The ways statistics are taught in many universities is detrimental to science

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I originally planned to write an article about Bayesian vs. Frequentists Methods. Midway through my writing, however, I realized that the issue isn’t really understanding the difference and then “choosing” aside. Both schools of thought have good reasons to be applied to one setting or the other. In some cases, these seemingly different ways of viewing data and the world are not even that different.

Reading through some articles and books about Bayesian Methods made me realize how useful these could be, but also how little I learned about them in my university stats education. I learned about Bayes Theorem…

An overview of the fundamental formula for Bayesian Statistics

When I sat in my second stats class in university I was introduced to Bayes’ Theorem, I naively thought it was just another formula to use for a given task. I quickly discovered that there was a whole school of thought and statistics I had never heard of. Later I discovered that the Bayesian way of thinking really appealed to me. I also realized that this formula I’d learned by heart to do well on my first exam, had many shapes and forms and more use cases than I could have imagined. I want to share these shapes and forms…

Hands-on Tutorials

Using the spotify library to create a version of Spotify’s Duo Mix

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Spotify offers a Duo Subscription which comes with a unique playlist called Duo Mix. This playlist is supposed to be for both users and combine their music tastes.

My girlfriend and I were eager to see what this playlist was all about. We started listening to it, but it somehow felt a little off. The artists were “correct” but the songs were not, the playlist hardly featured the songs we both actually listened to. It also jumped between styles pretty hard, going from a chilled jazzy song into techno, rap, or metalcore (okay, that might be a little on me…

Three approaches you can use to bring structure to your learning and portfolio projects

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Projects are a great way to learn Data Science. They provide a meaningful, self-guided way to improve your skills and possibly solve real problems for you and others. Projects are also a great way to showcase your skills in a portfolio. While there are some small projects that you just “do” in a day or two to get familiar with certain skills, libraries or topics there may be projects that are a little larger and require a little more upfront planning.

I have made the mistake of just starting a project and then losing track of all the little tasks…

Easy deployment and public hosting with Streamlit and Streamlit Sharing

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You’ve analyzed a data set and found interesting insights, you have built a machine learning pipeline, but so far they just live within your jupyter notebook. If others want to view your work they have to read through your notebook and view every output, that’s only ideal in a few cases. It’s time to take your work and showcase it interactively.

This does not have to be hard and you don’t require the help of a front-end developer. You, as a data scientist or someone on the path to becoming one, can deploy and host your project or application.


Two quick and easy ways to read in data from Google Sheets without using the Google Sheets API

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Google Sheets is a common alternative to Microsoft Excel and is especially useful if you wish to work collaboratively on your spreadsheet or share your data. I want to quickly share two ways of reading Google Sheets data into a pandas DataFrame through the .read_csv() method without having to safe the sheet locally first or having to use the GoogleAPI.


All you need is a Google Sheets file with one or more sheets and of course some data. The file needs to be set to the sharing option which allows everyone with the link to view the data.

How to use the Spotify API and spotipy library to filter Spotify’s recommendations.

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Music plays a large role in many people’s lives, it’s hard to imagine a day without it. I, like many others mainly consume it through streaming on Spotify. If you ever scrolled down to the end of your playlist you have met Spotify’s recommendations. Once in a while they seem spot on, at other times I wonder whether the recommender system took a wrong turn somewhere. But maybe that’s just me and my diverse taste in music.

If you are satisfied with your recommendations you can still use this article to learn how to use the Spotify API with spotipy…

The catalog of resources is endless, here are my recommendations

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There is a vast and growing number of Data Science resources. It can be hard to find the best ones for you. It may even be hard to find the right “Roadmap for Data Science” or “Top Skills to Learn for Data Science”.
I don’t claim to have the best resources or the correct path to a career in Data Science. What I have is a list of useful resources and if even one of them furthers your learning my goal is accomplished. …

A rejection is more than just a ‘no’ from a company you applied to

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The Data Science application process can seem very daunting, especially if you are just trying to break into the field and don’t come from a “traditional” background like computer science or math. It certainly sometimes does for me.

There are many factors that play into that feeling. One of them certainly is the application process itself. Even if you heard back from companies and are invited to interviews, tests etc. you might feel uncomfortable and lack confidence in your acquired skills.

Now before I go on, this is not an actual guide on how to technically fail an interview or…

Good Data Visualization requires more than your code and good color choice

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You probably already created some data visualizations when you learned how to use a library such as matplotlib or plotly. Maybe you even frequently use visualizations for exploratory data analysis (EDA) or dashboards. Or you are just a beginner and still in the process of figuring everything out. Wherever you are in your journey, I want to invite you to look past the code and discover the basic qualities of great data visualizations, so that you can use them as well.

“Most of us need to listen to the music to understand how beautiful it is. But often that’s how…

Merlin Schäfer

Data Scientist at StackFuel with a psychology background. Interested in all things “data”, machine learning and AI.

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