Python/Jupyter

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GESIS Notebooks

Have a Binder-Ready repository? With GESIS Notebooks, turn this repository into a persistent Jupyter environment, allowing you to continue your analysis from anywhere at any time.

This service is intended for use by social scientists. You can build and launch all binder-ready projects without logging in. If you want to have more persistent projects, you need to log in.

GESIS Training

At GESIS we offer a wide range of events, especially training courses on empirical social research methods. Our theory founded and hands-on courses develop participants’ methods skills and are aimed at both early career and senior researchers from Germany, Europe, and the whole world.

Library Carpentry

Library Carpentry workshops teach people working in library- and information-related roles how to:

  • Cut through the jargon terms and phrases of software development and data science and apply concepts from these fields in library tasks;
  • Identify and use best practices in data structures;
  • Learn how to programmatically transform and map data from one form to another;
  • Work effectively with researchers, IT, and systems colleagues;
  • Automate repetitive, error prone tasks.
Harvard University: online courses

About 200 online courses dedicated to various disciplines including humanities and social sciences.

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Utrecht University : workshop data handling in R

Educational materials used in the workshop 'Data handling in R' run at Utrecht University

It focuses on raw data handling using R, though a Jupyter notebook, run on CoCalc or SURF.

Contents covered: 

- Naming conventions for files

- Ordering scripts

- Layout of scripts

- Commenting code: best practices

Code Reuse and Modularity in Python

Computer programs can become long, unwieldy and confusing without special mechanisms for managing complexity. This lesson will show you how to reuse parts of your code by writing functions and break your programs into modules, in order to keep everything concise and easier to debug.

 

Core Curriculum

The lessons introduce terms, phrases, and concepts in software development and data science, how to best work with data structures, and use regular expressions in finding and matching data. We introduce the Unix-style command line interface, and teach basic shell navigation, as well as the use of loops and pipes for linking shell commands. We also introduce grep for searching and subsetting data across files. Exercises cover the counting and mining of data. In addition, we cover working with OpenRefine to transform and clean data, and the benefits of working collaboratively via Git/GitHub and using version control to track your work.

Videolectures

Video presentations on CLARIN topics given in various contexts, such as the CLARIN Annual Conference, CLARIN workshops, research institutions and universities.

JOSS

The code for the JOSS submission tool

How to build a digital edition web app

This series of tutorials describes one approach on how to develope a web application to publish digital editions.