Installation: GNU Octave

Related lectures (32)

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Introduces Pandas, Numpy, and Matplotlib for data analysis and visualization in Python.

Covers the installation process of GNU Octave 3.8.0, a high-level interpreted language for numerical computations.

Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.

Covers NumPy arrays and their graphical representations using Matplotlib, focusing on array creation, manipulation, and visualization techniques.

Covers data visualization techniques, tools, and concepts for effective data representation.

Discusses numerical methods, focusing on stopping criteria, SciPy for optimization, and data visualization with Matplotlib.

Covers Principal Component Analysis for dimension reduction in biological data, focusing on visualization and pattern identification.

Delves into data physicalization, expressiveness, feminist visualization, and the balance between exploration and explanation in data visualization.

Introduces NumPy, focusing on array creation, manipulation, and its advantages for scientific computing.

Explores EPFL's doctoral theses history, data visualization, and the innovative D3 approach.