Hillmaker

New Python based hillmaker

hillmaker is a Python package that computes time of day and day of week specific occupancy statistics from transaction data containing arrival and departure timestamps. Typical use is for capacity planning problems in places like hospital emergency departments, surgical recovery rooms or any system in which entities arrive, occupy capacity for some amount of time, and then depart. It gets its name from the hill-like nature of plots based on temporal occupancy statistics.

Occupancy Plot

This new version was first released in early 2016 and provides the basis for ongoing development of hillmaker.

For now, I'm just using the GitHub repo as the project home page but plan to launch an official project website.

Project home page: https://github.com/misken/hillmaker License: Apache 2.0

A few features of the new hillmaker include

  • Takes a pandas DataFrame as the input data type
  • Functions for computing arrival, departure and occupancy summary statistics by time of day, day of week, and entity category based on a pandas DataFrame containing one record per visit.
  • Functions for computing arrival, departure and occupancy for each datetime bin in the analysis period, by category.
  • Select any time bin size (minutes) that divides evenly into a day.
  • Optionally specify one or more categories to ignore in the analysis.
  • Output statistics includes sample size, mean, min, max, standard deviation, coefficient of variation, standard error, skew, kurtosis, and a whole slew of percentiles (50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 97.5, 99).
  • Output CSV files are written by default but can be supressed.
  • Optionally capture outputs as a dictionary of pandas DataFrames for further post-processing (e.g. plot creation).
  • Requires Python 3 and pandas

Quick Start

A companion repo, https://github.com/misken/hillmaker-examples/ contains IPython notebooks and Python scripts illustrating the use of hillmaker.

In particular, the following IPython notebooks explains how to get and use hillmaker.

For Windows https://github.com/misken/hillmaker-examples/blob/master/notebooks/basic_win_usage_shortstay_unit.ipynb

For others https://github.com/misken/hillmaker-examples/blob/master/notebooks/basic_usage_shortstay_unit.ipynb

Both Win-64 and Linux-64 versions are available.

conda install -c https://conda.anaconda.org/hselab hillmaker

The source and a binary wheel are available from PyPi. You can install using pip:

pip install hillmaker

More examples and documentation are on the way.

Old MS Access based Hillmaker

Hillmaker is a Microsoft Access add-in that can be used to create statistical and graphical summaries of arrival, departure and occupancy patterns by time of day for systems having entities flowing into and out of some location.

It was released back in 2005 and has gotten quite a bit of use in the healthcare industry. While it still works just fine, I have no plans to update it. It is hosted on SourceForge.

Project home page: http://hillmaker.sourceforge.net/

License: GPL

Background paper:

Isken, M.W. (2002) Modeling and Analysis of Occupancy Data: A Healthcare Capacity Planning Application, International Journal of Information Technology and Decision Making, 1, 4 (December) 707-729.