This output is unexpected. The In returns the capitalize In from PorterStemmer's output.

>>> from nltk.stem import PorterStemmer
>>> porter = PorterStemmer()
>>> porter.stem('In')
'In'

More details on https://stackoverflow.com/q/60387288/610569

The documentation specifies:

The words and sentences properties are helpers that use the textblob.tokenizers.WordTokenizer and textblob.tokenizers.SentenceTokenizer classes, respectively.

You can use other tokenizers, such as those provided by NLTK, by passing them into the TextBlob constructor then accessing the t

The procedure for downloading the "en_vectors_web_lg" in spacy. by downloading and unzipping the file, and shifting it to the appropriate directory, as illustrated here is l

This is also on page 356.

from nltk.corpus import sentiwordnet as swn

good = swn.senti_synsets('good', 'n')[0]
Traceback (most recent call last):
File "", line 1, in
TypeError: 'filter' object is not subscriptable

Hello,

I am getting the following error message "error: package directory 'rake_nltk' does not exist" when installing rake-nltk with:
git clone https://github.com/csurfer/rake-nltk.git
python rake-nltk/setup.py install :

I also tried the option pip install rake-nltk but the installation also fails:

File "/tmp/pip-build-2zTHYP/rake-nltk/setup.py", line 17, in _post_install
import

Just an idea:
I think README would be the best thing to run LDA on, since it contains a pretty good description of the project. Projects without README should be penalised either way. Often times the repository description is too short to describe in detail what the repository is all about.

#840 updated the stop module (cltk.stop.stop) but its docs was not updated.

It seems that a child class of BaseCorpusStoplist must have attributes vectorizer and tfidf_vectorizer like in cltk.stop.latin

@stevenbird
Initial release of the corpus available at: https://doi.org/10.7488/ds/1411

Suggested NLTK name: ARCOSG

I have updated and corrected the corpus for inclusion in NLTK. (The one at the link above is older and shouldn't be used).

Corpus reader code verified:
`arcosg = LazyCorpusLoader(
'arcosg',
CategorizedTaggedCorpusReader,
r'.*.txt',
cat_file='cats.prn',

Text version

master

Orange version

master

Expected behavior

I search for a word in Corpus Viewer and get some documents. I would then expect the output to be those documents that I also select in the documents list. It would behave more like Data Table.

Actual behavior

The output is always documents that match search regardless of what is selected in the documents li