A collection of sloppy snippets for scientific computing and data visualization in Python. Notice: For an update tutorial on how to use minisom refere to the examples in the official documentation. The Self Organizing Maps (SOM), also known as Kohonen maps, are a type of Artificial Neural Networks able to convert complex, nonlinear statistical relationships between high-dimensional data items into
A collection of sloppy snippets for scientific computing and data visualization in Python. A boxplot (also known as a box-and-whisker diagram) is a way of summarizing a set of data measured on an interval scale. In this post I will show how to make a boxplot with pylab using a dataset that contains the monthly totals of the number of new cases of measles, mumps, and chicken pox for New York City d
A collection of sloppy snippets for scientific computing and data visualization in Python. In Network Analysis the identification of important nodes is a common task. We have various centrality measures that we can use and in this post we will focus on the Betweenness Centrality. We will see how this measure is computed and how to use the library networkx in order to create a visualization of the
A collection of sloppy snippets for scientific computing and data visualization in Python. A Bloom Filter is a data structure designed to tell you, rapidly and memory-efficiently, whether an element is present in a set. It is based on a probabilistic mechanism where false positive retrieval results are possible, but false negatives are not. In this post we will see a pure python implementation of
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