PATH ridership stats

Cleaned + Plotted PATH ridership data (source)

Interactive versions of the plots below:

• ire.runsascoded.com/#gl=hudcostreets/path-data/-/main/months.ipynb
• path.hudcostreets.org

Contents:

• Cleaned data
  • Jan 2012 – Oct 2023
  • Closer look at 2020-Present
  • Weekends only
  • Weekends (2020-Present)
  • Weekdays, Grouped by Month
  • Weekends, Grouped by Month
  • Weekdays vs. Weekends
  • Weekdays vs. Weekends, compared to 2019
• Usage
  • Update PATH Monthly Data PDFs
    • 0. Install
    • 1. Download PATH Ridership Reports
    • 2. Process each year's data, output .pqts
    • 3. Combine all years' data
  • Bridge & Tunnel Data (WIP)

Cleaned data

• data/all.pqt

Jan 2012 – Oct 2023

Closer look at 2020-Present

Weekends only

Weekends (2020-Present)

Weekdays, Grouped by Month

Weekends, Grouped by Month

Weekdays vs. Weekends

Weekdays vs. Weekends, compared to 2019

As of October 2024:

• weekday ridership was 71.2% of October '19 (pre-COVID)
• weekend ridership was 113.5% of October '19 (pre-COVID)

Usage

Update PATH Monthly Data PDFs

0. Install

git clone https://github.com/hudcostreets/path
cd path
pip install -e .

1. Download PATH Ridership Reports

path-data refresh

• refresh.py
• Updates local copies of PANYNJ PDFs, e.g.:
  • 2024-PATH-Monthly-Ridership-Report.pdf
  • 2024-PATH-Hourly-Ridership-Report.pdf

1b. Create Tabula templates

This is already done, the resulting templates are saved in templates/.

2. Process each year's data, output .pqts

path-data update

• update.py
• monthly.ipynb
• Outputsdata/20*.pqt

3. Combine all years' data

path-data combine

• combine.py
• months.ipynb
• Outputs: data/all.pqt, img/weekdays.png, etc.

Bridge & Tunnel Data (WIP)

Merge per-year PDFs into one:

/opt/homebrew/bin/gs \
  -o merged.pdf \
  -sDEVICE=pdfwrite \
  -dPDFFitPage \
  -g12984x10033 \
  -dPDFSETTINGS=/prepress \ 
  traffic-e-zpass-usage-20*

cf. SO.