<mods:mods version="3.3" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mods:titleInfo><mods:title>Usage Stats for High-Demand Items with Python</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">Henry</mods:namePart><mods:namePart type="family">Steele</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>Does your institution want to know if you have enough copies of high-demand items, such as reserves and equipment?   This session will show a way to use the Python pandas and numpy libraries to drill through Analytics reports and find out how often all copies of a given item were checked out.  I'll briefly introduce the libraries, and talk about how Tufts has used these stats to allocate funding for our Purchased Textbook program.</mods:abstract><mods:originInfo><mods:dateIssued encoding="iso8601">2019-04-30</mods:dateIssued></mods:originInfo><mods:genre>Conference or Workshop Item</mods:genre></mods:mods>