html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1282#issuecomment-467568194,https://api.github.com/repos/pydata/xarray/issues/1282,467568194,MDEyOklzc3VlQ29tbWVudDQ2NzU2ODE5NA==,1197350,2019-02-26T19:01:46Z,2019-02-26T19:01:46Z,MEMBER,Closed by #2430 #2657.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,209561985
https://github.com/pydata/xarray/issues/1282#issuecomment-281883932,https://api.github.com/repos/pydata/xarray/issues/1282,281883932,MDEyOklzc3VlQ29tbWVudDI4MTg4MzkzMg==,1217238,2017-02-23T03:30:30Z,2017-02-23T03:30:30Z,MEMBER,"Agreed!

Here's what @jhamman and I wrote in the abstract for [our paper](https://github.com/jhamman/xarray_paper/blob/master/jors_xarray.tex) on Xarray:

> Xarray is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays. Our approach combines an application programming interface (API) inspired by pandas with the Common Data Model for self-described scientific data. Key features of the Xarray package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib), out-of-core computation on datasets that don't fit into memory, a wide range of serialization and input/output (I/O) options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. Xarray, as a data model and analytics toolkit, has been widely adopted in the geoscience community but is also used more broadly for multi-dimensional data analysis in physics, machine learning and finance.

Probably something like that first sentence is a better high level description.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,209561985