Examples for Jupyter Notebooks
A space to collect and share Jupyter notebooks.
All notebooks should ideally work without any extra files, use only standard Python libraries (pandas, scikit-learn, etc.), and gather their data from the web. An introduction into Jupyter Notebooks and Python is also available online.
Contributing to this Repository
To contribute a notebook, please
- fork this project,
- add your notebook and
- create a merge request.
If you did everything correctly, you should see your changes in the list of merge requests. After your request has been approved, your notebook will be available in this repository. Thank you for contributing!
List of Notebooks
So far, notebooks are listed alphabetically and stars shall indicate their difficulty (☆ = simple, ☆☆ = advanced, ☆☆☆ = sophisticated):
- AirBnB Use in Berlin
- exemplary (and excellent) term paper for the module “Datenanalyse & -auswertung” (☆☆)
- Amazon reviews
- crawling web sites with Scrapy, processing JSON data, basic statistics and visualisation (☆☆)
- Computer-generated art
- translation, scaling and composition of functions (☆☆)
- Classification
- basic machine learning classification example (☆)
- Community detection
- applying community detection algorithms to network graphs (☆☆)
- Crawling a blog
- crawling web sites, basic text mining, basic statistics and visualisation (☆☆)
- Distances
- comprehensive interactive simulation of recovering information from noisy data (namely, point positions given their noisy distance matrix) (☆☆☆)
- DraCor
- retrieving data from a REST API, text transformation and classification (☆☆)
- Exponential smoothing
- using Jupyter’s interactive widget to explore exponential smoothing (☆)
- Hamming
- a graph visualising a strange type of word similarity (☆)
- Jupyter demo
- demo of some Jupyter features useful for creating learning material (☆)
- Mondrian
- turtle graphics, recursion, art (☆☆)
- Nikolaus
- graph traversal and drawing (☆☆☆)
- Statistics top 50 faculty
- exploratory statistical analysis of the dataset of 2200 faculty in 50 top US computer science graduate programs (☆☆)
- analysing Twitter data (raw JSON from Twitter’s API) (☆)
- Wikipedia
- plotting the depth and number of articles of different Wikipedia language editions (☆)