From 2bc63b5cf1badb3fea12d43a1342b1f7b9975971 Mon Sep 17 00:00:00 2001 From: Bob Borges Date: Wed, 18 Oct 2023 15:04:17 +0200 Subject: [PATCH] feat:starting stats-dashboard / dynamic README --- input/accuracy/difference.csv | 1691 ----------------- .../stats-dashboard/descr_stats_version.csv | 4 + scripts/stats-dashboard/generate-markdown.py | 239 +++ scripts/stats-dashboard/readme-template.md | 73 + 4 files changed, 316 insertions(+), 1691 deletions(-) delete mode 100644 input/accuracy/difference.csv create mode 100644 scripts/stats-dashboard/descr_stats_version.csv create mode 100644 scripts/stats-dashboard/generate-markdown.py create mode 100644 scripts/stats-dashboard/readme-template.md diff --git a/input/accuracy/difference.csv b/input/accuracy/difference.csv deleted file mode 100644 index a74fc98747..0000000000 --- a/input/accuracy/difference.csv +++ /dev/null @@ -1,1691 +0,0 @@ -version,year,accuracy -0.4.0,1920.0,0.8210511075720284 -0.4.0,1921.0,0.7721176081929303 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-v0.10.0,2022.0,0.9881273485948776 diff --git a/scripts/stats-dashboard/descr_stats_version.csv b/scripts/stats-dashboard/descr_stats_version.csv new file mode 100644 index 0000000000..22e6416f4b --- /dev/null +++ b/scripts/stats-dashboard/descr_stats_version.csv @@ -0,0 +1,4 @@ +version,corpus_size,N_prot,N_prot_pages,N_prot_words,N_mot,N_mot_pages,N_mot_words,N_MP,N_MIN +v0.8.1,5.58,17642,1041807,441525242,0,0,0,5975,535 +v0.9.0,5.58,17642,1041807,441525242,0,0,0,5975,535 +v0.10.0,5.58,17642,1041807,441525242,0,0,0,5975,535 diff --git a/scripts/stats-dashboard/generate-markdown.py b/scripts/stats-dashboard/generate-markdown.py new file mode 100644 index 0000000000..ede5bc42e0 --- /dev/null +++ b/scripts/stats-dashboard/generate-markdown.py @@ -0,0 +1,239 @@ +#!/usr/bin/env python3 +""" +Generates a markdown file for the repo's main README. + - generate variable dict + - reads in readme-template.txt + - substitutess variables + - writes README.md +""" +from pyriksdagen.utils import ( + protocol_iterators, + elem_iter, + ) +from lxml import etree +from py_markdown_table.markdown_table import markdown_table +from tqdm import tqdm +import argparse, os +import pandas as pd +import re + + + +here = os.path.dirname(__file__) + + +""" +TO DO +===== +Corpus information +------------------ +(This should probably just be a table). + +[x] The total number of persons in the MP catalogue +[x] The total number of pages by document type +[x] The size in Gb of the corpus folder + +Corpus Statistics - Figures +--------------------------- +[x] Number of documents by type (protocols, motions, government bills etc), year, and corpus version +[x] Number of pages by type (protocols, motions, government bills etc), year, and corpus version +[_] Number of MPs by year and chamber (with the actual number of seats as a line - Bobs plot, but more readable) +[ ] The number of speeches by year and corpus version + +Corpus Quality +-------------- +[x] Speech-to-speaker mapping proportion by year and corpus version +[_] Number of members of parliament by year and chamber as a ratio with respect to the actual number of seats (see paper) +[ ] The OCR quality (character- and word error rate) by decade and document type (records) + - note this is a two-stage sample and needs to be estimated by taking this into account, liam knows more +[ ] The segmentation error by decennia and document type (records) +[ ] The segmentation classification error by decennia and document type (records) +[ ] The number proportion of empty chairs and chairs with multiple persons overlap. +""" + + +corpus_paths = { + "protocols_path": "corpus/protocols", + "metadata_path": "corpus/metadata/", + } + +md_row_names = { + "-": "", + "corpus_size": "Corpus size (GB)", + "N_prot": "Number of protocols", + "N_prot_pages": "Total protocol pages*", + "N_prot_words": "Total protocol words", + "N_mot": "Number of Motions", + "N_mot_pages": "Total motion pages", + "N_mot_words": "Total motion words", + "N_MP": "Number of people with MP role", + "N_MIN": "Number of people with minister role" + } + + + + +def render_markdown(renderd): + with open(f"{here}/readme-template.md", 'r') as inf: + template = inf.read() + readme = template.format(**renderd) + with open(f"{here}/_README.md", 'w+') as out: # testing -- later write to project root + out.write(readme) + return True + + + + +def mk_table_data(df): + table_data = [] + D = {} + version = sorted(list(set(df['version'])), key=lambda s: list(map(int, s[1:].split('.'))), reverse=True) + cols = [c for c in df.columns if c != "version"] + for v in version[:3]: + dfv = df.loc[df["version"]==v].copy() + dfv.reset_index(inplace=True, drop=True) + for col in cols: + if col not in D: + D[col] = {} + D[col][v] = dfv.at[0, col] + for k, v in D.items(): + n = {'': md_row_names[k]} + n.update(v) + table_data.append(n) + return table_data + + + + +def calculate_corpus_size(): + print("Calculating corpus size...") + corpus_size = 0 + for k, v in corpus_paths.items(): + for dirpath, dirnames, filenames in os.walk(v): + for f in filenames: + fp = os.path.join(dirpath, f) + if not os.path.islink(fp): + corpus_size += os.path.getsize(fp) + fsize = "%.2f" % (corpus_size / (1024 * 1024 * 1024)) # converts size to gigabytes + print(f"...{fsize} GB") + return fsize + + + + +def count_pages_words(protocol): + pages, words = 0,0 + tei_ns = ".//{http://www.tei-c.org/ns/1.0}" + xml_ns = "{http://www.w3.org/XML/1998/namespace}" + parser = etree.XMLParser(remove_blank_text=True) + root = etree.parse(protocol, parser).getroot() + tei = root.find(f"{tei_ns}TEI") + for tag, elem in elem_iter(root): + if tag == "u": + for segelem in elem: + words += len([_.strip() for _ in segelem.text.split(' ') if len(_) > 0 and _ != '\n']) + pages = len(tei.findall(f"{tei_ns}pb")) + return pages, words + + + + +def calculate_prot_stats(): + print("Calculating protocol summary statistics...") + N_prot,N_prot_pages,N_prot_words = 0,0,0 + protocols = sorted(list(protocol_iterators("corpus/protocols/", start=1867, end=2022))) + for protocol in tqdm(protocols, total=len(protocols)): + N_prot += 1 + pp, pw = count_pages_words(protocol) + N_prot_pages += pp + N_prot_words += pw + print(f"...{N_prot} protocols, {N_prot_pages} protocol pages, {N_prot_words} protocol words") + return N_prot, N_prot_pages, N_prot_words + + + + +def calculate_mot_stats(): + print("Calculating motion summary statistics...") + print("...this function hasn't been written yet, return 0,0,0") + N_mot, N_mot_pages, N_mot_words = 0,0,0 + return N_mot, N_mot_pages, N_mot_words + + + + +def count_MP(): + print("Counting MPs (unique people w/ role)...") + N_MP = 0 + df = pd.read_csv("corpus/metadata/member_of_parliament.csv") + N_MP = len(df["wiki_id"].unique()) + print(f"... {N_MP} individuals have a 'member of parliament' role") + return N_MP + + + + +def count_MIN(): + print("Counting ministers (unique people with role)...") + N_MIN = 0 + df = pd.read_csv("corpus/metadata/minister.csv") + N_MIN = len(df["wiki_id"].unique()) + print(f"... {N_MIN} individuals have a 'minister' role") + return N_MIN + + + + +def main(args): + print(f"CALUCLATING SUMSTATS FOR {args.version}") + print("---------------------------------") + new_version_row = [args.version] + new_version_row.append(calculate_corpus_size()) + #[new_version_row.append(_) for _ in calculate_prot_stats()] + [new_version_row.append(_) for _ in [0,0,0]] # use this to do fast testing + [new_version_row.append(_) for _ in calculate_mot_stats()] + new_version_row.append(count_MP()) + new_version_row.append(count_MIN()) + + # Update running stats + running_stats = pd.read_csv(f"{here}/descr_stats_version.csv") + running_stats.drop(running_stats[running_stats.version == args.version].index, inplace=True) + running_stats.reset_index(inplace=True, drop=True) + running_stats.loc[len(running_stats)] = new_version_row + running_stats.to_csv(f"{here}/descr_stats_version.csv", index=False) + + # generate table data + table_data = mk_table_data(running_stats) + # generate table + table = markdown_table( + table_data + ).set_params( + quote=False, + padding_width=3, + row_sep="markdown" + ).get_markdown() + + print("Sumstats, last 3 versions:\n") + print(table) + print("\n\n") + + to_render = { + "sumstats_table": table, + } + if render_markdown(to_render): + print("New README generated successfully.") + + + + +if __name__ == '__main__': + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("-v", "--version", type=str) + args = parser.parse_args() + exp = re.compile(r"v([0-9]+)([.])([0-9]+)([.])([0-9]+)(b|rc)?