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This advanced course will provide knowledge on how to visualize your data using Python. By using application-oriented examples, we will provide you with all the necessary knowledge about the Python libraries Matplotlib and Seaborn in order to implement complex graphics quickly and easily.
In addition to the creation of basic visualizations, various customization options are covered. These can be used to shape the appearance of the graphic according to personal requirements. General techniques and methods of visualization will be taught, too. The course deals with the following topics:
- Graphics with Matplotlib and Seaborn
- Various one- and two-dimensional graphic types
- Customization of graphics through individual elements
- Control of the appearance
- Graphic export
- Principles for creating good graphics
- Tips & tricks
During the course, participants will learn how to visualize their data in an informative and appealing way with Python.
This is a course for advanced Python users. The course is aimed at people who have already had some programming experience with Python and have a basic understanding of statistics. Python beginners should participate in our workshop Introduction to Data Science with Python
ABOUT THE TRAINER
Florian Schmoll studied Mathematics at the University of Kassel and has been working as a Data Scientist at eoda since 2017. Working as a consulting Data Scientist he carries out projects in different sectors such as industry or commerce. In addition to his project work he has worked as a trainer for Machine Learning and Time Series analysis in R and Python.
eoda GmbH is an IT company specialized in Data Science working towards the mission “Data Science Empowerment”. As a pioneer in Germany for open-source programming languages and as a Full Service Certified Partner of RStudio and Anaconda, eoda offers a holistic training and qualification concept – with a performant toolset around programming languages like R, Python and Spark.
The interdisciplinary team of eoda combines deep knowledge of business processes with the competent application of the appropriate analytic methods and can draw from experiences in cross-disciplinary use cases. Learn more about eoda