Clean label
Toyota Camry
59,325
hidden by splits
144,981
cleaned records
104
raw variants
40.9%
fragmented
Raw source labels
TOYT CAMRY
85,656
TOYOTA CAMRY
36,311
TOYT Camry
9,270
TOYO Camry
7,576
TOYOTA Camry
4,202
Data cleaning impactPublic CCRS analysis
The public record is only as useful as the labels behind it.
Crash records guide city meetings, newsroom charts, grant proposals and transportation research. When one vehicle or crash cause is split across typos, abbreviations, and swapped fields, the public sees a weaker signal than the record actually contains.
This page shows how much interpretation changes after standardization, while keeping the original CCRS source values available for audit.
Vehicle records reviewed
4,818,302
2,648,388 crash records represented
Make and model changed
2,016,795
41.9% of reviewed vehicle party records
Labels brought together
12,157
94,516 raw labels to 82,359 cleaned labels
Active cleaning rules
3,275
Rules applied before public vehicle comparisons
For residents
A safer-street conversation should not depend on whether one model was typed three different ways.
For city staff
Bad labels can move a problem down the list before it ever reaches a grant memo, council packet, or safety plan.
For newsrooms
A ranking built from raw labels can turn a typo pattern into a headline. Cleaning is part of responsible reporting.
For police leaders
Fragmented records make it harder to see where training, forms, or review workflows are creating public confusion.
Why this matters
A real pattern can disappear into spelling noise.
Raw labels are not neutral. If a model is recorded several ways, a basic "top vehicles" chart undercounts it. The corrected view groups those labels into one analytical name, then keeps the raw variants visible.
Current example: Toyota Camry recovers 59,325 records that would otherwise sit under smaller aliases.
Clean label
Honda Civic
58,385
hidden by splits
147,082
cleaned records
68
raw variants
39.7%
fragmented
Raw source labels
HOND CIVIC
88,697
HONDA CIVIC
33,712
HOND Civic
14,575
HONDA Civic
8,540
HOND CIV
783
Clean label
Honda Accord
57,578
hidden by splits
140,006
cleaned records
77
raw variants
41.1%
fragmented
Raw source labels
HOND ACCORD
82,428
HONDA ACCORD
34,709
HOND Accord
13,511
HONDA Accord
8,440
HOND ACC
244
Clean label
Toyota Corolla
44,986
hidden by splits
113,711
cleaned records
112
raw variants
39.6%
fragmented
Raw source labels
TOYT COROLLA
68,725
TOYOTA COROLLA
26,224
TOYT Corolla
7,356
TOYO Corolla
6,106
TOYOTA Corolla
3,272
Before and after
The leaderboard can move after labels are grouped.
This is where data quality becomes a decision risk. A raw-label chart can rank a vehicle lower simply because its records were scattered across aliases.
| After cleaning | Best raw version | Recovered | Decision shift |
|---|---|---|---|
#2 Toyota Camry 144,981 cleaned records | TOYT CAMRY raw rank #3 | 50,042 | +1 places |
#3 Honda Accord 140,006 cleaned records | HOND ACCORD raw rank #2 | 44,041 | +-1 places |
#1 Honda Civic 147,082 cleaned records | HOND CIVIC raw rank #1 | 43,777 | same rank |
#4 Toyota Corolla 114,347 cleaned records | TOYT COROLLA raw rank #4 | 37,952 | same rank |
#15 Tesla Model 3 29,117 cleaned records | TESL MODEL 3 raw rank #99 | 22,726 | +84 places |
#6 Toyota Tacoma 69,497 cleaned records | TOYT TACOMA raw rank #7 | 21,885 | +1 places |
#5 Chevrolet Silverado 77,887 cleaned records | CHEV SILVERADO raw rank #6 | 20,780 | +1 places |
#7 Toyota Prius 63,906 cleaned records | TOYT PRIUS raw rank #8 | 20,006 | +1 places |
#9 Nissan Altima 60,824 cleaned records | NISS ALTIMA raw rank #11 | 18,912 | +2 places |
#28 Tesla Model Y 23,356 cleaned records | TESL Y raw rank #104 | 17,155 | +76 places |
Where the answer is fragile
ZIPs most sensitive to raw labels.
These ZIP areas have the highest share of changed vehicle labels. They deserve extra caution before someone uses raw records to describe local crash patterns.
Unincorporated / 95387
781 of 979 vehicle records changed
79.8%
Freightliner Cascadia
54
Honda Civic
41
Toyota Camry
35
Unincorporated / 95722
125 of 157 vehicle records changed
79.6%
Toyota Tacoma
7
Toyota Tundra
6
Chevrolet Silverado
5
Unincorporated / 93653
117 of 148 vehicle records changed
79.1%
Chevrolet Silverado
8
Toyota Corolla
7
Honda Accord
4
Unincorporated / 94128
945 of 1,199 vehicle records changed
78.8%
Toyota Corolla
55
Toyota Camry
50
Toyota Prius
50
Union City / 94587
2,950 of 3,769 vehicle records changed
78.3%
Toyota Camry
186
Honda Accord
177
Honda Civic
169
Current highest-impact ZIP: Unincorporated / 95387.
