National Childcare Price Search

National childcare price data — county by county, age group by age group — drawn directly from the U.S. Department of Labor Women's Bureau National Database of Childcare Prices (NDCP). This actor covers 3,000+ US counties across 15 years of study data (2008–2022) and is the most comprehensive federal source for childcare cost research available as structured output.

Each record pairs center-based and family-based weekly prices across four age groups — infant, toddler, preschool, and school-age — with county-level demographic context and a built-in affordability analysis benchmarked against the HHS 7% threshold. Whether you are a policy researcher, employer benefits team, journalist, or real estate analyst, you get clean, structured childcare price data without parsing government APIs yourself.

What data can you extract?

Why use National Childcare Price Search?

Finding reliable, structured childcare cost data by county requires navigating the DOL Open Data Portal API, understanding the NDCP dataset schema, building paginated queries with correct filter syntax, and then cleaning and enriching the raw output. That process takes a developer several hours and requires an API key, knowledge of the WB/ndcp endpoint, and patience for rate limiting.

This actor automates the entire process: it builds the correct DOL API filter from your inputs, paginates through results with automatic retry on rate-limit responses (exponential backoff up to 4 attempts), transforms raw government field names into readable camelCase output, computes affordability percentages against HHS benchmarks, and assembles a full summary with the top 10 most expensive and most affordable counties from your result set.

• Scheduling — run quarterly to track year-over-year childcare price trends by county or state
• API access — trigger runs from Python, JavaScript, or any HTTP client and pipe results into dashboards
• Monitoring — get Slack or email alerts if runs fail or return unexpectedly empty results
• Integrations — export directly to Google Sheets, Zapier, Make, or push to webhooks for downstream workflows
• Apify free tier — new accounts include $5 of monthly credits, enough for hundreds of county records

Features

• 15 years of data — the NDCP covers study years 2008 through 2022, enabling longitudinal childcare cost analysis at the county level
• 3,000+ US counties — near-complete national coverage using FIPS codes for unambiguous geographic matching
• Four age groups per provider type — infant, toddler, preschool, and school-age prices for both center-based (mc_*) and family-based (mfcc_*) care
• Built-in affordability scoring — calculates annual infant care cost as a percentage of median household income, rated against the HHS 7% threshold into four tiers: Affordable, Moderate, Expensive, Very Expensive
• County demographic context — each record includes total population, median household income (mhi_2019), median earnings (me_2019), poverty rate, unemployment rate, and labor force participation
• Computed aggregate prices — averageCenterPrice and averageFamilyPrice are calculated as non-null averages across all four age groups per record
• Automatic pagination — fetches up to 5,000 records across multiple 1,000-record DOL API pages with a 500ms inter-page delay
• Exponential backoff retry — handles HTTP 429 rate-limit responses with 2^attempt × 2000ms wait, up to 4 retries per page
• Flexible filtering — filter by state abbreviation (exact match), county name (partial match via SQL LIKE), exact year, or year range (yearFrom/yearTo)
• Compound filter support — combines multiple conditions into a single DOL API filter_object using and logic
• Run summary with rankings — every run produces a summary object including averages, year range, top 10 most expensive counties, top 10 most affordable counties, and per-state breakdowns
• Dry run mode — returns realistic sample data for New York County, San Francisco County, and Douglas County (NE) without consuming an API call

Use cases for childcare price data

Policy research and advocacy

Policy researchers, think tanks, and advocacy organizations use NDCP data to measure childcare affordability gaps across geographies and time periods. Querying all counties in a state over multiple years produces the trend data needed to support legislative testimony, grant applications, or published reports on the childcare affordability crisis.

Employer benefits planning

HR and total compensation teams use county-level childcare costs to benchmark childcare subsidy programs, set dependent care FSA contribution guidance, and evaluate office-location decisions. A firm relocating operations from San Francisco County to Douglas County, NE can quantify exactly how much the move reduces the childcare burden on employees with infants.

Real estate and cost-of-living analysis

Residential real estate platforms, relocation services, and cost-of-living calculators integrate childcare prices as a key household expense variable. Weekly center-based infant costs of $450 in New York County versus $220 in Omaha represent a $11,960 annual difference — a material factor for families evaluating a move.

Journalism and data reporting

Data journalists covering family economics, workforce participation, or inequality use the NDCP to produce county-level stories with real numbers. The built-in affordability rating and income percentage fields make it straightforward to identify counties where center-based infant care exceeds 25% of median household income.

Nonprofit and childcare desert mapping

Nonprofits working on childcare access pair price data with supply-side information to identify areas where care is both scarce and unaffordable. The h_under6_both_work and h_under6_f_work demographic fields in the underlying dataset quantify how many households with young children have dual working parents.

Academic and economic research

Economists studying labor force participation, wage gaps, and household formation use NDCP data as a control variable. The dataset's consistent methodology across 3,000+ counties and 15 years makes it suitable for panel regression studies on how childcare costs affect maternal employment rates.

How to search childcare price data

1. Get a free DOL API key — register at dataportal.dol.gov/registration. The key is free and issued immediately. Enter it in the apiKey field.
2. Set your filters — enter a two-letter state abbreviation (e.g., CA) in the state field, optionally add a countyName partial match (e.g., San), and set a year or year range. Leave all filters blank to retrieve recent national data.
3. Run the actor — click "Start". A query for one state and one year typically completes in under 30 seconds. A full national pull at maxResults: 5000 takes 2–4 minutes.
4. Download results — open the Dataset tab and export as JSON, CSV, or Excel. The summary object at the top of each record gives you aggregated rankings without additional processing.

