Library Checkouts

This dataset provides comprehensive records of library book lending transactions, including details on book titles, borrowers, checkout and due dates, renewals, and return status. It enables efficient tracking of borrowing activity, overdue management, and supports analysis of library usage patterns and borrower behavior.

  • last updated 29 Oct 2025
  • by GoMask
The brief that made it

Library circulation and usage analytics

Sample rows

preview · 8 of 200 rows · all 11 columns
checkout_idstringrenewal_countintegerreturnedbooleanbook_idstringbook_titlestringborrower_idstringborrower_namestringcheckout_datedatedue_datedatereturn_datedateoverdueboolean
CKOUT_001A0trueBK101To Kill a MockingbirdBR201Emily Johnson2024-03-022024-03-162024-03-15false
CKOUT_002B1trueBK1021984BR202David Lee2024-03-102024-03-242024-03-25true
CKOUT_003C2falseBK103The Great GatsbyBR203Sophia Martinez2024-03-152024-03-29blankfalse
CKOUT_004D0trueBK104Brave New WorldBR204Michael Brown2024-03-182024-04-012024-03-30false
CKOUT_005E1trueBK105Pride and PrejudiceBR205Olivia Davis2024-03-202024-04-032024-04-05true
CKOUT_006F0falseBK106The HobbitBR206James Wilson2024-03-252024-04-08blankfalse
CKOUT_007G2trueBK107Moby DickBR207Grace Thomas2024-03-282024-04-112024-04-12true
CKOUT_008H0trueBK108Jane EyreBR208Benjamin Harris2024-04-012024-04-152024-04-14false

What the 200 rows show

from the 200-row sample
  • 62%returned = true
  • 1median renewal_count
renewal_count200 rows, in bands of 0.5
0408076070050401.53renewal_count →

Median 1, from 0 to 3.

11 columns by typefrom the column list below
  • string 5
  • integer 1
  • date 3
  • boolean 2

Columns

11 columns in four groups
blueprint · 11 columns
columntypedescriptionexample
Text 5 columns
checkout_idstringUnique identifier for each checkout transactionuniqueCKOUT_001A
book_idstringUnique identifier for the book being checked outBK101
book_titlestringTitle of the book being checked outTo Kill a Mockingbird
borrower_idstringUnique identifier for the borrowerBR201
borrower_namestringFull name of the borrowerEmily Johnson
Numbers 1 column
renewal_countintegerNumber of times the checkout has been renewed0 or more0
Dates and times 3 columns
checkout_datedateDate when the book was checked out2024-03-02
due_datedateDate when the book is due to be returned2024-03-16
return_datedateDate when the book was actually returned (if applicable)optional2024-03-15
True or false 2 columns
returnedbooleanIndicates whether the book has been returnedtrue
overduebooleanIndicates whether the book was returned after the due datefalse

Use it for

  • returned62%124 of 200 rows

    An education dashboard

    The returned rate and renewal_count. Excel, Power BI or Tableau.

  • Why do 124 of 200 rows have returned = true?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 200 rows.

  • A software demo

    Believable checkouts with book_id, book_title and borrower_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 11 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows11 columns
Yours1,000 rows11 columns

blueprint · library-checkouts

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 11 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Checkout date before due date
  • Loan period varies by item type
  • Renewals allowed up to maximum count
  • Late fees calculated after due date
  • Status: checked out, returned, overdue, lost
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
library-checkouts

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