Notebooks

Notebooks am IBI

All art classification clustering crawling daa datamining datavis dracor fca graph image integerlinearprogramming jupyter literature optimization search similarity statistics student tabular text trie turtle web wikipedia

Airbnb Use Berlin ★★★ German
by Juliane Köhler

Untersuchung der Einflüsse auf Übernachtungspreise, Bewertungen, Absagen, etc. von Airbnb-Inseraten in Berlin.
Amazon Reviews ★★★ English
by Michael Paris

Learning to analyze web data by analyzing Amazon reviews with Python.
Art ★★☆ English
by Robert Jäschke

Creating an artwork inspred by Peter Saville's cover of the Joy Division album Unknown Pleasures.
Das Haus vom Nikolaus ★★★ German
by Robert Jäschke

Wir suchen alle möglichen Lösungen für das Zeichenspiel "Das Haus vom Nikolaus".
Dashboard ★★☆ English
by Robert Jäschke

This notebooks shows an example of how to create a dashboard for data exploration using plotly dash.
Textklassifikation mit DraCor ★★☆ German
by Robert Jäschke

In diesem Notebook testen wir, inwiefern sich die Autor:innen von Dramen anhand ihrer Texte identifizieren lassen.
Gender of Characters in Dramas ★★★ German
by Janina Pingel & Vivian Schlosser

Untersuchung der Beschaffenheit der weiblichen Repräsentanz anhand der landesspezifischen DramaCorpora Deutschlands und Frankreichs.
FCA & DraCor ★★☆ English
by Robert Jäschke

We want to analyse which patterns can be discovered when we consider which characters speak in scenes of different plays. Therefore, we extract the corresponding information from DraCor and analyse it using Formal Concept Analysis (FCA).
Hamming Similarity ★☆☆ English
by Robert Jäschke

This notebook explores a (probably slightly weird) similarity measure for strings.
Jupyter Demo ★☆☆ German
by Robert Jäschke

Dieses Notebook enthält Beispiele für verschiedene Anwendungsfälle von Jupyter-Notebooks.
Digital Mondrian ★★☆ English
by Robert Jäschke

This notebook aims to automatically create images similar to those of Piet Mondrian.
Analyzing Twitter Data ★☆☆ English
by Robert Jäschke

Different examples of Twitter data analysis for raw JSON fom Twitter's API.
Video Games Sales ★★★ English
by Jan Raoul Weber

Examine the sales of video games across different regions of the world to find out what video games are sold where and how the regional markets differ regarding preferences for e.g. Publishers.
Weinbewertungen Vivino ★★★ German
by Heike Wilhelm

Untersuchung von Weinbewertungen des Online-Weinmarktplatzes Vivino und ihrer Zusammenhänge mit Preis, Herkunftsland und Sorte der Weine.
World Risk and Happiness ★★★ English
by Helene Hellmich

A closer look at the World Worry Index of the "World Risk Poll 2021" to determine if there is a relationship between responses or demographic factors of the respondents and the worry index, then comparison to the demographic's ranking in the "World Happiness Report".
Classification ★☆☆ English
by Robert Jäschke

This notebook shows the basic steps to apply a machine learning classification algorithm. The example uses a decision tree but the procedure is very similar for other algorithms.
Community Detection in Networks ★★☆ English
by Michel Schwab

In this notebook we want to detect community in network graphs.
Crawling a Blog ★★☆ English
by Robert Jäschke

This Jupyter notebook shows how to crawl a web blog and extract information from it for later analysis.
Distances ★★★ English
by Robert Jäschke

If we have a number of devices in a room which can communicate with each other and measure the distance to each other (e.g., using round-trip time or signal strength), can we use that information to reconstruct the positions of the devices?
Exponential Smoothing ★☆☆ English
by Robert Jäschke

Using Jupyter's interactive widget to explore exponential smoothing.
Wörter im Faust ★★☆ German
by Robert Jäschke

Finding the most frequent nouns (verbs, adjectives, …) in Goethe's works (Faust in our example).
Machine Learning Recipes ★★☆
by Robert Jäschke

This notebook contains recipes for common machine learning tasks.
Optimization Example ★★★ English
by Frederik Arnold

This notebook shows an example of how to use linear programming to solve the following optimization problem using Python and the PuLP library.
Scraping Reviews ★★★ English
by Michel Schwab

We use the Python package scrapy to download all reviews of a literature blog.
Statistics Top 50 Faculty ★★☆ English
by Robert Jäschke

Basic statistics using the top 50 faculty dataset.
Comparing Wikipedia Language Editions ★☆☆ English
by Robert Jäschke

Wikipedia (as of January 2022) has more than 300 active language editions. We can compare (some of) these editions quantitatively and qualitatively using the table from https://meta.wikimedia.org/wiki/Wikipedia_article_depth.
Wikipedia RegEx ★☆☆ German
by Robert Jäschke

Anwendung von regulären Ausdrücken am Beispiel von Wikipedia-Seiten.
Visualizing Word Siblings ★★☆ English
by Robert Jäschke

Visualizing a graph of words that are related (similar) to each other.
Prefix Search ★★☆ English
by Frederik Arnold

Implementing prefix search using a Trie and comparing runtime with a naive approach.