This course is part of our Python Summer School. We will offer courses throughout the week from August 10–14.
You can sign up for one course or as many as you like.

Python for Absolute Beginners Part 1 & 2 are our core courses. After completing these (or if you already have Python knowledge equivalent to the course material), you can join all other Python courses in our Summer School.

You can find all of our course materials here: https://kubdatalab.github.io/python

And sign up for more courses here: https://kubkalender.kb.dk/calendar/datalab

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In the Python for not quite Absolute Beginners courses, we expand on previous learning to write more structured and reliable programs. Before you attend these courses, make sure you have completed Python for Absolute Beginners Part 1 and 2 or are familiar with its topics.

In this workshop, you gain knowledge about how to work with texts as data using the library pandas. We will use fairy tales as our example material and combine many of them into a single dataset. 

You will gain knowledge about: 

• what a dataset of texts is in practice
• how a DataFrame can be built from a folder of text files
• how to combine multiple DataFrames using pd.concat
• how to apply functions to text with .apply (for example, for text cleaning)
• how to calculate simple metrics such as word count and TTR (type-token ratio)
• how to compare authors using groupby (Split-Apply-Combine)
• how to visualise simple patterns (for example, average word length by author)
• how to save the data for further analysis

By the end of the workshop, you will have a structured dataset that you can use in Workshop 2 and in your own projects. 

Practical information: We will be working in Jupyter Lab / Jupyter Notebook, which requires some installation, but you can also work in either Google Colabs or ERDA which require only a Google or KU account, respectively. For more information and help, consult "Install & Run Python" on the course page:
https://kubdatalab.github.io/python/docs/howto/setup.html