Alex Parsons ajparsons

## constituency_converstion.py
"""
This file is a standlone library to convert polling data from one geography to another.
It has minimal dependencies beyond pandas.
Ideally it uses parquet and pyarrow - but if this is an obstacle,
adjust the parquet references to csv.

Note, when converting to LAD23, this is the lower level geography.

Additional conversion for higher level is in convert_specific_polling.py
in the climate_mrp_polling package.

## compress_docker_vdisk.txt
wsl --shutdown
diskpart
select vdisk file="C:\Users\USER\AppData\Local\Docker\wsl\data\ext4.vhdx"
attach vdisk readonly
compact vdisk
detach vdisk
exit

## startrek_wikidata_midpoint.R
# Wikidata/R script to find the midpoint of all current star trek tv/films

library(WikidataQueryServiceR)

query <- '
SELECT DISTINCT ?item ?itemLabel ?duration ?startrekLabel
WHERE
{
 #star trek films
 {?item wdt:P31 wd:Q61283808.}

## json_bods_flatten.py
# Roundtrip json bods to xlsx

import os
import openpyxl
import json

from tempfile import TemporaryDirectory
from flattentool import flatten, unflatten


## assemblies_websites.json
[{"children": [], "child_of": null, "link": "https://docs.google.com/document/d/1as8y1rV3EEnyHDTlKsWZ988NnUs5QvUgT-RruUrCwV0/edit#heading=h.8n1yv86y9wvz", "name": "Introduction", "id": 1}, {"children": [{"children": [], "child_of": 2, "link": "https://docs.google.com/document/d/1as8y1rV3EEnyHDTlKsWZ988NnUs5QvUgT-RruUrCwV0/edit#heading=h.2zqzc2994t4y", "name": "Design", "id": 3}, {"children": [], "child_of": 2, "link": "https://docs.google.com/document/d/1as8y1rV3EEnyHDTlKsWZ988NnUs5QvUgT-RruUrCwV0/edit#heading=h.3w2umh6zwbbd", "name": "Discoverability", "id": 4}, {"children": [], "child_of": 2, "link": "https://docs.google.com/document/d/1as8y1rV3EEnyHDTlKsWZ988NnUs5QvUgT-RruUrCwV0/edit#heading=h.xxzaducm929a", "name": "Accessibility", "id": 5}, {"children": [], "child_of": 2, "link": "https://docs.google.com/document/d/1as8y1rV3EEnyHDTlKsWZ988NnUs5QvUgT-RruUrCwV0/edit#heading=h.s7hmntikgtgr", "name": "Plain language", "id": 6}, {"children": [], "child_of": 2, "link": "https://docs.google.com/document/d/1as8y

## assemblies_toc.json
[{"children": [], "child_of": null, "link": "https://docs.google.com/document/d/17sMqrBrQO89pkSly8vg2CNOvm26bsqgPrZ-S-q4EsvQ/edit#heading=h.apm3u78ms6oq", "name": "Introduction", "id": 1}, {"children": [], "child_of": null, "link": "https://docs.google.com/document/d/17sMqrBrQO89pkSly8vg2CNOvm26bsqgPrZ-S-q4EsvQ/edit#heading=h.hl4hiday6wcc", "name": "Potential uses of digital tools", "id": 2}, {"children": [{"children": [], "child_of": 3, "link": "https://docs.google.com/document/d/17sMqrBrQO89pkSly8vg2CNOvm26bsqgPrZ-S-q4EsvQ/edit#heading=h.wnh22yd3dipg", "name": "Question forming", "id": 4}, {"children": [], "child_of": 3, "link": "https://docs.google.com/document/d/17sMqrBrQO89pkSly8vg2CNOvm26bsqgPrZ-S-q4EsvQ/edit#heading=h.lfshf3fygn0a", "name": "Public submissions", "id": 5}, {"children": [], "child_of": 3, "link": "https://docs.google.com/document/d/17sMqrBrQO89pkSly8vg2CNOvm26bsqgPrZ-S-q4EsvQ/edit#heading=h.v3wu5gbewhp4", "name": "Finding experts and stakeholders", "id": 6}], "child_of": null, "link": "h
	"""
	This file is a standlone library to convert polling data from one geography to another.
	It has minimal dependencies beyond pandas.
	Ideally it uses parquet and pyarrow - but if this is an obstacle,
	adjust the parquet references to csv.

	Note, when converting to LAD23, this is the lower level geography.

	Additional conversion for higher level is in convert_specific_polling.py
	in the climate_mrp_polling package.
	wsl --shutdown
	diskpart
	select vdisk file="C:\Users\USER\AppData\Local\Docker\wsl\data\ext4.vhdx"
	attach vdisk readonly
	compact vdisk
	detach vdisk
	exit
	# Wikidata/R script to find the midpoint of all current star trek tv/films

	library(WikidataQueryServiceR)

	query <- '
	SELECT DISTINCT ?item ?itemLabel ?duration ?startrekLabel
	WHERE
	{
	#star trek films
	{?item wdt:P31 wd:Q61283808.}
	# Roundtrip json bods to xlsx

	import os
	import openpyxl
	import json

	from tempfile import TemporaryDirectory
	from flattentool import flatten, unflatten