artanis/Territory-Analysis---Mapper
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Refactor: Integrate scripts into a single application (v1.2.0)

Browse Source
This commit is contained in:
Spencer Grimes
2025-12-29 16:45:40 -06:00
parent 671741772f
commit 5bd154fb4e
6 changed files with 213 additions and 251 deletions
Download Patch File Download Diff File Expand all files Collapse all files

77
category_analysis.py
View File

@@ -1,41 +1,26 @@
import csv
import json
import argparse
import pandas as pd
parser = argparse.ArgumentParser(description='Analyze territory data by category.')
parser.add_argument('filename', help='The CSV file to analyze.')
args = parser.parse_args()
def generate_category_map(df):
"""
Takes a DataFrame, performs category-based analysis, and generates category_map.html.
"""
# Calculate total address count for each CategoryCode
category_address_counts = df.groupby('CategoryCode')['Address Count'].sum().to_dict()
data = []
with open(args.filename, 'r') as f:
reader = csv.DictReader(f)
for row in reader:
data.append(row)
# Assign a distinct color to each category for the map
unique_categories = sorted(list(df['CategoryCode'].unique()))
colors = [
'#e6194b', '#3cb44b', '#ffe119', '#4363d8', '#f58231', '#911eb4',
'#46f0f0', '#f032e6', '#bcf60c', '#fabebe', '#008080', '#e6beff'
]
category_colors = {category: colors[i % len(colors)] for i, category in enumerate(unique_categories)}
category_address_counts = {}
for row in data:
category = row['CategoryCode']
if 'Address Count' in row and row['Address Count']:
address_count = int(row['Address Count'])
if category in category_address_counts:
category_address_counts[category] += address_count
else:
category_address_counts[category] = address_count
# Prepare data for embedding in HTML's JavaScript
data_for_json = df.to_dict(orient='records')
# --- New code for category colors ---
unique_categories = sorted(list(category_address_counts.keys()))
# A list of 12 distinct colors
colors = [
'#e6194b', '#3cb44b', '#ffe119', '#4363d8', '#f58231', '#911eb4',
'#46f0f0', '#f032e6', '#bcf60c', '#fabebe', '#008080', '#e6beff'
]
category_colors = {}
for i, category in enumerate(unique_categories):
category_colors[category] = colors[i % len(colors)]
with open('category_map.html', 'w') as f:
f.write(f'''
with open('category_map.html', 'w') as f:
f.write(f'''
<!DOCTYPE html>
<html>
<head>
@@ -53,23 +38,27 @@ with open('category_map.html', 'w') as f:
attribution: '&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> contributors'
}}).addTo(map);
var territories = {json.dumps(data, indent=4)};
var territories = {json.dumps(data_for_json, indent=4)};
var categoryColors = {json.dumps(category_colors, indent=4)};
var categoryAddressCounts = {json.dumps(category_address_counts, indent=4)};
for (var i = 0; i < territories.length; i++) {{
var territory = territories[i];
if (territory.Boundary) {{
var boundary = JSON.parse('[' + territory.Boundary + ']');
var color = categoryColors[territory.CategoryCode];
var polygon = L.polygon(boundary.map(p => [p[1], p[0]]), {{
fillColor: color,
color: "#000",
weight: 1,
fillOpacity: 0.7
}}).addTo(map);
var categoryAddressCount = categoryAddressCounts[territory.CategoryCode]
polygon.bindPopup('<b>Territory ID:</b> ' + territory.TerritoryID + '<br><b>Category:</b> ' + territory.CategoryCode + '<br><b>Category Address Count:</b> ' + categoryAddressCount);
try {{
var boundary = JSON.parse('[' + territory.Boundary + ']');
var color = categoryColors[territory.CategoryCode];
var polygon = L.polygon(boundary.map(p => [p[1], p[0]]), {{
fillColor: color,
color: "#000",
weight: 1,
fillOpacity: 0.7
}}).addTo(map);
var categoryAddressCount = categoryAddressCounts[territory.CategoryCode]
polygon.bindPopup('<b>Territory ID:</b> ' + territory.TerritoryID + '<br><b>Category:</b> ' + territory.CategoryCode + '<br><b>Category Address Count:</b> ' + categoryAddressCount);
}} catch(e) {{
console.error("Could not parse boundary for territory: " + territory.TerritoryID, e);
}}
}}
}}
</script>