I'm trying to get data from the Lithuanian Statistics Department. They offer SDMX API with either XML or JSON (LSD).
The example XML shown is : https://osp-rs.stat.gov.lt/rest_xml/data/S3R629_M3010217 which downloads the XML file.
I tried following:
devtools::install_github("opensdmx/rsdmx")
library(rsdmx)
string <- "https://osp-rs.stat.gov.lt/rest_xml/data/S3R629_M3010217"
medianage <- readSDMX(string)
which results in error:
<simpleError in doTryCatch(return(expr), name, parentenv, handler): Invalid SDMX-ML file>
I also tried simply reading in the manually downloaded file
devtools::install_github("opensdmx/rsdmx")
library(rsdmx)
medianage <- readSDMX(file="rest_data_M3010217_20180116163251.xml" , isURL = FALSE)
medianage <- as.data.frame(medianage)
results in medianage being NULL (empty)
Maybe soneone has an idea, how I could solve downloading /transforming the data from LSD by using either:
https://osp-rs.stat.gov.lt/rest_xml/data/S3R629_M3010217
https://osp-rs.stat.gov.lt/rest_json/data/S3R629_M3010217
Thanks a lot!
In order to use rsdmx for this datasource, some enhancements have been added (see details at https://github.com/opensdmx/rsdmx/issues/141). You will need re-install rsdmx from Github (version 0.5-11)
You can use the url of the SDMX-ML file
library(rsdmx)
url <- "https://osp-rs.stat.gov.lt/rest_xml/data/S3R629_M3010217"
medianage <- readSDMX(url)
df <- as.data.frame(medianage)
A connector has been added in rsdmx to facilitate data query on the LSD (Lithuanian Statistics Department) SDMX endpoint. See below an example on how to use it.
sdmx <- readSDMX(providerId = "LSD", resource = "data",
flowRef = "S3R629_M3010217", dsd = TRUE)
df <- as.data.frame(sdmx, labels = TRUE)
The above example shows how to enrich the data.frame with code labels extracted from the SDMX Data Structure Definition (DSD). For this, specify dsd = TRUE with readSDMX. This allows then to use labels = TRUE when converting to data.frame. For filtering data with readSDMX, e.g. (startPeriod, endPeriod, code filters), check this page https://github.com/opensdmx/rsdmx/wiki#readsdmx-as-helper-function
Related
I am currently trying to scrape the data from the two graphs on following html page (information from two graphs listed there: Forsmark and Ringhals): https://group.vattenfall.com/se/var-verksamhet/vara-energislag/karnkraft/aktuell-karnkraftsproduktion
The data originate from script tags like this (fragment)
<script type="text/javascript">
/*<![CDATA[*/ productionData = JSON.parse("{\"timestamp\":1582642616000,\"powerPlant\":\"Ringhals\", // etc
</script>
I would like to get two dataframes that looks like these:
F1 F2 F3
number number number
and
R1 R2 R3
number number number
I tried to use XML and xpath to parse an html page but did not get anywhere with that.
Do you have any ideas?
Thanks!
Those charts are <iframe>s that load from
https://gvp.vattenfall.com/sweden/produced-power/iframe/forsmark and
https://gvp.vattenfall.com/sweden/produced-power/iframe/ringhals
so you should scrape those two pages directly.
This was an interesting challenge.
It becomes not too hard with rvest and jsonlite, which you will have to install if you don't already have. Both require rtools.
Try this:
library('rvest')
library('jsonlite')
# Load the URL (do the same for the other iframe)
url <- 'https://gvp.vattenfall.com/sweden/produced-power/iframe/forsmark'
# Parse it
webpage <- read_html(url)
# Extract the script element. That's a CSS selector for the specific one that holds the json data
# You can find it in your browser's DevTools by finding the script element
# and right-clicking, choosing Copy > CSS Path/Selector
script_element <- html_nodes(webpage, 'body > section:nth-child(2) > script:nth-child(2)')
# Extract its string content
json = html_text(script_element)
# Clean it up
json = gsub("\n /*<![CDATA[*/\n productionData = JSON.parse(", "", json, fixed=TRUE)
json = gsub(");\n /*]]>*/\n ", "", json, fixed=TRUE)
json = gsub("\"{", "{\"", json, fixed=TRUE)
json = gsub("}\"", "}", json, fixed=TRUE)
json = gsub("{\"\\\"", "{\\\"", json, fixed=TRUE)
# Extract data
data = jsonlite::fromJSON(gsub("\\\"", "\"", json, fixed=TRUE))
Caveat: I'm not really an R expert, there is likely a more elegant way of doing this (particularly the data cleaning portion). But it works.
