Also known as Statistical Data and Metadata eXchange
Statistical Data and Metadata eXchange (SDMX) is a set of technical standards designed to describe statistical data and metadata, normalise their exchange, and improve their efficient sharing across statistical and similar organisations. It is published as ISO 17369.
simpledmx is a minimalistic Python package experience with SDMX that fetches all data from sources defined by the user. Although SDMX is very flexible, the main use case of simpledmx is when a user wants to download all available data from a specific source(s), for a given frequency (eg, annual, semi-annual, quarterly, monthly, daily). simpledmx uses pandasdmx as the backend to explore and fetch datasets from sources using SDMX. Further details on the sources and dataflows can be found in the pandasdmx documentation. simpledmx returns only the data, not the variable names. The user can learn more about the specific data at hand from the column names: each variable starts with its source, then the dataflow, followed by the key(s) (except for the time period) of that specific dataflow. in some cases, parsing the files downloaded from the original sources can take a long time. This is an issue with XML parsing, not with simpledmx or its backend ( pandasdmx ) specifically.
Excerpt from the source-code README · 1,885 chars · not written by Vinony
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Statistical Data and Metadata eXchange (SDMX) is a set of technical standards designed to describe statistical data and metadata, normalise their exchange, and improve their efficient sharing across statistical and similar organisations. It is published as ISO 17369.
== Development == The standards were developed by international initiative that aims at standardising and modernising ("industrialising") the mechanisms and processes for the exchange of statistical data and metadata among international organisations and their member countries.
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Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).