Analyzing linguistic data: links

List of software we will use in the class

Python and Python packages:

• • We strongly recommend installing Anaconda, as that includes Python along with all Python packages we need.

    • If you install anaconda, you will have to add gensim. Here is a tutorial on how to add a package to Anaconda: https://docs.anaconda.com/anaconda/navigator/tutorials/manage-packages/#installing-a-package

    • Please do this, and choose to add gensim.

  • lternatively, you can individually install:

    • Python: https://www.python.org/downloads/ Any version >= 3.4 should be fine.

  • Jupyter notebooks: https://jupyter.org/

    • pandas: https://pandas.pydata.org/

    • numpy: https://numpy.org/

    • matplotlib: https://matplotlib.org/

    • Statsmodels: https://www.statsmodels.org/stable/index.html

    • NLTK: Installing NLTK itself: http://www.nltk.org/install.html You also need the NLTK data, see http://www.nltk.org/data.html

  • gensim

To test your Python installation, use this Jupyter notebook.

Slack:

We are using Slack for in-class discussions. Please see Canvas for the link to the class Slack space.

Tips and tricks:

Learning Python:

• • How To Think Like A Computer Scientist is a very good and accessible online Python textbook.

  • (Caution: It uses Python 2 rather than Python 3. One main difference you will note is that they omit the () around the print() command.)

  • A Python tutorial

Jupyter notebooks:

• Jupyter notebook for data science tips and tricks

Fun with statistics

• • Language Log: a language and linguistics blog written by Mark Liberman and others

  • Bad science: Ben Goldacre's blog with lots of illustrations of what not to do in statistics

  • xkcd: A webcomic of romance, sarcasm, math, and language.

    • And then there's the RXKCD package.