For historical preservation, that takes this DOM node (the text content of the <script> tag):
"\n /*<![CDATA[*/\n productionData = JSON.parse(\"{\\\"timestamp\\\":1582643336000,\\\"powerPlant\\\":\\\"Forsmark\\\",\\\"blockProductionDataList\\\":[{\\\"name\\\":\\\"F1\\\",\\\"production\\\":998.86194,\\\"percent\\\":99.88619},{\\\"name\\\":\\\"F2\\\",\\\"production\\\":1120.434,\\\"percent\\\":97.8545},{\\\"name\\\":\\\"F3\\\",\\\"production\\\":1189.7126,\\\"percent\\\":99.55754}]}\");\n /*]]>*/\n "
and will result in data of this format
> data
$timestamp
[1] 1.582647e+12
$powerPlant
[1] "Forsmark"
$blockProductionDataList
name production percent
1 F1 997.7902 99.77902
2 F2 1131.6150 98.83100
3 F3 1190.0520 99.58594
I was provided with a list of identifiers (in this case the identifier is called an NPI). These identifiers can be copied and pasted to this website (https://npiregistry.cms.hhs.gov/registry/?). I want to return the name of the NPI number, name of the physician, address, phone number, and specialty.
I have over 3,000 identifiers so a copy and paste is not efficient and not easily repeatable for future use.
If possible, I would like to create a list of URLs, pass them into a function, and received a dataframe that provides me with the variables mentioned above (NPI, NAME, ADDRESS, PHONE, SPECIALTY).
I was able to write a function that produces the URLs needed:
Here are some NPI numbers for reference: 1417024746, 1386790517, 1518101096, 1255500625.
This is my code for reading in the file that contains my NPIs
npiList <- c("1417024746", "1386790517", "1518101096", "1255500625")
npiList <- as.list(npiList)
npiList <- unlist(npiList, use.names = FALSE)
This is the function to return the list of URLs:
npiaddress <- function(x){
url <- paste("https://npiregistry.cms.hhs.gov/registry/search-results-
table?number=",x,"&addressType=ANY", sep = "")
return(url)
}
I saved the list to a variable and perhaps this is my downfall:
npi_urls <- npiaddress(npiList)
From here I wrote a function that can accept a single URL, retrieves the data I want and turns it into a dataframe. My issue is that I cannot pass multiple URLs:
npiLookup <- function (x){
url <- x
webpage <- read_html(url)
npi_html <- html_nodes(webpage, "td")
npi <- html_text(npi_html)
npi[4] <- gsub("\r?\n|\r", " ", npi[4])
npi[4] <- gsub("\r?\t|\r", " ", npi[4])
npiFinal <- npi[c(1:2,4:6)]
npiFinal <- as.data.frame(npiFinal)
npiFinal <- t(npiFinal)
npiFinal <- as.data.frame(npiFinal)
names(npiFinal) <- c("NPI", "NAME", "ADDRESS", "PHONE", "SPECIALTY")
return(npiFinal)
}
For example:
If I wanted to get a dataframe for the following identifier (1417024746), I can run this and it works:
x <- npiLookup("https://npiregistry.cms.hhs.gov/registry/search-results-table?number=1417024746&addressType=ANY")
View(x)
My output for the example returns the NPI, NAME, ADDRESS, PHONE, SPECIALTY as desired, but again, I need to do this for several thousand NPI identifiers. I feel like I need a loop within npiLookup. I've also tried to put npi_urls into the npiLookup function but it does not work.
Thank you for any help and for taking the time to read.
You're most of the way there. The final step uses this useful R idiom:
do.call(rbind,lapply(npiList,function(npi) {url=npiaddress(npi); npiLookup(url)}))
do.call is a base R function that applies a function (in this case rbind) to the list produced by lapply. That list is the result of running your npiLookup function on the url produced by your npiaddress for each element of npiList.
A few further comments for future reference should anyone else come upon this question: (1) I don't know why you're doing the as.list, unlist sequence at the beginning; it's redundant and probably unnecessary. (2) The NPI registry provides a programming interface (API) that avoids the need to scrape data from the HTML pages; this might be more robust in the long run. (3) The NPI registry provides the entire dataset as a downloadable file; this might have been an easier way to go.
I have multiple JSON files containing Tweets from Twitter. I want to import and edit them in R one by one.
For a single file my code looks like this:
data <- fromJSON("filename.json")
data <- data[c(1:3,13,14)]
data$lang <- ifelse(data$lang!="de",NA,data$lang)
data <- na.omit(data)
write_as_csv(data,"filename.csv")
Now I want to apply this code to multiple files. I found a "for" loop code here:
Loop in R to read many files
Applied to my problem it should look something like this:
setwd("~/Documents/Elections")
ldf <- list()
listjson <- dir(pattern = "*.json")
for (k in 1:length(listjson)){
data[k] <- fromJSON(listjson[k])
data[k] <- data[k][c(1:3,13,14)]
data[k]$lang <- ifelse(data[k]$lang!="de",NA,data[k]$lang)
data[k] <- na.omit(data[k])
filename <- paste(k, ".csv")
write_as_csv(listjson[k],filename)
}
But the first line in the loop already doesn't work.
