Key Calculations Explained
1. Relative Use
Relative Use is a powerful metric that shows how efficiently a specific collection is being used in relation to its size. It helps to identify collections that are either outperforming or underperforming relative to their share of the total collection.
The formula is:
Relative Use= Item Percentage / Circulation Percentage
Circulation Percentage is the percentage of a collection’s total circulations out of the library’s overall circulation.
Item Percentage is the percentage of a collection’s total items out of the library’s overall item count.
Interpreting the Value:
A Relative Use greater than 1.0 indicates that the collection is being circulated more than its size would suggest, meaning it’s highly efficient and in high demand.
A Relative Use less than 1.0 indicates that the collection is being circulated less than its size would suggest, indicating potential underutilization.
2. Percentage Checked Out
This metric provides a snapshot of a collection’s activity at a specific point in time. It measures what percentage of the items in a given collection are currently in circulation.
The formula is:
Percentage Checked Out= Total Items in Collection / Items Checked Out
Interpreting the Value:
A high percentage suggests that the collection is in high demand and that most items are actively in use by patrons.
A low percentage may indicate that items are frequently on the shelves and that the collection has lower current demand.
3. Total Circulation
Total Circulation is a fundamental metric that represents the overall activity for a collection within a specified period. This value is a straightforward summation of all items that were checked out, renewed, or otherwise recorded as being circulated.
The formula is:
Total Circulation=Checkouts + Check-ins + Renewals Interpreting the Value: This metric provides a direct measure of a collection’s volume of use, which can be compared over time or across different collections to identify overall trends in patron behavior.
2. Time-Based Trend Analysis
Seasonal Patterns
`summarise()` has grouped output by 'month_name'. You can override using the
`.groups` argument.
Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.
| Apr |
#N/A |
0 |
0 |
| Apr |
Adult |
444472 |
310424 |
| Apr |
Early |
102147 |
66476 |
| Apr |
Juvenile |
59807 |
36417 |
| Apr |
Kids |
146852 |
85607 |
| Apr |
Staff |
36 |
29 |
| Apr |
Teen |
17777 |
11666 |
| Aug |
#N/A |
0 |
0 |
| Aug |
Adult |
435406 |
313508 |
| Aug |
Early |
102719 |
72012 |
| Aug |
Juvenile |
70483 |
46496 |
| Aug |
Kids |
148602 |
89549 |
| Aug |
Staff |
17 |
13 |
| Aug |
Teen |
21570 |
14045 |
| Dec |
#N/A |
0 |
0 |
| Dec |
Adult |
387543 |
274663 |
| Dec |
Early |
98847 |
58602 |
| Dec |
Juvenile |
52668 |
32327 |
| Dec |
Kids |
117999 |
68191 |
| Dec |
Staff |
58 |
44 |
| Dec |
Teen |
16358 |
11710 |
| Feb |
#N/A |
0 |
0 |
| Feb |
Adult |
502781 |
357307 |
| Feb |
Early |
117569 |
82440 |
| Feb |
Juvenile |
64756 |
43464 |
| Feb |
Kids |
159600 |
98175 |
| Feb |
Staff |
52 |
41 |
| Feb |
Teen |
18187 |
12390 |
| Jan |
#N/A |
0 |
0 |
| Jan |
Adult |
527077 |
382024 |
| Jan |
Early |
117769 |
85900 |
| Jan |
Juvenile |
67129 |
46379 |
| Jan |
Kids |
163057 |
103432 |
| Jan |
Staff |
61 |
31 |
| Jan |
Teen |
20441 |
14054 |
| Jul |
#N/A |
0 |
0 |
| Jul |
