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.Rhistory

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+Rscript pivot.R
+q()

.gitignore

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-.venv
-.DS_Store
-.ipynb_checkpoints/
+boston_311_2023_raw.csv

boston_311_2023_by_reason.csv

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+reason,Count
+Abandoned Bicycle,1318
+Administrative & General Requests,2025
+Air Pollution Control,35
+Alert Boston,3
+Animal Issues,4155
+Billing,6
+Boston Bikes,64
+Bridge Maintenance,8
+Building,5209
+Catchbasin,621
+Cemetery,29
+Code Enforcement,31812
+Employee & General Comments,2166
+Enforcement & Abandoned Vehicles,61541
+Environmental Services,4416
+Fire Hydrant,205
+General Request,196
+Generic Noise Disturbance,109
+Graffiti,1839
+Health,1349
+Highway Maintenance,25096
+Housing,7590
+MBTA,1
+Massport,8
+Needle Program,7413
+Neighborhood Services Issues,28
+Noise Disturbance,832
+Notification,607
+Office of The Parking Clerk,18
+Operations,283
+Park Maintenance & Safety,7932
+Parking Complaints,19
+Pothole,85
+Programs,6
+Recycling,9955
+Sanitation,59389
+Sidewalk Cover / Manhole,291
+Signs & Signals,11209
+Street Cleaning,45659
+Street Lights,8499
+Traffic Management & Engineering,751
+Trees,10390
+Valet,7
+Weights and Measures,52

pivot.py

@@ -1,15 +1,35 @@
 #!/usr/bin/env python3
 
 import pandas as pd
+import matplotlib.pyplot as plt
 
 # Read the CSV file into a pandas DataFrame
 data = pd.read_csv('boston_311_2023_raw.csv')
 
 # Group the data by the 'reason' column and count the occurrences of each reason
 reason_counts = data.groupby('reason').size().reset_index(name='Count')
 
-# Save the result to a new CSV file
+# Save the result to a new CSV file (optional)
 reason_counts.to_csv('boston_311_2023_by_reason.csv', index=False)
 
-# Print the result (optional)
-print(reason_counts)
+# Sort the reasons by count and select the top 10
+top_10_reasons = reason_counts.sort_values(by='Count', ascending=False).head(10)
+
+# Create a horizontal bar chart
+plt.figure(figsize=(10, 6))
+plt.barh(top_10_reasons['reason'], top_10_reasons['Count'], color='skyblue')
+
+# Add labels, title, and citation
+plt.xlabel('Number of Calls', fontsize=12)
+plt.ylabel('Reason', fontsize=12)
+plt.title("Top 10 Reasons for 311 Calls in Boston (2023)", fontsize=16)
+plt.figtext(0.5, -0.1, "Data Source: Boston 311, Author: Your Name", ha="center", fontsize=10)
+
+# Adjust layout to prevent overlap
+plt.tight_layout()
+
+# Save the chart as an image
+plt.savefig('top_10_reasons_311_calls_horizontal.png')
+
+# Show the chart
+plt.show()