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v1.1.0: consolidated panel + panel_dictionary, isora.py loader, World Bank income groups (current + per fiscal year), thousands flag on derived expenditure aggregates
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"""Render the Hugging Face dataset card from card_template.md and the build summary."""
from __future__ import annotations
import argparse
import json
from string import Template
import pandas as pd
from isora_hf import config
TEMPLATE = config.PROJECT_ROOT / "card_template.md"
OUTPUT = config.OUT_DIR / "README.md"
SUMMARY = config.OUT_DIR / "metadata" / "build_summary.json"
def fmt(n: float) -> str:
return f"{int(n):,}"
def generation_table(summary: dict) -> str:
rows = [
"| Questionnaire generation | Source dataflow | Fiscal years | Rows | Jurisdictions | Indicator codes |",
"|---|---|---|---|---|---|",
]
for flow in summary["dataflows_used"]:
g = summary["observations"]["by_generation"][flow["generation"]]
years = f"FY{g['fiscal_years'][0]}–FY{g['fiscal_years'][-1]}"
rows.append(
f"| {flow['generation']} | `{flow['id']}` v{flow['version']} | {years} | {fmt(g['rows'])} | {g['jurisdictions']} | {fmt(g['indicators'])} |"
)
return "\n".join(rows)
def fiscal_year_table(summary: dict) -> str:
rows = [
"| Fiscal year | Collected in | Jurisdictions | Indicator codes | Rows |",
"|---|---|---|---|---|",
]
for year, r in summary["observations"]["by_fiscal_year"].items():
rnd = config.FISCAL_YEAR_TO_ROUND[int(year)]
rows.append(
f"| {year} | {rnd} | {r['jurisdictions']} | {r['indicators']} | {fmt(r['rows'])} |"
)
return "\n".join(rows)
def status_table(summary: dict) -> str:
counts = summary["observations"]["value_status"]
total = sum(counts.values())
meaning = {
"value": "a numeric or text answer is present",
"not_available": "the administration answered `D` (data not available) to a numeric question",
"not_applicable": "the administration answered *Not Applicable*",
"empty": "the cell was published empty",
"unrecognized_code": "the published value is the undocumented code `P` (ISORA 2016 only)",
}
rows = ["| `value_status` | Rows | Share | Meaning |", "|---|---|---|---|"]
for k in ("value", "not_available", "not_applicable", "empty", "unrecognized_code"):
n = counts.get(k, 0)
rows.append(f"| `{k}` | {fmt(n)} | {100 * n / total:.1f}% | {meaning[k]} |")
return "\n".join(rows)
def dataflow_versions_table(summary: dict) -> str:
rows = [
"| Dataflow | Version | Data structure | Last updated at source | Used here |",
"|---|---|---|---|---|",
]
used = {(f["id"], f["version"]) for f in summary["dataflows_used"]}
vint = {("ISORA_LATEST_DATA_PUB", v) for v, _, _ in config.VINTAGES}
for d in sorted(
summary["dataflow_versions_at_source"], key=lambda x: (x["dataflow_id"], x["version"])
):
key = (d["dataflow_id"], d["version"])
use = "observations" if key in used else ("revisions" if key in vint else "no")
rows.append(
f"| `{d['dataflow_id']}` | {d['version']} | `{d['data_structure']}` | {d['last_updated_at_source'] or '—'} | {use} |"
)
return "\n".join(rows)
def kind_table(summary: dict) -> str:
counts = summary["observations"]["indicator_value_kind"]
meaning = {
"numeric": "every published answer is a number",
"binary": "answers are Yes / No",
"categorical": "answers come from a closed list (≤ 25 distinct values)",
"free_text": "more than 25 distinct text answers",
"mixed": "numbers and text both occur (usually a category plus a numeric ‘other’)",
"no_values": "only `D`, empty or not-applicable cells were published",
}
rows = ["| `indicator_value_kind` | Rows | What it means |", "|---|---|---|"]
for k, n in sorted(counts.items(), key=lambda kv: -kv[1]):
rows.append(f"| `{k}` | {fmt(n)} | {meaning.get(k, '')} |")
return "\n".join(rows)
def panel_table() -> str:
"""Markdown table of the consolidated panel columns, from panel_dictionary.parquet."""
