pySTOPS

A utility for parsing and reading FTA STOPS Reports and Skim outputs with python, Numpy, and Pandas. The tool currently supports parsing STOPS skims and the following tables from the Results file:

• 1.02 (Station Listing)
• 2.04, 2.05, 2.07, 2.08,
• 3.01, 3.02, 3.03,
• 4.01, 4.04
• 8.01 (PMT Change)
• 9.01 (Station Boardings)
• 10.01 (Route Boardings)
• Assorted tables from Section 15: Detailed District-to-District Linked Trips and Selected Station-Station Flows (See listing in reader.py)

More table parsers coming soon.

Happily accepting additions.

Usage

In a real world usage, reading in a STOPS Report table into a Pandas dataframe becomes trivial.

import pystops

pystops.parse_table(report_file, '10.01')

For the data file in the example directory, this will return the following Pandas dataframe.

route_id	route_name	route_count	exist_walk	exist_knr	exist_pnr	exist_all	...	bld_all
1&C	--1-Metric/South Congress	6227	5394	242	117	5754	...	117
...	...	...					...
990&C	--990-Manor/Elgin Express	83	1	42	10	52	...	52

An example notebook is also available to demonstrate use cases and application.

Installation

The project relies on Python.

1. Create a pySTOPS-oriented virtual python environment. Recommend using a Anaconda Conda virtual env with the environment.yml included in this repository.

>>conda env create -f environment.yml

2. Switch the Virtual Env

conda activate pystops

3. Use the setup.py to install the package.

>>python setup.py install

4. Move to the test folder.

>>cd tests

5. Run example

python example.py

Additional Tables

The pySTOPS library searches the STOPS Results file for tags the start and end of each table, and the library then processes these tags to create Pandas DataFrames. If you want to add support for an additional table, modify the _table_parameters dictionary in the reader.py Python file.

The table name (e.g., '2.04', '10.01') is the key for each dictionary entry, and it is the way that the library finds the appropriate table. The rest of potential tags are below.

Tag	Required	Description
df_drop_top_rows		(Integer) Number of any extranenous top rows to discard
df_drop_tail_rows		(Integer) Number of any extranenous bottom (tail) rows to discard
end_table_tag	X	(String) Identify the last row of the data table
int_columns		(String Array) Force a retyping of columns to integers
index_col		(String) Set the index of the DataFrame to a specific column
rename_columns		(Dictionary) Column name mappings
reset_header		(Boolean) Change the header names to column numbers
skip_rows		(Integer) Number of lines to skip in the table header
widths		(Integer Array) Fixed width column lengths for the table