The behavior of names and values in Python can be confusing. Like many parts of Python, it has an underlying simplicity that can be hard to discern, especially if you are used to other programming languages. Here I'll explain how it all works, and present some facts and myths along the way. Call-by-reference? Call-by-value? The answer will be clear!
Guido van Rossum, creator of the Python programming language, discusses type hinting in Python 3.5. With type hinting, programmers can use type annotations to provide tools like type checkers and IDEs with more information about the expected types of values and enable better static analysis. This talk was organized by ...
PyPy.js is an experiment in building a fast, compliant, in-browser python interpreter. By compiling the PyPy interpreter into javascript, and retargeting its JIT compiler to emit asmjs code at runtime, it is possible to run python code in the browser at speeds competitive with a native python environment. ...
In this tutorial we will give an introduction to two advanced data storage formats. HDF5 and NetCDF were designed to efficiently store the results of supercomputing applications like climate model outputs, or the data streams received from NASA's fleet of earth observing satellites. They provide a lot of optimizations concerning ...
PyData SV 2014
In the past two years, there has been incredible progress in Python data visualization libraries, particularly those built on client-side JavaScript tools such as D3 and Leaflet. This talk will give a brief demonstration of many of the newest charting libs: mpld3 (using Seaborn/ggplot), nvd3-python, ggplot, Vincent, ...
PyData SV 2014
Many real-world datasets have missing observations, noise and outliers; usually due to logistical problems, component failures and erroneous procedures during the data collection process. Although it is easy to avoid missing points and noise to some level, it is not easy to detect wrong measurements and outliers ...