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OECD data mining using pandasdmx and pandas
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README.md

oecd-data-mining

The Organisation for Economic Co-operation and Development (OECD) Interface software suite provides a means to discover, download, and convert OECD SDMX-JSON data sets into CSV files. The files can be further processed to select a subset according to set criteria (e.g. industries with electricity), with specific fixed (normalized) column types. The suite covers:

  • downloading list of all OECD data set IDs and descriptions;
  • downloading list of all data set schema;
  • downloading all OECD SDMX-JSON data sets;
  • converting all time period data sets to un-pivoted CSV files;
  • selecting a subset according to set criteria with specific fixed (normalized) column types
  • concatenating this subset of fixed column CSV files into an overall master CSV file.

There is also the means to work with just OECD frequency dimension data, which are a subset of the main time period data sets. This suite covers :

  • identifing frequency dimension (annual/quarterly) supporting schema;
  • downloading just OECD SDMX-JSON data sets with a frequency dimension;
  • converting frequency dimension data sets to multi-indexed CSV files.

The OECD Interface software suite is written for Python 3.5, pandas 0.21.0, and uses the pandasdmx 0.7.0 Python package to convert SDMX-JSON files to multi-indexed CSV files.

The full online documentation is to be found here, and lays out the workflow for using these utilities: https://snatch59.github.io/oecd-data-mining/

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