Adult |
446356 |
319693 |
| Jul |
Early |
102223 |
72374 |
| Jul |
Juvenile |
80020 |
54666 |
| Jul |
Kids |
161821 |
97215 |
| Jul |
Staff |
42 |
34 |
| Jul |
Teen |
25583 |
17843 |
| Jun |
#N/A |
16 |
12 |
| Jun |
Adult |
481418 |
348550 |
| Jun |
Early |
115670 |
86944 |
| Jun |
Juvenile |
85894 |
65039 |
| Jun |
Kids |
175122 |
111295 |
| Jun |
Staff |
37 |
25 |
| Jun |
Teen |
26925 |
20284 |
| Mar |
#N/A |
0 |
0 |
| Mar |
Adult |
512061 |
361291 |
| Mar |
Early |
121386 |
84135 |
| Mar |
Juvenile |
72396 |
49900 |
| Mar |
Kids |
171284 |
104981 |
| Mar |
Staff |
68 |
53 |
| Mar |
Teen |
20923 |
14696 |
| May |
#N/A |
0 |
0 |
| May |
Adult |
445340 |
311887 |
| May |
Early |
94726 |
63205 |
| May |
Juvenile |
60878 |
38691 |
| May |
Kids |
142233 |
82753 |
| May |
Staff |
30 |
17 |
| May |
Teen |
19199 |
13506 |
| Nov |
Adult |
397502 |
282559 |
| Nov |
Early |
107636 |
74414 |
| Nov |
Juvenile |
59201 |
40802 |
| Nov |
Kids |
135273 |
82635 |
| Nov |
Staff |
113 |
97 |
| Nov |
Teen |
16089 |
11236 |
| Oct |
Adult |
411122 |
293012 |
| Oct |
Early |
114532 |
75772 |
| Oct |
Juvenile |
59030 |
38047 |
| Oct |
Kids |
140708 |
85786 |
| Oct |
Staff |
55 |
39 |
| Oct |
Teen |
16653 |
11197 |
| Sep |
#N/A |
0 |
0 |
| Sep |
Adult |
403123 |
287799 |
| Sep |
Early |
105136 |
72374 |
| Sep |
Juvenile |
61247 |
39616 |
| Sep |
Kids |
134437 |
82386 |
| Sep |
Staff |
39 |
27 |
| Sep |
Teen |
16674 |
10948 |
3. Collection Management Insights
Fiction vs. Nonfiction Analysis
`summarise()` has grouped output by 'age'. You can override using the `.groups`
argument.
| #N/A |
#N/A |
1597 |
16 |
12 |
4 |
0.008 |
0.333 |
| Adult |
Equipment |
106419 |
153681 |
113522 |
40159 |
1.067 |
0.354 |
| Adult |
Fiction |
4859745 |
2258366 |
1513230 |
745136 |
0.311 |
0.492 |
| Adult |
Magazine |
674579 |
250662 |
124704 |
125958 |
0.185 |
1.010 |
| Adult |
Music CD |
1169548 |
245408 |
171982 |
73426 |
0.147 |
0.427 |
| Adult |
NF |
5292282 |
1041594 |
625319 |
416273 |
0.118 |
0.666 |
| Adult |
Videogame |
82297 |
69935 |
32872 |
37063 |
0.399 |
1.127 |
| Adult |
both |
92759 |
36320 |
31550 |
4770 |
0.340 |
0.151 |
| Early |
Fiction |
1445357 |
955309 |
657950 |
297359 |
0.455 |
0.452 |
| Early |
NF |
82621 |
18431 |
12839 |
5592 |
0.155 |
0.436 |
| Juvenile |
Equipment |
1038 |
2137 |
2133 |
4 |
2.055 |
0.002 |
| Juvenile |
Fiction |
1653601 |
781624 |
522607 |
259017 |
0.316 |
0.496 |
| Juvenile |
NF |
8766 |
1196 |
839 |
357 |
0.096 |
0.426 |
| Kids |
Equipment |
80803 |
94103 |
55414 |
38689 |
0.686 |
0.698 |
| Kids |
Fiction |
617596 |
521801 |
278404 |
243397 |
0.451 |
0.874 |
| Kids |
Magazine |
28458 |
19744 |
7959 |
11785 |
0.280 |
1.481 |
| Kids |
Music CD |
92541 |
32500 |
19237 |
13263 |
0.208 |
0.689 |
| Kids |
NF |
1981757 |
396281 |
260880 |
135401 |
0.132 |
0.519 |
| Kids |
Videogame |
109088 |
159514 |
74047 |
85467 |
0.679 |
1.154 |
| Staff |
Magazine |
10514 |
0 |
0 |
0 |
0.000 |
NaN |
| Staff |
NF |
14905 |
495 |
357 |
138 |
0.024 |
0.387 |
| Teen |
Equipment |
1602 |
1015 |
1013 |
2 |
0.632 |
0.002 |
| Teen |
Fiction |
13682 |
1544 |
1012 |
532 |
0.074 |
0.526 |
| Teen |
Magazine |
226 |
16 |
7 |
9 |
0.031 |
1.286 |
| Teen |
Videogame |
1283 |
968 |
968 |
0 |
0.754 |
0.000 |
Holds Analysis
`summarise()` has grouped output by 'format'. You can override using the
`.groups` argument.