Reporting quality
Messy labels become public blind spots.
This is not a blame scoreboard. It is an audit trail for the places where public crash records need the most translation before anyone should compare them.
A fragmented record can make a vehicle trend, crash cause, or neighborhood risk look smaller than it is. That affects public meetings, newsroom charts, enforcement reviews, grant narratives, and the everyday driver trying to understand local danger.
Jurisdiction currently uses the CCRS city label as a public reporting proxy until a dedicated police-department dimension is exposed.
Places where vehicle labels changed most
Minimum 250 vehicle party records. Higher share means raw labels are more likely to distort local comparisons.
Delano
1,813 changed vehicle labels, 592 raw values collapsed to 468
77.5%
vehicle labels changed
Seal Beach
3,288 changed vehicle labels, 904 raw values collapsed to 792
75.6%
vehicle labels changed
South San Francisco
3,688 changed vehicle labels, 1,250 raw values collapsed to 994
74.0%
vehicle labels changed
Menlo Park
2,779 changed vehicle labels, 1,065 raw values collapsed to 868
73.2%
vehicle labels changed
San Bruno
2,716 changed vehicle labels, 996 raw values collapsed to 783
72.4%
vehicle labels changed
Unincorporated
933,268 changed vehicle labels, 47,538 raw values collapsed to 42,063
72.0%
vehicle labels changed
Orinda
1,268 changed vehicle labels, 542 raw values collapsed to 476
71.8%
vehicle labels changed
Millbrae
1,025 changed vehicle labels, 570 raw values collapsed to 453
71.7%
vehicle labels changed
Year-by-year cleanup sensitivity
If this line stays high, the issue is not a one-year typo batch.
Delano
2020 to 2026
20
21
22
23
24
25
26
Menlo Park
2020 to 2026
20
21
22
23
24
25
26
San Bruno
2020 to 2026
20
21
22
23
24
25
26
Seal Beach
2020 to 2026
20
21
22
23
24
25
26
South San Francisco
2020 to 2026
20
21
22
23
24
25
26
Crash-cause cleanup not shown yet
Primary Collision Factor means the reported crash cause or violation. Those mappings are still being reconciled, so this page avoids showing a misleading 0.0% score.
Cleaning progress
The current rulebook.
These mappings are applied before the public pages calculate vehicle rankings. Raw source values are preserved, so every cleaned label can still be audited.
Vehicle Make
83 clean labels
222
rules
Vehicle Make V2
38 clean labels
68
rules
Vehicle Model
1,693 clean labels
2,985
rules
Audit examples
Raw values mapped into clean labels.
Cascadia
32 raw values
Vehicle Model
Freightliner || 3 Axle CascadiaFreightliner || ASCADIAFreightliner || CASACADIAFreightliner || CASADIAFreightliner || CASCAFreightliner || CASCAD
Camry
19 raw values
Vehicle Model
Toyota || AMRYToyota || CAMToyota || CAMARYToyota || CAMERYToyota || CAMRToyota || CAMREY
Silverado
19 raw values
Vehicle Model
Chevrolet || 1500SILVERADOChevrolet || 2500SILVERADOChevrolet || SILERADOChevrolet || SILVARADOChevrolet || SILVARDOChevrolet || SILVER
Corolla
18 raw values
Vehicle Model
Toyota || CAROLLAToyota || COAToyota || CORLLAToyota || COROLToyota || COROL.LAToyota || COROLA
Odyssey
18 raw values
Vehicle Model
Honda || / ODYSSEY /Honda || ODDHonda || ODDYSEYHonda || ODDYSSEYHonda || ODESSEYHonda || ODY
Accord
17 raw values
Vehicle Model
Honda || / ACCORD /Honda || ACCHonda || ACCCORDHonda || ACCDHonda || ACCOHonda || ACCOD
scope
Summary totals include all vehicle labels. Example rankings filter out Unknown model labels so the public story focuses on resolved make-model cleanup.
privacy
The public report uses aggregate counts only and does not expose individual crash records.
comparison
Compares source vehicle labels to the current cleaned warehouse labels.
jurisdiction
Reporting-jurisdiction examples use CCRS city labels as the public agency proxy because no separate police-department dimension is currently exposed in the mart.
zip threshold
ZIP impact examples require at least 100 party vehicle records in the selected window.
Source: California Highway Patrol CCRS public records, processed independently in BigQuery. This page measures label standardization impact. It does not claim that one vehicle is more dangerous than another, and crash records are not adjusted for registrations, miles driven, or population exposure.