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Exploratory Analysis of the TTC Delay data from the City of Toronto data portal, cross-examined with historical weather data and TTC ridership statistics.

Python 18.40% Jupyter Notebook 81.60%
ttc toronto toronto-open-data transportation transportation-planning public-transportation weather ttc-delays ttc-ridership-data toronto-data-portal

ttc-delay-analysis's Introduction

TTC-Delay-Analysis

Exploratory Analysis of the Toronto Transit Commission (TTC) Delay data from the City of Toronto data portal, cross-examined with historical TTC ridership statistics and Toronto weather data.

Data Sources

Transportation Mode Delay Data

TTC delay data was sourced for the following modes: Subway, Streetcar, Bus

See data gathering script

TTC Ridership Data

The TTC ridership data was sourced from the City of Toronto website, Progress Portal.

From the above site, using the 'Export Data' option, the 2 measures included in the data extract were:

  • 'TTC Average Weekday Ridership', and
  • 'TTC Monthly Ridership

Selecting these measures will output the raw .csv file 'TorontoMeasureData.csv' within this repository.

Canada Weather Data

Weather data was sourced from Canada Weather Stats, extracted manually from the data download page using the following parameters:

Daily Climate Data:

  • 'Climate Daily/Forecast/Sun'
  • Row limit: 2,400

Hourly Climate Data:

  • 'Climate Hourly'
  • Row limit: 60,000

Hourly data was extracted to allow for extra granularity when analyzing relationships between weather and TTC delays as weather can change drastically throughout the day and is expected to affect delay occurences and durations. Daily data was extracted to capture snow and rain data per day (as hourly data set did not contain these features).

Additional information on the data, features, and methods can be found here.

Data Cleaning & Processing

The data cleaning procedures are outlined in detail within the 'data_cleaning' notebook.

Cleaned data sets are subsequently moved under the 'data/cleaned_final' folder.

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