Xray: N-D labeled arrays and datasets in Python

Two weeks ago I was on my babymoon in Corfu, Greece. While in transit, I was overseeing a GSoC intern submit an important feature to my array database library, Xarray-SQL. He added `to_dataset()`, which completed the roundtrip between thinking of array data in a tabular model simultaneously as gridded rasters (the premise of the project is that every Nd array can be mapped to 2d, where orthogonal dims of the Nd array are just primary keys of a tabular representation). We discussed in chat, now that this feature existed, what demos could we make that would prove this data model works? With…

Hi HN, We're Anna, Adrian, Marcin and Matt, developers of dlt. dlt is an open source library to automatically create datasets out of messy, unstructured data sources. You can use the library to move data from about anywhere into most of well known SQL and vector stores, data lakes, storage buckets, or local engines like DuckDB. It automates many cumbersome data engineering tasks and can by handled by anyone who knows Python. Here’s our Github: https://github.com/dlt-hub/dlt Here’s our Colab demo:…

Like a Python list but better. Contribute to Lauriat/funct development by creating an account on GitHub.

Visions is a python library for working with user defined data type systems. Out of the box, it provides type inference and automated data cleaning of sequence data with backend specific implementations for pandas, spark, python, and numpy. We often use it as a first pass cleaning step when working with tabular data and to simplify the backend logic of both pandas-profiling[1] and our tabular data compression library compressio[2]. Because data types are user defined, we can build user customizable libraries based around types without adding code complexity. In the case of compressio that…