> data[k] <- fromJSON(listjson[k])
Warning message:
In `[<-.data.frame`(`*tmp*`, k, value = list(createdAt = c(1505935036000, :
provided 35 variables to replace 1 variables
I can't figure out why. Also, I wonder if there is a nicer way to realize this problem without using a for loop. I read about the apply family, I just don't know how to apply it to my problem. Thanks in advance!
This is an example how my data looks:
https://drive.google.com/file/d/19cRS6p_mHbO6XXprfvc6NPZWuf_zG7jr/view?usp=sharing
It should work like this:
setwd("~/Documents/Elections")
listjson <- dir(pattern = "*.json")
for (k in 1:length(listjson)){
# Load the JSON that correspond to the k element in your list of files
data <- fromJSON(listjson[k])
# Select relevant columns from the dataframe
data <- data[,c(1:3,13,14)]
# Manipulate data
data$lang <- ifelse(data$lang!="de",NA,data$lang)
data <- na.omit(data)
filename <- paste(listjson[k], ".csv")
write_as_csv(data,filename)
}
For the second part of the question, apply applies a function over rows or columns of a dataframe. This is not your case, as you are looping through a vector of character to get filenames to be used somewhere else.
I am trying to turn a .json file into a data frame for data visualization.
If I run the below code I get picture 1.
library(jsonlite)
jdata <- fromJSON("test.json")
data <- as.data.frame(jdata)
And when I try to transpose it, I get picture 2.
data2 <- as.data.frame(t(data))
This is how the json looks like raw:
I don't understand why column one has no name or is not part of the data frame (is jsonlite assuming these are tittles?). How can I overcome this?
I need a data frame from the json files:
Column1 (with the dates) | Column2 (I will divide it into values and coordinates
Try this for the input file test.json
library(jsonlite)
jdata <- read_json("test.json", simplifyVector = TRUE)
I am trying to use \Sexpr{} to include values from my R objects in a LaTeX table. I am essentially trying to replicate the summary output of a lm object in R because xtable's built in methods xtable.lm and xtable.summary.lm don't seem to include the Fstats, adjusted R-squared, etc (all the stuff at the bottom of the summary printout of the lm object in R console) So I tried accomplishing this by building a matrix to replicate the xtable.summary.lm output then construct a data frame of the relevant info for the extra stuff so I can refer to the values using \Sexpr{}. I tried doing this by using add.to.row to append the \multicolumn{} command in order to merge all columns of the last row of the LaTeX table and then just pass all the information I need into that cell of the table.
The problem is that I get an "Undefined control sequence" for the \Sexpr{} expression in the \multicolumn{} expression. Are these two not compatible? If so, what am I doing wrong and if not does anyone know how to do what I am trying to do?
Thanks,
Here is the relevant part of my code:
<<Test, results=tex>>=
model1 <- lm(stndfnl ~ atndrte + frosh + soph)
# Build matrix to replicate xtable.summary.lm output
x <- summary(model1)
colnames <- c("Estimate", "Std. Error", "t value", "Pr(<|t|)")
rownames <- c("(Intercept)", attr(x$terms, "term.labels"))
fpval <- pf(x$fstatistic[1],x$fstatistic[2], x$fstatistic[3], lower.tail=FALSE)
mat1 <- matrix(coef(x), nrow=length(rownames), ncol=length(colnames), dimnames=list(rownames,colnames))
# Make a data frame for extra information to be called by \Sexpr in last row of table
residse <- x$sigma
degf <- x$df[2]
multr2 <- x$r.squared
adjr2 <- x$adj.r.squared
fstat <- x$fstatistic[1]
fstatdf1 <- x$fstatistic[2]
fstatdf2 <- x$fstatistic[3]
extradat <- data.frame(v1 = round(residse,4), v2 =degf, v3=round(multr2,4), v4=round(adjr2,4),v5=round(fstat,3), v6=fstatdf1, v7=fstatdf2, v8=round(fpval,6))
addtorow<- list()
addtorow$pos <-list()
addtorow$pos[[1]] <- dim(mat1)[1]
addtorow$command <-c('\\hline \\multicolumn{5}{l}{Residual standard error:\\Sexpr{extradat$v1}} \\\\ ')
print(xtable(mat1, caption="Summary Results for Regression in Equation \\eqref{model1} ", label="tab:model1"), add.to.row=addtorow, sanitize.text.function=NULL, caption.placement="top")
You don't need to have Sexpr in your R code; the R code can use the expressions directly. Sexpr is not a LaTeX command, even though it looks like one; it's an Sweave command, so it doesn't work to have it as output from R code.
Try
addtorow$command <-paste('\\hline \\multicolumn{5}{l}{Residual standard error:',
extradat$v1, '} \\\\ ')
Also, no need to completely recreate the matrix used by xtable, you can just build on the default output. Building on what you have above, something like:
mytab <- xtable(model1, caption="Summary Results", label="tab:model1")
addtorow$pos[[1]] <- dim(mytab)[1]
print(mytab, add.to.row=addtorow, sanitize.text.function=NULL,
caption.placement="top")
See http://people.su.se/~lundh/reproduce/sweaveintro.pdf for an example which you might be able to use as is.