From 2f7bc48f3d6f830e7b6193f383ba667e12bcb89a Mon Sep 17 00:00:00 2001
From: Jigsaw <no-reply@google.com>
Date: Wed, 11 Dec 2024 09:42:50 -0800
Subject: [PATCH] Internal change

GitOrigin-RevId: 4607c9bbbea5e5d4afa7f15f12a85d1d0ac2efd2
---
 bin/process_polis_data.py | 97 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 97 insertions(+)
 create mode 100755 bin/process_polis_data.py

diff --git a/bin/process_polis_data.py b/bin/process_polis_data.py
new file mode 100755
index 0000000..3640e6e
--- /dev/null
+++ b/bin/process_polis_data.py
@@ -0,0 +1,97 @@
+#!/usr/bin/env python3
+
+import pandas as pd
+import argparse as arg
+
+
+print("starting program")
+
+# argparse setup with arguments for two input files
+def getargs():
+    parser = arg.ArgumentParser(description="Process Polis data from the openData export data.")
+    parser.add_argument("export_directory", help="Path to export directory.")
+    parser.add_argument("--participants-votes", help="Participants votes file (override).")
+    parser.add_argument("--comments", help="Path to the comments file (override).")
+    parser.add_argument("-o", "--output_file", help="Path to the output CSV file.", required=True)
+    args = parser.parse_args()
+    args.participants_votes = args.participants_votes or f"{args.export_directory}/participants-votes.csv"
+    args.comments = args.comments or f"{args.export_directory}/comments.csv"
+    return args
+
+
+print("processing args")
+args = getargs()
+
+# Read the CSV files into pandas DataFrames
+try:
+    votes = pd.read_csv(args.participants_votes)
+    comments = pd.read_csv(args.comments)
+except FileNotFoundError as e:
+    print(f"Error: One or both input files not found: {e}")
+    exit(1)
+except pd.errors.EmptyDataError as e:
+    print(f"Error: One or both input files are empty: {e}")
+    exit(1)
+except pd.errors.ParserError as e:
+    print(f"Error parsing CSV file: {e}")
+    exit(1)
+
+print("args processed")
+
+# make sure to cast comment ids as ints
+comments['comment-id'] = comments['comment-id'].astype(int)
+
+
+# filter out votes rows where group-id is nan, and make ints
+votes = votes[votes['group-id'].notna()]
+votes['group-id'] = votes['group-id'].astype(int)
+group_ids = votes['group-id'].unique()
+
+# prompt: find all of the column names in the votes df that match a numeric regex
+import re
+comment_ids = [col for col in votes.columns if re.match(r'^\d+$', col)]
+print(comment_ids)
+
+
+# Melt the DataFrame
+melted_votes = votes.melt(id_vars=["group-id"], value_vars=comment_ids, var_name='comment-id', value_name='value')
+melted_votes['comment-id'] = melted_votes['comment-id'].astype(int)
+print(melted_votes)
+# Group, count, unstack, and fill missing values
+result = (
+    melted_votes.groupby(['comment-id','group-id'])['value']
+    .value_counts()
+    .unstack(fill_value=0)
+    .reset_index()
+)
+
+# Rename columns
+result = result.rename(columns={-1: 'disagree-count', 0: 'pass-count', 1: 'agree-count'})
+
+# pivot out the group-id column so that each of the vote count columns look like "group-N-VOTE-count"
+pivoted = result.pivot(index="comment-id", columns='group-id')
+
+# ...?
+for_merge = pd.DataFrame({'comment-id': pivoted['disagree-count'][0.0].index})
+for group_id in group_ids:
+  for count_col in ["disagree-count", "pass-count", "agree-count"]:
+    for_merge["group-" + str(group_id) + "-" + count_col] = pivoted[count_col][group_id]
+
+# zero out total vote tallies since incorrect from filtering or database caching
+comments["agrees"] = 0
+comments["disagrees"] = 0
+comments["passes"] = 0
+
+# merge in the per group tallies above
+comments = comments.merge(for_merge, on='comment-id')
+
+# add up from the votes matrix for consistency
+for group_id in group_ids:
+  comments["disagrees"] += comments["group-" + str(group_id) + "-disagree-count"]
+  comments["agrees"] += comments["group-" + str(group_id) + "-agree-count"]
+  comments["passes"] += comments["group-" + str(group_id) + "-pass-count"]
+
+# prompt: write out to a CSV file
+comments = comments.rename(columns={'comment-body': 'comment_text'})
+comments.to_csv(args.output_file, index=False)
+