Are you swiping Tinder on hard Mode?

In this post, I share results from a novel experiment on Tinder. We collect a unique dataset while swiping Tinder using different profile names and with heterosexual and homosexual search preferences. From this, we uncover vastly different patterns in matching and messaging behavior between sexes. More dramatically, we find strong evidence for name based discrimination on Tinder.

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Interactive plots of large data sets made easy: Datashader

When plotting huge data sets using Python while keeping interactivity, Datashader is paramount. In this post, I demonstrate the abilities of this powerful and convenient library. We use an unique dataset containing a whole year of shared bike usage in Cologne to plot over a million locations on a map.

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Interactive maps with Python made easy: Introducing Geoviews

Do you want to build map visualizations in Python? Look no further than GeoViews. It is not only super simple to use but also offers several interactive features that make your visualization stand out. Using geo spatial data from our bike rental data set we explore some of the possibilities.

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A match made in heaven: Tinder and Statistics — Insights from an unique Dataset of swiping

Tinder is hugely popular and offers fascinating data on online dating. Still, there are barely any analysis of tinder data. In this endeavor we change that, by analyzing an unique dataset of tinder profiles. The data contains thousands of female and male profiles collected by swiping as a hetero- and homosexual male. Using descriptive statistics, visualization and natural language processing we uncover exciting patterns.

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Include variables in Markdown cells of JupyterLab Notebooks

Including variables in a JupyterLab Notebook's Markdown cells seems like a basic thing. Turns out it is not. It's simply not yet supported out of the box. Here is how to do it anyways. Moreover, learn how to selectively hide code cells when exporting your Notebook. Improve the aesthetics and dynamic capabilities of your Notebook by using this simple approach.

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Build custom skills for Alexa with Python and Flask-Ask

Alexa is Amazon’s voice guided assistant. It is affordable, has many helpful functions, and can be enhanced with custom skills. Are you missing a feature? Become a developer and implement it yourself! With basic Python knowledge you can quickly learn how to build your own skills.

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Investigating bike rentals in Cologne - Part 2: Map visualization

In this multi part post, I will take a look at the bike rental system in Cologne. In the first part we applied web-scraping and XML parsing to retrieve data and build a dataset of bike locations. Now, we will deal with geospatial tools and map visualization in order to search for interesting patterns in the bike-rental data.

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Solving unconfirmed Bitcoin transactions in Electrum

There are a handful solutions for dealing with unconfirmed bitcoin transactions. However, depending on the case only a few of those might be viable. In this post, I describe how to apply the child pays for parent method in electrum. It is a solution that works most times.

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