([0-9]+)?") + if exp.search(args.version) is None: + print(f"{args.version} is not a valid version number. Exiting") + exit() + else: + args.version = exp.search(args.version).group(0) + main(args) diff --git a/scripts/stats-dashboard/readme-template.md b/scripts/stats-dashboard/readme-template.md new file mode 100644 index 0000000000..b9ff6dc37f --- /dev/null +++ b/scripts/stats-dashboard/readme-template.md @@ -0,0 +1,73 @@ +[![Unit tests](https://github.com/welfare-state-analytics/riksdagen-corpus/actions/workflows/push.yml/badge.svg)](https://github.com/welfare-state-analytics/riksdagen-corpus/actions/workflows/push.yml) +[![Validate Parla-Clarin XML](https://github.com/welfare-state-analytics/riksdagen-corpus/actions/workflows/validate.yml/badge.svg)](https://github.com/welfare-state-analytics/riksdagen-corpus/actions/workflows/validate.yml) + + +# Swedish parliamentary proceedings --- 1867--today + +_Westac Project, 2020--2023_ + +_Swerik Project, 2023--2025_ + +## The data set + +The full data set consists of multiple parts: + +- Parliamentary records (riksdagens protokoll) from 1867 until today in the [Parla-clarin](https://github.com/clarin-eric/parla-clarin) format +- Comprehensive list of members of parliament, ministers and governments during this period + associated metadata (mandate periods, party info, etc) +- [In progress] An annotated catalog of motions submitted to the parliament with linked metadata +- [Documentation](https://github.com/welfare-state-analytics/riksdagen-corpus/tree/main/docs/) of the corpus and the curation process +- [A Google Colab notebook](https://colab.research.google.com/drive/1C3e2gwi9z83ikXbYXNPfB6RF7spTgzxA?usp=sharing) that demonstrates how the dataset can be used with Python + +## Basic use + +A full dataset is available under [this download link](https://github.com/welfare-state-analytics/riksdagen-corpus/releases/latest/download/corpus.zip). It has the following structure + +- Annual protocol files in the ```corpus/protocols/``` folder +- Structured metadata on members of parliament, ministers, and governments in the ```corpus/metadata/``` folder + +The workflow to use the data is demonstrated in [this Google Colab notebook](https://colab.research.google.com/drive/1C3e2gwi9z83ikXbYXNPfB6RF7spTgzxA?usp=sharing). + +## Design choices of the project + +The Riksdagen corpus is released as an iterative process, where the corpus is curated and expanded. Semantic versioning is used for the whole corpus, following the established major-minor-patch practices as they apply to data. For each major and minor release, a battery of unit tests are run and a statistical sample is drawn, annotated and quantitatively evaluated to ensure integrety and quality of updated data. Errors are fixed as they are detected in order of priority. Moreover, the edit history is kept as a traceable git repository. + +While the contents of the corpus will change due to curation and expansion, we aim to keep the deliverable API, the `corpus/` folder, as stable as possible. This means we avoid relocating files or folders, changing formats, changing columns in metadata files, or any other changes that might break downstream scripts. Conversely, files outside the `corpus/` folder are internal to the project. End users may find utility in them but we make no effort to keep them consistent. + +The data in the corpus is delivered as TEI XML files to follow established practices. The metadata is delivered as CSV files, following a [normal form](https://en.wikipedia.org/wiki/Database_normalization) database structure while allowing for a legible git history. A more detailed description of the data and metadata structure and formats can be found in the README files in the `corpus/` folder. + +## Descriptive statistics at a glance + +{sumstats_table} + + + + +\* Digital original parliamentary records in the period YEAR--YEAR were not paginated and thus do not contribute to the page count. + +### Documents by type over time + +FIGURE: N-protocols over time + +### Members of Parliament over time + +FIGURE: N by chamber/year + +## Quality assessment + +### Correct number of MPs over time + +FIGURE: ratio of MP mandates and baseline + +### Speech-to-speaker mapping + +We check how many speakers in the parliamentary records our algorithms idenify in each release. + +![Estimate of mapping accuracy](https://raw.githubusercontent.com/welfare-state-analytics/riksdagen-corpus/main/input/accuracy/version_plot.png) + + +## Participate in the curation process + +If you find any errors, it is possible to submit corrections to them. This is documented in the [project wiki](https://github.com/welfare-state-analytics/riksdagen-corpus/wiki/Submit-corrections). + + +## Acknowledgement of support