Presenter: Andrew Kelly, Cataloging & E-Resources Librarian, Paul Smith's College This poster has two accompanying handouts: https://www.slideshare.net/NASIG/a-snake-a-planet-and-a-bear-ditching-spreadsheets-handout1 and https://www.slideshare.net/NASIG/a-snake-a-planet-and-a-bear-ditching-spreadsheets-handout2slides.

1. A Snake, A Planet, & A Bear:
Ditching spreadsheets for quick, reproducible report
production with python, jupyter, & pandas
Features of this platform:
• Actions are modular, allowing
for generalization of
techniques: easily do the
same normalization or merge
procedures across different
documents or updated inputs.
• Easily merge and combine
data from disparate sources,
more flexible than Excel’s
VSLOOKUP function and less
cumbersome than loading
data into a SQL Database.
• Large, active projects with
ongoing development, wide
availability of resources &
other users.
Three part data analysis &
manipulation platform:
• Python Programming language:
widely used programming language
often used as introduction to
computer programming and has rich
ecosystem of software libraries for
adding a wide array of functionality.
• Jupyter Notebook: A web application
that runs on your computer and
allows straightforward view of code
input and output of results, charts,
and graphs.
• Pandas: software library works easily
with CSV and excel files as inputs
while providing the data frame data
structure that mirrors familiar
components of Excel, R.
Use Cases:
I’ve worked to adopt this platform so
that I can easily build on a given
annual report’s features from year-to-
year. Reports built to date use data for
a variety of Technical Services
functions, including Acquisitions,
collections analysis and assessment.
Acquisitions Reporting Collection Analysis Print Serials Evaluation
Using book vendor accounting data to
analysis current total monograph
spending, easily summarize spending with
charts and annually look at how spending
was broken down across individual liaison
librarians as well as across programs.
Allows our distributed model of Collection
Development to function with low
administrative overhead.
Decisions on where to focus collection
development activities can be made
throughout the year instead of in a
scramble at the close of the fiscal year.
Making use of our ILS to export a subject
specific part of our print monograph
collection, I processed the records to a
tab-delimited file in MarcEdit and
imported them into a notebook file.
The graphs above show the distribution of
dates and the date the title was added to
our collection, giving an idea of the age of
our collection and history of collecting in
this subject area.
Leveraging experience in previous reports
to quickly make this report and use it to
successfully argue for additional start-up
funds for a new program.
This project combines in-house usage data
pulled live from our usage database and
combines it with two vendor data sources
on renewal pricing, historical data, format
availability and allows for rich querying of
current subscriptions.
We can now answer questions about our
print subscriptions such as “Which titles
that cost over $500 per year and saw fewer
than 5 recorded uses in the last 5 year.”
Moving forward, we will be able to build on
this baseline analysis with a new year’s
renewal to answer more sophisticated
questions about these resources.
Future Directions:
Given the reusability of these reports,
there is ample opportunity to build on
current progress, share reports, and
drive adoption methods for analysis of
an even wider variety of library data.
This could include COUNTER reports,
holdings information, or usage logs.
Andrew M. Kelly
Cataloging & E-Resources Librarian
Presented at NASIG Annual Conference 2017
June 9, 2017 -- Indianapolis, IN
Getting Started:
• Easy to install with Anaconda
python distribution.
• Familiar tasks such as filtering
tables or constructing pivot
tables can be accomplished in
single lines of python.
• Export results as full HTML
pages or individual parts as
CSV or image files.