Python-bloggers

Raymond Hattinger is one of the core Python developers whose talks I’ve featured on my blog before. And rightfully so, as Raymond’s presentations are unarguably entertaining and deeply insightful from an technical perspective. In this recorded talk at the 2016 Annual Holiday Party for Python Devs in San Fransisco Bay Area, Raymond walks us through … Continue reading History of the Modern Python Dictionary – by Raymond Hattinger → [...Read more...]

Over the course of last week, I built a Python program that scrapes quotes from Goodreads.com in a tidy format. For instance, these are the first three results my program returns when scraping for the tag robot: Quote author source likes tags Goodbye, Hari, my love. Remember always–all you did for me. Isaac Asimov Forward … Continue reading Python Web Scraping: Quotes from Goodreads.com → [...Read more...]

I’ve been writing a lot about a category theory interpretations of data-processing pipelines and some of the improvements we feel it is driving in both the data_algebra and in rquery/rqdatatable. I think I’ve found an even better category theory re-formulation of the package, which I will describe here. In the earlier formalism our data transform … Continue reading A Richer Category for Data Wrangling [...Read more...]

In our recent note What is new for rquery December 2019 we mentioned an ugly processing pipeline that translates into SQL of varying size/quality depending on the query generator we use. In this note we try a near-relative of that query in the data_algebra. dplyr translates the query to SQL as: SELECT 5.0 AS `x`, … Continue reading Better SQL Generation via the data_algebra [...Read more...]

Introduction I would like to talk about some of the design principles underlying the data_algebra package (and also in its sibling rquery package). The data_algebra package is a query generator that can act on either Pandas data frames or on SQL tables. This is discussed on the project site and the examples directory. In this … Continue reading data_algebra/rquery as a Category Over Table Descriptions [...Read more...]

Python peeps: any idea why this attribute changes value when I re-examine it? I am using PyCharm, but the calculation is weird even in Jupyter. It doesn’t just seem to be the debugger, running it in Jupyter gives the wrong value (just {'x'}, instead of {'x', 'y'}). The type appears to be a dictionary object … Continue reading Python changing attribute mystery. Help? [...Read more...]

Slides for PyData LA 2019 vtreat Talk are here! [...Read more...]

Slides from my PyData2019 data_algebra lightning talk are here. [...Read more...]

We’ve had really good progress in bringing the Python data_algebra to feature parity with R rquery. In fact we are able to reproduced the New Introduction to rquery article as a “New Introduction to the data_algebra” here. The idea is: you may have good reasons to want to work in R or to want to … Continue reading New Introduction to the data_algebra [...Read more...]

Jumping Rivers is a data science consultancy company focused on R and Python. We work across industries and throughout the world. We offer a mixture of training, modelling, and infrastructure support. Jumping Rivers is an RStudio Full Service Certified Partner. This role is suitable for anyone interested in deploying (Linux-based) data science services and contains The post Job: Junior Systems Administrator (with a focus on R/Python) appeared first on Jumping Rivers. [...Read more...]