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twitter-topics's Issues

CountVectorizer error

raise ValueError("empty vocabulary; perhaps the documents only"
ValueError: empty vocabulary; perhaps the documents only contain stop words

Why am i getting this error, min_df = 2 and everything else seems to be right

Algorithm does not output anything

Hey there!
First of all, Thank you so much for providing your code and the sample data set. I highly appreciate that. I tried to run the code with the given data sets. Both algorithms
twitter-topics-from-json-text-stream.py
and
extract-json-to-text-stream.py
do not output anything. Do you have an idea what I do wrong?
That's how I call, e.q. the last one:
python2 extract-json-to-text-stream.py test.json output.json.txt
The files are created, but they are empty and the algorithm (first one) runs roundabout 5-10 seconds (dependent on the example data set 1k, 10k or 100k)

Thank you. I hope you have an idea what is going on

My best!

Error while running the code

I am getting this error at countvectorizer
"max_df corresponds to < documents than min_df")
ValueError: max_df corresponds to < documents than min_df

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