Introduction to NumPy
08-29, 13:30–15:00 (Europe/Zurich), HS 118

This tutorial will provide an introduction to the NumPy library intended for beginners.

NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.


This tutorial will provide an introduction to the NumPy library intended for beginners.

You are encouraged to type along with me. For this you bring your laptop with a Firefox 90+ or Chromium 89+ installed. We will work through this repository: https://github.com/maikia/numpy-demo

NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.

This tutorial will notably introduce the following aspects:

  • n-dimensional arrays (ndarray)
  • indexing of ndarray
  • operations on ndarray

Abstract as a tweet

Introduction to the NumPy library for scientific computing

Domains

General-purpose Python, Statistics

Expected audience expertise: Domain

none

Expected audience expertise: Python

none

Public link to supporting material

https://github.com/maikia/numpy-demo

Maria Teleńczuk, PhD, is a Data Scientist at Owkin and a PyLadies Paris Organiser.
At Owkin she works in a Federated Learning group where she investigates the strategies towards better analysis of and secure access to biomedical data.
Her experience varies from computational and experimental neuroscience to machine learning.
She taught Python at various courses and used it throughout her career.