Introduction You may have heard of the Kelly bet allocation strategy. It is a system for correctly exploiting information or bias in a gambling situation. It is also known as a maximally aggressive or high variance strategy, in that betting more than the Kelly selection can be quite ruinous. I […] [...Read more...]

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Introduction A neat bit of “engineering mathematics” is solving recurrence relations. The solution method falls out of the notation itself, and harkens back to a time where formal sums were often used in place of vector subscript notation. Unfortunately the variety of such solutions is small enough to allow teaching […] [...Read more...]

The Pandas data frame is probably the most popular tool used to model tabular data in Python. For in-memory data, Pandas serves a role that might normally fall to a relational database. Though, Pandas data frames are typically manipulated through methods, instead of with a relational query language. One can […] [...Read more...]

I’ve been seeing a lot of hot takes on if one should do data science in R or in Python. I’ll comment generally on the topic, and then add my own myopic gear-head micro benchmark. I’ll jump in: If learning the language is the big step: then ... [...Read more...]

I’ve just started experimenting with the Polars data frame library in Python. I really like the programmable API it exposes. In fact I am starting an experimental adapter from the data algebra to Polars. When this is complete one can use the data algebra to run the same data ... [...Read more...]

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I have a new theoretical finance note up: an appreciation of Cover’s universal portfolio in Python. [...Read more...]

I am pleased to announce the 0.9.0 release of the data algebra. The data algebra is realization of the Codd relational algebra for data in written in terms of Python method chaining. It allows the concise clear specification of useful data transforms. Some examples can be found here. Benefits include […] [...Read more...]

I have a new intermediate introduction on the data algebra up here: Using the data algebra for Statistics and Data Science. The data algebra is a tool for data processing in Python which is implemented on top of any of Pandas, Google BigQuery, PostgreSQL, MySQL, Spark, and SQLite. It allows […] [...Read more...]