Error on All Queries - "CHAR() can only be applied to a 'CHARSXP', not to a 'NULL' about ngramr HOT 15 CLOSED

It's a bit of a cat and mouse game with ngram - Google doesn't provide an API so it's all about scraping and keeping up with their obfuscation changes. I have to admit it's been a long time since I wrote this package so it might take me a while to get back up to speed and work out what's broken! I'll see what I can do - but no promises...

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Thanks again Sean! This package truly makes my life easier, and I'm really looking forward to using it!

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I have the same problem. Would be very grateful for a fix!!

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I have pushed a new version to GitHub (not yet to CRAN). Let me know if the problem has been resolved.

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Thanks for getting back to this. It still appears there is another issue now.

Error in pivot_longer(df, -Year, names_to = "Phrase", values_to = "Frequency") : could not find function "pivot_longer"

4. | ngram_single(phrases, corpus = corp, year_start = year_start, year_end = year_end, smoothing = smoothing, tag = tag, case_ins)
3. FUN(X[[i]], ...)
2. | lapply(corpus, function(corp) ngram_single(phrases, corpus = corp, year_start = year_start, year_end = year_end, smoothing = smoothing, tag = tag, case_ins))
1. | ngramr::ngram("dog")

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Hi - the package now requires tidyr, so try installing that package first and see if that helps.
Sean.

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I've also changed the way the tidyr function is called so you may need to reinstall ngramr too.
Sean.

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Thanks Sean - when explicitly loading "library(tidyr)" after loading library(ngramr) this was able to work!

library(devtools)
install_github("seancarmody/ngramr")

library(ngramr)
library(tidyr)

dog <- ngramr::ngrami("dog")
dog

There might be some point in your package where you can state tidyr as a dependency, so it loads automatically for your users.
In my package rhymebrainR, I have a devstuffs.R file, which contains the following dependencies of my package. Potentially stating tidyr in this fashion will allow the package to load with your ngramr package.

# Get the dependencies
use_package("httr")
use_package("jsonlite")
use_package("curl")
use_package("attempt")
use_package("purrr")

One last note I'll make, is on your package description page, the command you have to install/load your package from GitHub doesn't seem to work with my version of R (perhaps this was a previous method?).

To install the package from your GitHub account, I had to use the following code:

library(devtools)
install_github("seancarmody/ngramr")

Lastly Sean - thanks for providing this fix - assuming you're in the States, it should technically still be my birthday - and it is a sweet gift at that!
I'm looking forward to using this package in one of my hobby projects! Thanks so much for fixing it!
~ Final edit, noticed you're another Aussie! In that case, cheers!

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Thanks for the feedback! I thought I'd updated the dependency on tidyr but my R package skills are a bit rusty so I did it in the wrong place. I'm hoping it works now without the explicit call to library(tidyr). If there are still problems, do let me know.

On the install_github, you're right, the syntax for the function has changed, so I've updated the README.

Enjoy and a belated Happy Birthday.

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Sorry about that! Result of poorly executed switch from the (old) ddply to dplyr Should be fixed now.

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Note: I've redeveloped a lot of the underlying code which will (hopefully) make it more robust and provide better warnings. If you have a chance, have a look at the development version and let me know if it causes any problems (note if you use the "tag" argument in ngram that won't work anymore - I've removed it). When I'm confident it's stable I plan to replace the master version and republish on CRAN.

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I'm glad it's working for you. I've just pushed an update to the development version with a new function chunk that could be helpful to speed up your process a bit. Here's how I'd use it:

tokens <- c("asynchronously","barware","bender", etc... )
ng <- bind_rows(lapply(chunk(tokens, 12), function(c, ...) {Sys.sleep(2); ngram(c, ...)}, year_start = 1960))

Googe's Ngram Viewer will allow up to 12 tokens and this chunks your bigger list into a list of chunks of length 12 to work on.

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