Skip to main content

Update to Data on Github Post: Solution to an RCurl problem

A reader of my most recent post tried the R code I had written to download the data set of electoral disproportionality from the GitHub repository. However, it didn’t work for them. After entering disproportionality.data <- getURL(url) they got the error message:

Error in function (type, msg, asError = TRUE)  : 
SSL certificate problem, verify that the CA cert is OK. Details:
error:14090086:SSL routines:SSL3_GET_SERVER_CERTIFICATE:certificate verify failed


The Solution

The problem seems to be that they didn’t have a certificate from an appropriate signing agent (see the RCurl FAQ page near the bottom) for more information. If you are really interested in SSL verification this page from redhat is a place to look).

The solution to this problem is pretty straightforward. As the RCurl FAQ page points out you can use the argument ssl.verifypeer = FALSE to skip certificate verification (effectively a man-in-the-middle attack).

So, if you get the above error message just use this new code:

library(RCurl)

url <- "https://raw.github.com/christophergandrud/Disproportionality_Data/master/Disproportionality.csv"

disproportionality.data <- getURL(url, ssl.verifypeer = FALSE)                

disproportionality.data <- read.csv(textConnection(disproportionality.data))

That should work.



Question

I didn’t originally mention this issue, because I didn’t get it when I ran the code on my Mac. When I tried the code on a Windows machine I was able to replicate the error.

Does any reader know why Windows computers (or any other types) lack certificates from an appropriate signing agent needed to download data from GitHub? How can you get one?

Labels:

Comments

Tangential Insights said…
A certificate bundle comes with various browsers as well as with the RCurl library

R-2.15.0\library\RCurl\CurlSSL\cacert.pem

curl <- getCurlHandle(cainfo="cacert.pem",followlocation=TRUE,
cookiefile='cookies.txt',cookiejar='cookies.txt')
url1 <- "https://telogdata.hrsd.com/TWM/DesktopLoginPage.aspx"
out <- getURI(url1,curl=curl)
12:39
Tangential Insights said…
This comment has been removed by the author.
12:40
Unknown said…
A solution is provided at http://tonybreyal.wordpress.com/2011/11/24/source_https-sourcing-an-r-script-from-github/
I adapted the script at https://github.com/bobthecat/codebox/blob/master/source_https.r
16:59
Unknown said…
Great, thanks for this.
22:44
Post a Comment

Popular posts from this blog

Showing results from Cox Proportional Hazard Models in R with simPH

Update 2 February 2014: A new version of simPH (Version 1.0) will soon be available for download from CRAN. It allows you to plot using points, ribbons, and (new) lines. See the updated package description paper for examples. Note that the ribbons argument will no longer work as in the examples below. Please use type = 'ribbons' (or 'points' or 'lines' ). Effectively showing estimates and uncertainty from Cox Proportional Hazard (PH) models , especially for interactive and non-linear effects, can be challenging with currently available software. So, researchers often just simply display a results table. These are pretty useless for Cox PH models. It is difficult to decipher a simple linear variable’s estimated effect and basically impossible to understand time interactions, interactions between variables, and nonlinear effects without the reader further calculating quantities of interest for a variety of fitted values. So, I’ve been putting together th
12 comments
Read more

Slide: one function for lag/lead variables in data frames, including time-series cross-sectional data

I often want to quickly create a lag or lead variable in an R data frame. Sometimes I also want to create the lag or lead variable for different groups in a data frame, for example, if I want to lag GDP for each country in a data frame. I've found the various R methods for doing this hard to remember and usually need to look at old blog posts . Any time we find ourselves using the same series of codes over and over, it's probably time to put them into a function. So, I added a new command– slide –to the DataCombine R package (v0.1.5). Building on the shift function TszKin Julian posted on his blog , slide allows you to slide a variable up by any time unit to create a lead or down to create a lag. It returns the lag/lead variable to a new column in your data frame. It works with both data that has one observed unit and with time-series cross-sectional data. Note: your data needs to be in ascending time order with equally spaced time increments. For example 1995, 1996
44 comments
Read more

Dropbox & R Data

I'm always looking for ways to download data from the internet into R. Though I prefer to host and access plain-text data sets (CSV is my personal favourite) from GitHub (see my short paper on the topic) sometimes it's convenient to get data stored on Dropbox . There has been a change in the way Dropbox URLs work and I just added some functionality to the repmis R package. So I though that I'ld write a quick post on how to directly download data from Dropbox into R. The download method is different depending on whether or not your plain-text data is in a Dropbox Public folder or not. Dropbox Public Folder Dropbox is trying to do away with its public folders. New users need to actively create a Public folder. Regardless, sometimes you may want to download data from one. It used to be that files in Public folders were accessible through non-secure (http) URLs. It's easy to download these into R, just use the read.table command, where the URL is the file name
84 comments
Read more