Bring structured U.S. sex offender registry data into your product, research, or data pipeline.
Get linked CSV files and images for nationwide or selected-state coverage, with monthly or one-time delivery.
Request free sex offender CSV data sample for evaluation.
Sex offender CSV dataset at a glance
Coverage
Files & fields
Updates
Access & delivery
Explore CSV data
Delivery is a folder containing related CSV files and images. Main registry records connect to separate files for aliases, offenses, marks, vehicles, and photos.
The main CSV’s id matches offenderid in related CSVs for the same state.
Full name, first name, last name, middle name, date of birth, age, gender, race, ethnicity
Height, weight, eye color, hair color, build, complexion, scars, tattoos, marks
Known aliases, alternate names, prior names, name suffixes, nickname, maiden name
Address, city, state, ZIP, county, address type, previous addresses, address dates
Registered date, status, risk tier, source state, source ID, registry type, last verification date
Offense description, statute, conviction date, offense code, conviction details, release date
Victim sex, victim age range, victim minor, relationship to offender, multiple victims
Employer name, occupation, work address, work city, work state, work ZIP
Vehicles: make, model, year, color, plate; driver’s license; professional license info
Photos, offender profile link, source URL, source name, record last updated
Comments, disposition, court information, supervising agency, notes, other reference fields
Around 80+ data fields total
Field availability varies by state and source.
Data update process
Build a full monthly source load from official registries and supplementary public sources available during collection.
Standardize names, dates, addresses, and other published fields into a common schema. Source gaps can still leave fields empty.
Assign record IDs and merge duplicates within each state. Records from different states remain separate.
Keep previously collected records missing from a later load with their last collection month. Review unusual release changes.
Our public statistics compare record and photo counts by jurisdiction, show the difference from the previous month.
| Jurisdiction | Records | Change |
|---|---|---|
| TX |
103,482
|
+1.8% |
| CA |
34,041
|
|
| FL |
83,060
|
|
| PR |
2,478
|
+2.1% |
Data delivery process
Tell us your intended use, geographic scope, delivery cadence, and destination. We can share a sample so your team can review the CSV structure and available fields.
Ask sex offender dataset sampleWe send you the agreement to sign, then submit the signed agreement for bank verification. Verification takes 1–3 business days.
Request a draft agreementWe issue an invoice for the agreed billing period. You pay the invoice before delivery.
Ask about payment termsStandard delivery is through our S3. We can also deliver to your S3, Google Cloud Storage, Azure Blob, FTP, SFTP, or another agreed destination.
Ask sex offender database downloadFor recurring access, subsequent deliveries follow the agreed schedule. The underlying dataset refreshes monthly.
Discuss monthly sex offender data feedSame dataset · two access models
Bulk access
Bring the agreed dataset into your own environment and control ingestion, joins, and processing.
Request-based access
Retrieve possible registry matches through API requests rather than managing a bulk delivery.
Use cases
Nannostomus quotes CSV dataset pricing for your requested coverage and delivery schedule. Tell us whether you need nationwide access or selected states, and whether you want one-time or recurring delivery. We confirm the price and billing period before invoicing.
Yes. You can buy one dataset release for the agreed geographic coverage. A one-time sex offender dataset purchase includes that delivery only; future monthly updates are not included.
Request a real sample to inspect the column names, value formats, and related files before purchase. A state sample reflects the data available for that jurisdiction; it does not establish nationwide field completeness.
Yes. We discuss which states you need and provide sample data for those states. You can review the available fields, format, and fit for your use case before deciding to purchase. Your delivery covers the agreed states.
No. Nationwide describes geographic collection scope, not guaranteed completeness. Collection covers all 50 U.S. states, DC, five territories, and available tribal sources. Record and field availability depend on what each source publishes and what the collection process captures.
Nannostomus compiles sex offender public records from official registries and supplementary public sources. Around 80% of records include a link to the public source profile or registry page, so you can review the published information. Visit our Trust Center for the sources used in each jurisdiction, coverage details, and source limitations.
Yes. The delivery includes CSV files and a separate folder of image files where photos are available from the source. CSV files in photo/ provide photo references; the img/ folder holds the actual images.
The real sample shows column names, value formats, and relationships between files. If your team needs a sex offender data dictionary, ask us to clarify field definitions and empty-value handling before mapping the data into your system.
The 64-character record ID remains stable while the fields used to calculate it stay unchanged. It identifies a registry record, not a nationally resolved person. Deduplication is within states, so the same person can have separate records in different states. The total record count is not a count of unique people.
In the supplied NY sample, downloaddate uses the YYYYMM format and shows the last month the record was collected into Nannostomus’s database. A record refreshed in a later load gets a newer month. Records missing from a later source load are retained with their earlier collection month. This is not the source’s last-modified date or confirmation of current registry status.
An empty field can mean the source did not publish a value, collection or parsing did not capture it, or validation rejected it. A blank value should not be treated as proof that the information does not exist. Confirm the field’s meaning before deciding how to handle missing values in your system.
We notify customers about CSV schema changes by email, usually one month before the change. Use that notice to review field mappings and check whether your import needs to be adjusted.