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Complete mini project 3 #3

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alakmazaheri
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victorbianchi added a commit to victorbianchi/TextMining that referenced this pull request Oct 13, 2017

### Required Packages:
pip install nltk requests vaderSentiment
pip install matplotlib scikit-learn scip
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This is really minor, but these two lines came out as on the same line which made it initially difficult to understand that there were two commands. Make sure that your markdown styling is what you want it to be in the final product.

for text in all_texts:
wordlist = text.split()
for word in wordlist:
if(word not in allwords):
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No parentheses needed

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Overall, really good work. Each function has an informative docstring. Code is concise and clean.

@osteele
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osteele commented Oct 16, 2017

Re: "I found unit testing quite challenging for the data sets of this size and nature": one technique is to use a small test set for unit tests. For example, in GeneFinder, tiny sequences are used in the unit tests, in order to make them manageable and debuggable. (In GeneFinder, I would actually use smaller unit tests, as in the GeneFinder solution set.)

@osteele
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osteele commented Oct 16, 2017

There's substantial duplication between pull_texts.py (whose comment says it is called text_similarity.py 😄 ) and text_mining.py. Common functions can be factored out into a module that both scripts import. We'll go over this on Thursday.

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3 participants