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Networks (a.k.a graphs) are one of the most interesting areas of data science and have been subject to an explosion of interest in recent years. The ability to model the relationship between data points is powerful. This article introduces some basic concepts in network science and... Read more
I’ve been in a reflective mood lately, probably because it’s the end of a very eventful year. Change is all around us and technology is the enabler. On that note, I’ve been thinking a lot about my own experiences with technology-driven change in the reinsurance industry,... Read more
We at Saturn Cloud are dedicated to fast and scalable data science with Python. Often this looks like querying data that resides in cloud storage or a data warehouse, then performing analysis, feature engineering, and machine learning with Python. Snowflake is a scalable cloud data warehouse... Read more
Pandas is a popular data analysis library built on top of the Python programming language, and getting started with Pandas is an easy task. It assists with common manipulations for data cleaning, joining, sorting, filtering, deduping, and more. First released in 2009, pandas now sits as... Read more
Python has a rich collection of built-in data structures. These data structures are sometimes called “containers” or “collections” because they contain a collection of individual items. These structures cover a wide variety of common programming situations. In this recipe, we’ll look at how we can update a set by... Read more
Cloud computing is one of the major trends in computing today and has been for many years. Public cloud providers have transformed the start-up industry and what it means to launch a service from scratch. We no longer need to build our own infrastructure; we can... Read more
This article discusses chaining in Python. A few years ago, in a Q&A session following a presentation I gave on data analysis (DA) to a group of college recruits for my then consulting company, I was asked to name what I considered the most important analytic... Read more
The goal of a data analysis pipeline in Python is to allow you to transform data from one state to another through a set of repeatable, and ideally scalable, steps. Problems for which I have used data analysis pipelines in Python include: Processing financial / stock... Read more
Why pick one when you can use both at the same time? R is primarily used for statistical analysis, while Python provides a more general approach to data science. R and Python are object-oriented towards data science for programming language. Learning both is an ideal solution.... Read more