Traffic Analysis

Lightweight Python tools to process, summarise, and visualise CSV traffic-count data collected across multiple dates and junctions.

Features

• Reads one or more CSV files from the data/ folder
• Normalises vehicle types (handles misspellings: buss → bus, etc.) and canonicalises junction names
• Computes per-date metrics including:
  • Total vehicles, trucks, electric/hybrid, and two-wheeled counts
  • Buses leaving Elm Avenue/Rabbit Road heading north
  • Vehicles that did not turn (same entry and exit direction)
  • Percentage of trucks and Elm Avenue scooters
  • Average bicycles per hour
  • Vehicles exceeding the speed limit
  • Peak hour(s) at Hanley Highway/Westway
  • Number of rainy hours
• Appends human-readable summaries to results.txt
• Interactive matplotlib histogram embedded in a Tkinter window — toggle sort order, save PNG
• Batch mode aggregates all files into a combined summary

Requirements

• Python 3.9+
• matplotlib (for histogram visualisation)
• pytest (for tests)

python -m pip install -r requirements.txt

Quickstart

Run the interactive processor:

python traffic_analysis.py

Or invoke it from a script:

python -c "from traffic_analysis import MultiCSVProcessor; MultiCSVProcessor().process_files()"

The menu lets you pick a single date file or process all files at once.

Running tests

python -m pytest -q

CI runs tests against Python 3.9, 3.10, and 3.11 on every push and pull request to main.

Project structure

Traffic_Analysis/
├── traffic_analysis.py      # Core processing, histogram UI, CLI processor
├── data/                    # CSV input files (traffic_dataXX062024.csv)
├── results.txt              # Appended output summaries
├── tests/
│   └── test_processing.py   # pytest tests for CSV parsing and aggregation
└── requirements.txt

Data files

Place CSV files in the data/ directory. Each file should contain columns including Date, JunctionName, VehicleType, VehicleSpeed, JunctionSpeedLimit, timeOfDay, elctricHybrid, travel_Direction_in, travel_Direction_out, and Weather_Conditions.

Sample files covering 15–29 June 2024 are included in data/.

Output

• Metrics for each processed file are printed to the terminal and appended to results.txt.
• An interactive matplotlib histogram shows vehicle counts per junction, embedded in a Tkinter window with toggle-sort and save-PNG controls.