d = pd.read_parquet(config.OUT_DIR / "data" / "panel_dictionary.parquet")
rows = [
"| Column | Unit | Description | Source code by generation (2016 / 2018 / 2020+) | Non-null rows |",
"|---|---|---|---|---|",
]
for col, grp in d.groupby("column", sort=False):
codes = {g: c for g, c in zip(grp["questionnaire_generation"], grp["indicator_code"])}
src = " / ".join(
f"`{codes[g]}`" if g in codes else "—"
for g in ("ISORA 2016", "ISORA 2018", "ISORA 2020+")
)
first = grp.iloc[0]
rows.append(
f"| `{col}` | {first['unit']} | {first['description']} | {src} | {fmt(first['n_non_null_in_panel'])} |"
)
return "\n".join(rows)
def build_context(summary: dict, repo_id: str) -> dict[str, str]:
obs, hist, rev = summary["observations"], summary["indicator_history"], summary["revisions"]
ct = rev["change_types"]
return {
"repo_id": repo_id,
"retrieved_at": summary["retrieved_at_utc"],
"retrieved_date": summary["retrieved_at_utc"][:10],
"obs_rows": fmt(obs["rows"]),
"n_jur": str(obs["jurisdictions"]),
"n_codes": fmt(obs["indicator_codes"]),
"fy_min": str(obs["fiscal_years"][0]),
"fy_max": str(obs["fiscal_years"][-1]),
"n_ind_rows": fmt(summary["indicators"]["rows"]),
"n_hist_rows": fmt(hist["indicator_codes"]),
"n_cov_rows": fmt(summary["coverage"]["rows"]),
"n_jur_rows": str(summary["jurisdictions"]["rows"]),
"hist_all_three": fmt(hist["in_all_three_generations"]),
"hist_two": fmt(hist["in_two_generations"]),
"hist_single": fmt(hist["single_generation"]),
"hist_label_changed": fmt(hist["comparability_flag"].get("label_changed", 0)),
"hist_label_stable": fmt(hist["comparability_flag"].get("label_stable", 0)),
"hist_changed_16_18": fmt(hist["label_changed_2016_to_2018"]),
"hist_changed_18_20": fmt(hist["label_changed_2018_to_2020plus"]),
"rev_keys_compared": fmt(rev["keys_compared"]),
"rev_keys_changed": fmt(rev["keys_with_changes"]),
"rev_value_revised": fmt(ct.get("value_revised", 0)),
"rev_text_revised": fmt(ct.get("text_revised", 0)),
"rev_scale": fmt(ct.get("scale_convention_change", 0)),
"rev_added": fmt(ct.get("added_in_later_release", 0)),
"rev_removed": fmt(ct.get("removed_in_later_release", 0)),
"not_available_rows": fmt(obs["value_status"].get("not_available", 0)),
"unrecognized_rows": fmt(obs["value_status"].get("unrecognized_code", 0)),
"monetary_thousands_rows": fmt(obs["monetary_unit"].get("thousands of local currency", 0)),
"monetary_units_rows": fmt(obs["monetary_unit"].get("local currency units", 0)),
"mojibake_values": fmt(obs["encoding_repairs"]["values"]),
"generation_table": generation_table(summary),
"fiscal_year_table": fiscal_year_table(summary),
"status_table": status_table(summary),
"dataflow_versions_table": dataflow_versions_table(summary),
"kind_table": kind_table(summary),
"panel_table": panel_table(),
"panel_rows": fmt(summary["panel"]["rows"]),
"panel_columns": str(summary["panel"]["indicator_columns"]),
"panel_income_matched": fmt(summary["panel"]["income_group_by_year_matched"]),
"panel_income_total": fmt(summary["panel"]["income_group_by_year_total"]),
"wb_matched": str(summary["jurisdictions"]["world_bank"]["jurisdictions_matched"]),
"wb_unmatched": ", ".join(
f"`{c}`" for c in summary["jurisdictions"]["world_bank"]["jurisdictions_unmatched"]
),
}
def render(repo_id: str) -> None:
summary = json.loads(SUMMARY.read_text(encoding="utf-8"))
text = Template(TEMPLATE.read_text(encoding="utf-8")).substitute(
build_context(summary, repo_id)
)
OUTPUT.write_text(text, encoding="utf-8")
print(f"wrote {OUTPUT} ({len(text.splitlines())} lines)")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--repo-id", default="FrenchCastle/isora-tax-administration")
render(parser.parse_args().repo_id)