Nltk Manual Download
Raphael Dyen
I am working with a computer that can only access to a private network and it cannot send instrunctions from command line. So, whenever I have to install Python packages, I must do it manually (I can't even use Pypi). Luckily, the NLTK allows my to manually download corpora (from here) and to "install" them by putting them in the proper folder (as explained here).
However, in most situations where the issue is due to an incorrect nltk_data install, NLTK will notify you that there was an issue with the install (and that you must perform e.g. nltk.download("wordnet") to resolve it)
A new window should open, showing the NLTK Downloader. Click on the File menu and select Change Download Directory. For central installation, set this to C:\nltk_data (Windows), /usr/local/share/nltk_data (Mac), or /usr/share/nltk_data (Unix). Next, select the packages or collections you want to download.
I guess the downloader script is broken. As a temporal workaround can manually download the punkt tokenizer from here and then place the unzipped folder in the corresponding location. The default folders for each OS are:
Step 1: Look up corresponding corpus in _data/. For example, it's Punkt Tokenizer Models in this case; click download and store in one of the folder mentioned above (if nltk_data folder does not exist, create one). For me, I picked 'C:\Users\username/nltk_data'.
Step 2: Notice that it said "Attempted to load tokenizers/punkt/english.pickle", that means you must create the same folder structure. I created "tokenizers" folder inside "nltk_data", then copy the unzipped content inside and ensure the file path "C:/Users/username/nltk_data/tokenizers/punkt/english.pickle" valid.
you should add python to your PATH during installation of python...after installation.. open cmd prompt type command-pip install nltkthen go to IDLE and open a new file..save it as file.py..then open file.pytype the following:import nltk
if you have already saved a file name nltk.py and again rename as my_nltk_script.py. check whether you have still the file nltk.py existing. If yes, then delete them and run the file my_nltk.scripts.py it should work!
.raw() is another method that exists in most corpora. By specifying a file ID or a list of file IDs, you can obtain specific data from the corpus. Here, you get a single review, then use nltk.sent_tokenize() to obtain a list of sentences from the review. Finally, is_positive() calculates the average compound score for all sentences and associates a positive result with a positive review.
In the provided code, we first imported the necessary nltk modules, retrieved the set of English stop words, tokenized our text, and then created a list, wordsFiltered, which only contains words not present in the stop word list.
We know that our tool's Python script is going to rely on NLTK. We also know that we're going to want to share this tool with other people. We could manually add NLTK to the Python distribution included with Alteryx and the tool would work on our machine, but then would fail on any machine that didn't go through the same manual NLTK installation process. To solve this issue, the Python SDK has recently been enhanced with the ability to leverage Python virtual environments. The documentation turned out to be quite easy to follow - it was a quick 2 step process. First, create the virtual environment:
The analysis showed that the obituaries section was the most male-dominated section in the paper over this period of time. After manually counting, I confirmed that 24 of 29 obituaries in this time frame (2018-03-13 to 2018-03-20) were for men. In a pure coincidence, this reminded me that on March 8th the New York Times noted that women have been historically underrepresented in their obituaries. While I hadn't set out to analyze the obituaries, the stark nature of the results led me down that path, and it turns out that the Times has performed their own comprehensive analysis.
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