| Book |
Adult |
26202 |
9187147 |
0.003 |
| Periodical |
Adult |
10733 |
670792 |
0.016 |
| Book |
Kids |
6684 |
2575226 |
0.003 |
| Book |
Early |
4265 |
1996913 |
0.002 |
| Book |
Juvenile |
2855 |
1645577 |
0.002 |
| Book |
Teen |
2681 |
584367 |
0.005 |
| Movie |
Adult |
2424 |
2226901 |
0.001 |
| Equipment |
Kids |
751 |
80803 |
0.009 |
| Equipment |
Adult |
600 |
106419 |
0.006 |
| Movie |
Kids |
583 |
508381 |
0.001 |
| Audiobook |
Adult |
558 |
597227 |
0.001 |
| Periodical |
Kids |
457 |
28458 |
0.016 |
| Videogame |
Kids |
411 |
109088 |
0.004 |
| Music CD |
Adult |
398 |
1169548 |
0.000 |
| Music CD |
Kids |
348 |
92541 |
0.004 |
| Videogame |
Adult |
167 |
82297 |
0.002 |
| Audiobook |
Juvenile |
111 |
63178 |
0.002 |
| Map |
Adult |
67 |
16964 |
0.004 |
| Movie |
Staff |
19 |
20789 |
0.001 |
| Audiobook |
Teen |
5 |
3875 |
0.001 |
| CD-Rom |
Adult |
2 |
3962 |
0.001 |
| #N/A |
#N/A |
0 |
1597 |
0.000 |
| Book |
Staff |
0 |
1668 |
0.000 |
| Equipment |
Juvenile |
0 |
1038 |
0.000 |
| Equipment |
Teen |
0 |
1602 |
0.000 |
| Microfilm |
Adult |
0 |
17066 |
0.000 |
| Periodical |
Staff |
0 |
10514 |
0.000 |
| Periodical |
Teen |
0 |
226 |
0.000 |
| Videogame |
Teen |
0 |
1283 |
0.000 |
| eMaterial |
Adult |
0 |
91782403 |
0.000 |
| eMaterial |
Kids |
0 |
8014307 |
0.000 |
| eMaterial |
Teen |
0 |
106267 |
0.000 |
2. Time-Based Trend Analysis
Data on circulation over time offers insights into seasonal changes and long-term recovery.
Post-COVID-19 Recovery: The Recovery and Growth by Year and Format table shows that both Book and eMaterial checkouts saw a significant rebound starting in 2021 after a dip in 2020. This suggests that patrons returned to physical and digital library services as the pandemic’s impact waned.
Monthly Fluctuation: The Seasonal Patterns data reveals that library use varies by month. Juvenile and Kids circulation seems to peak in the summer months (July and August), likely due to summer reading programs and school breaks. Meanwhile, Adult circulation appears to be more consistent throughout the year.
3. Collection Management Insights
The detailed analysis of different collection types provides actionable intelligence for future development.
High-Demand Items: The Holds Analysis table is a direct indicator of patron demand. It shows that eMaterial has a significantly higher number of holds (999,029 total items, with a total of 2,731 holds, not accounting for the high checkout rate), while Adult and Kids books also have substantial holds. This data can justify purchasing more licenses for popular eMaterials or adding more copies of highly-requested physical books.
New vs. Old Materials: The New vs. Stacks Collection Performance table clearly demonstrates the value of new items. Hot Picks and New materials have a much higher circulation_intensity (1.413 and 1.284, respectively) compared to Stacks (0.324). This reinforces the importance of a well-maintained and constantly updated “new materials” section to drive patron engagement.
Fiction vs. Nonfiction: The Fiction vs. Nonfiction table shows that while both Adult Fiction and Adult Nonfiction have similar circulation, Adult Fiction has a higher renewal_rate (0.492) than Adult Nonfiction (0.666). This suggests that fiction titles may be more likely to be read to completion and renewed.
