We are accessing OECD: MEI data via Python.:
https://git.nomics.world/dbnomics-json-data/oecd-json-data/tree/master/MEI/series.jsonl
We only need to access QUARTERLY data for all MEI series which we are then dumping as a .CSV in Rows x Columns format. The series.jsonl file we are accessing is massive as it contains Monthly (and Annual) data too; the Python script has to check every “row” in order to select only the Quarterly periodicity data and it’s taking a very long time (its regularly updated too)
Question: - do you ever store eg MEI JSON files that contain:
just QUARTERLY data eg “seriesQ.jsonl” or
just ANNUAL data eg “seriesA.jsonl” or
just MONTHLY data eg “seriesM.jsonl”
Accessing seriesQ.jsonl would then be MUCH quicker than the current “grand” series.jsonl
Is this file seperation feasible for MEI (& other datasets containing Monthly data as well as Quarterly & Annual data?)
Most kind