Cook County Data Portal Skill

Query and download datasets from the Cook County Open Data Portal using the Socrata Open Data API (SODA) and SoQL.

Prerequisites

Before querying, check if the user has an app token:

1. Look for

   COOK_COUNTY_DATA_PORTAL_TOKEN

   in the user's

   .env

   file
2. If not found, check for

   CHICAGO_DATA_PORTAL_TOKEN

   (both portals use Socrata, so tokens are interchangeable)
3. If found, use it in requests via header:

   X-App-Token: <token>

4. If neither token exists, instruct the user to:
   • Sign up at https://datacatalog.cookcountyil.gov/signup (or https://data.cityofchicago.org/signup)
   • Create an app token in Developer Settings
   • Add to

     .env

     :

     COOK_COUNTY_DATA_PORTAL_TOKEN=your_token_here

Queries work without a token but are rate-limited.

Quick Start

The Cook County Data Portal is at

datacatalog.cookcountyil.gov

uzyt-m557

Workflow

Step 1: Clarify the Data Need

Ask the user:

• Topic: What data? (property assessments, court cases, payroll, medical examiner, etc.)
• Geography: Countywide, township, municipality, or specific parcel/PIN?
• Time window: Date range, tax year, or fiscal quarter?
• Output: JSON (code) or CSV (Excel)?
• Granularity: Raw rows or aggregated counts?

Step 2: Find the Dataset

Option A - Catalog Search API:

GET https://api.us.socrata.com/api/catalog/v1?domains=datacatalog.cookcountyil.gov&q=<keywords>

Option B - Portal UI: Browse https://datacatalog.cookcountyil.gov and use the search bar.

Deliverable: Dataset name, 4x4 ID, and API endpoint.

See

references/datasets-*.md

• references/datasets-property.md

  - Assessor, Treasurer, parcel data

• references/datasets-courts.md

  - State's Attorney, sentencing, dispositions

• references/datasets-health.md

  - Medical Examiner cases

• references/datasets-finance.md

  - Payroll, procurement, budgets

Step 3: Get Dataset Metadata

Fetch schema and column info:

GET https://datacatalog.cookcountyil.gov/api/views/<4x4-ID>

Key fields in response:

• columns[].fieldName

  - exact column names for queries

• columns[].dataTypeName

  - data type (text, number, calendar_date, location, etc.)

• columns[].description

  - what the column means

• rowsUpdatedAt

  - last data update timestamp

Always verify column names from metadata before building queries.

Step 4: Build the Query

Legacy GET (simple, recommended for most cases):

https://datacatalog.cookcountyil.gov/resource/<4x4-ID>.json?$where=<filter>&$limit=1000

SODA3 POST (complex queries):

curl -X POST \
  -H "X-App-Token: YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"query": "SELECT * WHERE year = 2024", "page": {"pageNumber": 1, "pageSize": 1000}}' \
  https://datacatalog.cookcountyil.gov/api/v3/views/<4x4-ID>/query.json

Step 5: Handle Pagination

Default limit is 1000 rows. For larger extracts:

$limit=1000&$offset=0    # Page 1
$limit=1000&$offset=1000 # Page 2

Always include

$order

$order=year DESC&$limit=1000&$offset=0

For full dataset export, use CSV:

https://datacatalog.cookcountyil.gov/api/views/<4x4-ID>/rows.csv?accessType=DOWNLOAD

SoQL Essentials

Query Parameters

$select

$select=pin,year,mailed_tot

$where

$where=year=2024

$group

$group=township_code

$having

$having=count(*)>100

$order

$order=year DESC

$limit

$limit=500

$offset

$offset=1000

Syntax Rules

• Backticks around column names:

  `column_name`

• Single quotes for strings:

  'value'

• Dates as ISO strings:

  '2024-01-01T00:00:00'

Common Filters

-- Year range
$where=year >= 2020 AND year <= 2024

-- PIN lookup (zero-pad to 14 digits)
$where=pin = '12345678901234'

-- Text matching (case-insensitive)
$where=upper(manner_of_death) = 'HOMICIDE'

-- Null handling
$where=latitude IS NOT NULL

-- Multiple values
$where=township_code IN ('10', '20', '30')

Aggregations

$select=township_code, count(*) as total, avg(mailed_tot) as avg_value
$group=township_code
$order=total DESC

See

references/soql-quick-ref.md

Geospatial Queries

If the dataset has a location field (Point type):

-- Within radius (meters from downtown Chicago)
$where=within_circle(location, 41.8781, -87.6298, 5000)

-- Within bounding box
$where=within_box(location, 42.0, -87.9, 41.6, -87.5)

-- Within polygon
$where=within_polygon(location, 'MULTIPOLYGON(((-87.6 41.8, -87.5 41.8, -87.5 41.9, -87.6 41.9, -87.6 41.8)))')

App Tokens

Unauthenticated requests are rate-limited. Register for a free app token:

1. Create account at https://datacatalog.cookcountyil.gov
2. Go to Developer Settings
3. Create New App Token
4. Use via header:

   X-App-Token: YOUR_TOKEN

Cook County Specifics

Parcel Index Numbers (PINs)

• PINs are 14-digit identifiers for parcels
• Always zero-pad when querying:

  '01234567890123'

• Some exports may drop leading zeros; re-pad before joining datasets

Tax Years vs Calendar Years

• Assessor data uses tax year (property taxes assessed)
• Tax year 2024 bills are paid in 2025
• Use

  year

  or

  tax_year

  columns accordingly

Townships

• Cook County has 38 townships
• Township codes are 2-digit strings (e.g.,

  '10'

  = Barrington)
• See Assessor datasets for township boundaries

Fiscal Quarters (Payroll)

• Q1: December - February
• Q2: March - May
• Q3: June - August
• Q4: September - November

Output Format

Provide the user with:

1. Dataset: Name + 4x4 ID + portal link
2. Columns used: Exact field names
3. Query: Formatted SoQL
4. How to run: curl command or full URL
5. Assumptions: Time zone, update frequency, any caveats

Example Response Format

Dataset: Assessor - Assessed Values (uzyt-m557)
https://datacatalog.cookcountyil.gov/d/uzyt-m557

Query:
SELECT pin, year, class, mailed_tot, certified_tot
WHERE year = 2024 AND township_code = '70'
ORDER BY mailed_tot DESC
LIMIT 100

Run it:
curl "https://datacatalog.cookcountyil.gov/resource/uzyt-m557.json?\$select=pin,year,class,mailed_tot,certified_tot&\$where=year%20=%202024%20AND%20township_code%20=%20%2770%27&\$order=mailed_tot%20DESC&\$limit=100"

Note: Values are assessed values, not market values. Adjust by level of assessment to get market value.

Troubleshooting

Additional Resources

• references/datasets-property.md

  - Property & Taxation datasets

• references/datasets-courts.md

  - Courts & Legal datasets

• references/datasets-health.md

  - Health & Medical Examiner datasets

• references/datasets-finance.md

  - Finance & Administration datasets

• references/soql-quick-ref.md

  - All SoQL functions

• examples/python-query.py

  - Python code snippet

• examples/curl-examples.sh

  - curl command templates