Paul Heckmann | Software Developer / Data Scientist

As a PhD candidate in geoscience about to graduate, I have discovered my passion for data treatment and visualization. Throughout my academic journey, I have gained a foundation in data analysis, statistical methods, and programming. However, it was during my graduate studies that I realized my interest in exploring and visualizing data to uncover insights and patterns. I am passionate about using data to solve real-world problems and creating insightful visualizations that communicate complex data in a clear and understandable way. This portfolio is a reflection of my expertise and experience as a data scientist. It showcases some of my most interesting projects and highlights my approach to data analysis and visualization. I hope it provides you with insight into my capabilities as a data scientist and inspires you to explore the vast potential of data science.

Heckmann, P., Palinkaš, S. S., Hansen, H., Iacono-Marziano, G., Rajič, K., Forien, M., and Bergh, S. G.: Petrogenesis of zoned and unzoned mafic pegmatites: An insight from the Palaeoproterozoic mafic-ultramafic Hamn intrusion, Northern Norway, Lithos, 428, 106818, 2022. https://doi.org/10.1016/j.lithos.2022.106818

Heckmann, P., Iacono-Marziano, G., and Strmić Palinkaš, S.: An experimental study of the effect of water and chlorine on plagioclase nucleation and growth in mafic magmas: application to mafic pegmatites, European Journal of Mineralogy, 35, 1111–1124, 2023. https://doi.org/10.5194/ejm-35-1111-2023

Heckmann, et al., Sulfur isotopes, trace element, and textural analyses of base metal sulfides Paleoproterozoic mafic ultramafic Hamn intrusion Northern Norway (in progress)

Heckmann, et al., Petrology Multimeter (in progress)

Research Stay at Insitut des Sciences de la Terra d'Orleans, France

PhD Candidate at UiT The Arctic University of Norway

Master of Science in Geosciences from Georg-August-Universität Göttingen

Bachelor of Science in Geosciences from Georg-August-Universität Göttingen (with distinction)

Python (Pandas, Matplotlib, Scikit-learn)

JavaScript certificate

IN PROGRESS: React

IN PROGRESS: React Native

Snowflake certificate

SQL (PostgreSQL) certificate

Git

HTML, CSS

LaTex, Jabref

Fluent: German, English

Basics: Spanish, Norwegian

Historical weather data analysis

Click here to go to the app

Click here to go to the github repository

This streamlit app is based on publicly free available weather data from the German Meteorological Service (Deutscher Wetterdienst) and a shapefile from the German Federal Agency for Cartography and Geodesy (Bundesamt für Kartographie und Geodäsie). It offers an interactive visualization of weather data from the different german states, in terms of air temperature, precipitation and sunshine duration. The main purpose of this project was to test the python libraries geopandas in combination with the visualization library matplotlib and streamlit.

Music Billboard 100 top-ten singles Audio Analysis

Click here to go to the app

Click here to go to the github repository

This project was inspired by a blog post by Robert Ritz. In the blog post, Robert Ritz describes how one can scrape the Billboard Hot 100 top-ten singles from wikipedia and utilise the Spotify API via spotipy to build an app where the user can choose the years to receive the Spotify playlist link the the top songs of that years. In my project, I started to utilise the Ritz's scaping function to get a the data for the Billboard Hot 100 top-ten singles with the spotify (uris) to later be merge the list with audio analytic data from the spotify API via spotipy. The goal of the project is to see if through the last decates one can see a change in the polular key or beat-per-minute.

Fitness data visualization

Click here to go to the app

Click here to go to the github repository

I recreated the fitness data display from Garmin Connect for this project. The aim of this work was to learn how to dreat datatime data and create interactive plots with the visualization library altair