Présidents de session
Community specific analysis: Python introduction, useful packages and libraries for data scientists
- Tamas Gal
Community specific analysis: Numpy
- Tamas Gal
Community specific analysis: Pandas
- Tamas Gal
Community specific analysis: Matplotlib
- Tamas Gal
Community specific analysis: Reproducible science in practice
- Arturo Sanchez Pineda (LAPP)
Community specific analysis: Reproducible science in practice
- Arturo Sanchez Pineda (LAPP)
Community specific analysis: Scikit-HEP
- Eduardo Rodrigues (University of Liverpool)
Community specific analysis: Scipy
- Axel Donath
Community specific analysis: Gammapy
- Axel Donath
Community specific analysis: An introduction to gravitational wave data analysis
- Alberto Iess (INFN Roma Tor Vergata)
Community specific analysis: Astropy
- Axel Donath
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Tamas Gal09/06/2021 09:00
Python: this talk gives an overview about the Python language in the scientific context. It shows its strengths and weaknesses and also introduces a few important libraries which should be part of a scientist's toolbox.
Numpy: Numpy has built the foundation of numerical computing in Python. Without this package, Python could not have reached such a level of popularity in data science. This...
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09/06/2021 11:00
Numpy: Numpy has built the foundation of numerical computing in Python. Without this package, Python could not have reached such a level of popularity in data science. This course will teach the basics of Numpy and shows how to utilise it to solve numerical problems.ic computing.
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Tamas Gal09/06/2021 14:00
Pandas: Pandas is a great library to work with tabular data and perform high-level statistical analyses with them. In this short lecture, we will explore how to load, transform, combine and analyse datasets using the powerful Dataframe structure.
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Tamas Gal09/06/2021 15:30
Matplotlib: Visualisation is a key component of scientific work. Matplotlib is one of the most popular libraries to create static and interactive graphs with Python and offers endless possibilities to tweak those in detail. This lecture is a short introduction to the basics of working with Matplotlib.
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Arturo Sanchez Pineda (LAPP)10/06/2021 09:00
It refers to a series of principles, techniques, tools and practical considerations that allow the documentation, recording and preservation of data analysis pipelines — enhancing the possibilities of collaborations across borders and increasing the probabilities of replicating results by others (and yourself) in the future. Reproducibility involves using standard and well-established...
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Arturo Sanchez Pineda (LAPP)10/06/2021 11:00
It refers to a series of principles, techniques, tools and practical considerations that allow the documentation, recording and preservation of data analysis pipelines — enhancing the possibilities of collaborations across borders and increasing the probabilities of replicating results by others (and yourself) in the future. Reproducibility involves using standard and well-established...
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14/06/2021 15:30
Data analysis in High Energy Physics (HEP) has evolved considerably in recent years. In particular, the role of Python has gained much momentum, sharing at present the show with C++ as a language of choice. Several (community) domain-specific projects have seen the day, providing (HEP) data analysis packages that profit from, and talk to well with, the huge Python scientific ecosystem, which...
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Tamas Gal
Python: this talk gives an overview about the Python language in the scientific context. It shows its strengths and weaknesses and also introduces a few important libraries which should be part of a scientist's toolbox.
Numpy: Numpy has built the foundation of numerical computing in Python. Without this package, Python could not have reached such a level of popularity in data science. This...
Go to contribution page