Pygrunn 14 article #34
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| decided to show how these libraries are used to solve simple CL tasks. | ||
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| First, I `covered`__ `Zipf's law <http://en.wikipedia.org/wiki/Zipf%27s_law>`_ | ||
| and showed that it holds for an English text. As a homework, I asked whether the |
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First, I covered Zipf's law, which states that the frequency of any word in a corpus of texts is inversely proportional to its rank in the frequency table. With help of pandas??? I showed that it holds for an English text.
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| Conclusion |
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Maybe you could add a few closing words on Pygrunn, maybe something relating to linguistics as well. Or if you don't want to add anything you could just change Conclusion to References & keep the link below.
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i still want to write a conclusion, but i was too tired to write it :) |
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@Filip-Ter did you like the draft? |
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yeah it looks good |
| `My presentation`__ started as a demonstration of the modern pythonic scientific | ||
| tools (my subjective classification): | ||
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| __ http://nbviewer.ipython.org/urls/bitbucket.org/dimazest/phd-buildout/raw/tip/notebooks/pygrunn14.ipynb |
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It looks like the notebook is not loading.
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The article is improving!
Still the notebook is not loading. It is not found on the server.
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strange, it works for me, maybe there are some problems on the server. I'll give a link to the original file and to the rendered version.
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we can use word frequencies available here http://wacky.sslmit.unibo.it/doku.php?id=frequency_lists
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| .. image:: {filename}/static/images/016-en_zipf.png | ||
| :align: center | ||
| :alt: English word frequency counts on the log-log scale. |
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github doesn't know how to find it, but our blog engine does :)
This article has two parts:
while the first is more or less covered the second need more attention