of files with the a file extension that I want to change. I have used the following code but cannot get the last step to work.
I know similar questions have been asked before but I'm simply stuck and therefore reaching out anyway.
startingDir<-"/Users/anders/Documents/Juni 2019/DATA"
endDir<-"/Users/anders/Documents/Juni 2019/DATA/formatted"
#List over files in startingDir with the extension .zipwblibcurl that I want to replace
old_files<-list.files(startingDir,pattern = "\\.zipwblibcurl")
#View(old_files)
#Renaming the file extension and making a new list i R changing the file extension from .zipwblibcurl to .zip
new_files <- gsub(".zipwblibcurl", ".zip", old_files)
#View(new_files)
#Replacing the old files in the startingDir. Eventually I would like to move them to newDir. For simplicity I have just tried as in the other post without any luck:...
file.rename( old_files, new_files)
After running file.rename I get the output FALSE for every entry.
The full answer here, including comment from #StephaneLaurent: make sure that you have full.names = TRUE inside the list.files(); otherwise the path to the file will not be captured, just the file name.
Full working snippet:
old = list.files(startingDir,
pattern = "\\.zipwblibcurl",
full.names = TRUE) #
# replace the file names
new <- gsub(".zipwblibcurl", ".zip", old )
# Rename old files names to the new file names
file.rename(old, new)
Like #StéphaneLaurent said, it's most likely that R tries to look in the current working directory for the files and can't find them. You can correct this by adding
file.rename(paste(startingDir, old_files, sep = "/"), paste(newDir, new_files, sep = "/"))
In R, I am trying to download files off the internet using the download.file() command in a simple code (am complete newbie). The files are downloading properly. However, if a file already exists in the download destination, I'd wish to rename the downloaded file with an increment, as against an overwrite which seems to be the default process.
nse.url = "https://www1.nseindia.com/content/historical/DERIVATIVES/2016/FEB/fo04FEB2016bhav.csv.zip"
nse.folder = "D:/R/Download files from Internet/"
nse.destfile = paste0(nse.folder,"fo04FEB2016bhav.csv.zip")
download.file(nse.url,nse.destfile,mode = "wb",method = "libcurl")
Problem w.r.t to this specific code: if "fo04FEB2016bhav.csv.zip" already exists, then get say "fo04FEB2016bhav.csv(2).zip"?
General answer to the problem (and not just the code mentioned above) would be appreciated as such a bottleneck could come up in any other situations too.
The function below will automatically assign the filename based on the file being downloaded. It will check the folder you are downloading to for the presence of a similarly named file. If it finds a match, it will add an incrementation and download to the new filename.
ekstroem's suggestion to fiddle with the curl settings is probably a much better approach, but I wasn't clever enough to figure out how to make that work.
download_without_overwrite <- function(url, folder)
{
filename <- basename(url)
base <- tools::file_path_sans_ext(filename)
ext <- tools::file_ext(filename)
file_exists <- grepl(base, list.files(folder), fixed = TRUE)
if (any(file_exists))
{
filename <- paste0(base, " (", sum(file_exists), ")", ".", ext)
}
download.file(url, file.path(folder, filename), mode = "wb", method = "libcurl")
}
download_without_overwrite(
url = "https://raw.githubusercontent.com/nutterb/redcapAPI/master/README.md",
folder = "[path_to_folder]")
Try this:
nse.url = "https://www1.nseindia.com/content/historical/DERIVATIVES/2016/FEB/fo04FEB2016bhav.csv.zip"
nse.folder = "D:/R/Download files from Internet/"
#Get file name from url, with file extention
fname.x <- gsub(".*/(.*)", "\\1", nse.url)
#Get file name from url, without file extention
fname <- gsub("(.*)\\.csv.*", "\\1", fname.x)
#Get xtention of file from url
xt <- gsub(".*(\\.csv.*)", "\\1", fname.x)
#How many times does the the file exist in folder
exist.times <- sum(grepl(fname, list.files(path = nse.folder)))
if(exist.times){
# if it does increment by 1
fname.x <- paste0(fname, "(", exist.times + 1, ")", xt)
}
nse.destfile = paste0(nse.folder, fname.x)
download.file(nse.url, nse.destfile, mode = "wb",method = "libcurl")
Issues
This approach will not work in cases where part of the file name already exists for example you have url/test.csv.zip and in the folder you have a file testABC1234blahblah.csv.zip. It will think the file already exists, so it will save it as test(2).csv.zip.
You will need to change the #How many times does the the file exist in folder part of the code accordingly.
This is not a proper answer and shouldn't be considered as such, but the comment section above was too small to write it all.
I thought the -O -n options to curl could be used to but now that I looked at it more closely it turned out that it wasn't implemented yet. Now wget automatically increment the filename when downloading a file that already exists. However, setting method="wget" doesn't work with download.file because you are forced to set the destination file name, and once you do that you overwrite the automatic file increments.
I like the solution that #Benjamin provided. Alternatively, you can use
system(paste0("wget ", nse.url))
to get the file through the system (provided that you have wget installed) and let wget handle the increment.