Input parameters

Input examples

Search all Texas counties for the most recent study year:

{
    "apiKey": "YOUR_DOL_API_KEY",
    "dryRun": false,
    "state": "TX",
    "year": 2022,
    "maxResults": 500
}

Compare childcare prices across a decade in California:

{
    "apiKey": "YOUR_DOL_API_KEY",
    "dryRun": false,
    "state": "CA",
    "yearFrom": 2012,
    "yearTo": 2022,
    "maxResults": 2000
}

Quick county lookup by name (no state filter):

{
    "apiKey": "YOUR_DOL_API_KEY",
    "dryRun": false,
    "countyName": "Maricopa",
    "maxResults": 50
}

Input tips

• Start with dry run mode — omit the apiKey or set dryRun: true to see the full output structure with sample data before committing an API call.
• Register your DOL key before running — the key is free and issued instantly at dataportal.dol.gov/registration; you cannot run against real data without it.
• Use year: 2022 for most research — 2022 is the most recent study year in the dataset and the default sort order returns it first.
• Combine state and yearFrom/yearTo for trend analysis — requesting a single state across 10 years produces a manageable dataset (typically 250–500 records) for longitudinal analysis.
• Set maxResults conservatively — for a single state and year, 500 is more than enough; national pulls may need 3,000–5,000.

Output example

{
    "records": [
        {
            "countyFips": "36061",
            "countyName": "New York",
            "state": "New York",
            "stateAbbr": "NY",
            "year": 2022,
            "centerBased": {
                "infant": 450,
                "toddler": 400,
                "preschool": 375,
                "schoolAge": 280
            },
            "familyBased": {
                "infant": 320,
                "toddler": 290,
                "preschool": 270,
                "schoolAge": 210
            },
            "averageCenterPrice": 376,
            "averageFamilyPrice": 273,
            "demographics": {
                "totalPopulation": 1694251,
                "medianIncome": 93651,
                "medianEarnings": 72816,
                "povertyRate": 15.2,
                "unemploymentRate": 5.8,
                "laborForceParticipation": 69.1
            },
            "affordability": {
                "centerCostAsPercentOfIncome": 24.98,
                "familyCostAsPercentOfIncome": 17.78,
                "affordabilityRating": "Very Expensive"
            },
            "extractedAt": "2026-03-20T10:14:33.221Z"
        }
    ],
    "summary": {
        "totalRecords": 62,
        "yearRange": "2022–2022",
        "avgCenterInfant": 312,
        "avgCenterPreschool": 271,
        "avgFamilyInfant": 224,
        "avgFamilyPreschool": 196,
        "topExpensiveCounties": [
            { "county": "New York", "state": "NY", "centerInfant": 450 },
            { "county": "Kings", "state": "NY", "centerInfant": 435 },
            { "county": "San Francisco", "state": "CA", "centerInfant": 420 }
        ],
        "topAffordableCounties": [
            { "county": "Owsley", "state": "KY", "centerInfant": 115 },
            { "county": "Holmes", "state": "MS", "centerInfant": 120 },
            { "county": "McDowell", "state": "WV", "centerInfant": 125 }
        ],
        "byState": [
            { "state": "NY", "records": 62, "avgCenterInfant": 388 },
            { "state": "CA", "records": 58, "avgCenterInfant": 341 }
        ]
    }
}

Output fields

Affordability rating scale

Based on the HHS benchmark that childcare should cost no more than 7% of household income:

How much does it cost to search childcare price data?

National Childcare Price Search uses pay-per-result pricing — you pay only for Apify platform compute. Because this actor calls the DOL API rather than scraping the web, it is lightweight: typical runs consume 128 MB RAM for under one minute, making per-run costs very low.

You can set a maximum spending limit per run to control costs. The actor stops when your budget is reached.

Apify's free tier includes $5 of monthly credits — enough to run hundreds of national childcare price queries. There is no subscription required.

Search childcare price data using the API

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("ryanclinton/childcare-price-data").call(run_input={
    "apiKey": "YOUR_DOL_API_KEY",
    "dryRun": False,
    "state": "TX",
    "year": 2022,
    "maxResults": 500
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    for record in item.get("records", []):
        county = record["countyName"]
        state = record["stateAbbr"]
        infant_price = record["centerBased"]["infant"]
        rating = record["affordability"]["affordabilityRating"]
        print(f"{county}, {state}: ${infant_price}/week (infant center) — {rating}")

JavaScript

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });

const run = await client.actor("ryanclinton/childcare-price-data").call({
    apiKey: "YOUR_DOL_API_KEY",
    dryRun: false,
    state: "CA",
    yearFrom: 2018,
    yearTo: 2022,
    maxResults: 1000
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const item of items) {
    for (const record of item.records ?? []) {
        console.log(
            `${record.countyName}, ${record.stateAbbr} (${record.year}): ` +
            `center infant $${record.centerBased.infant}/wk — ` +
            `${record.affordability.affordabilityRating}`
        );
    }
}

cURL

# Start the actor run
curl -X POST "https://api.apify.com/v2/acts/ryanclinton~childcare-price-data/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "apiKey": "YOUR_DOL_API_KEY",
    "dryRun": false,
    "state": "FL",
    "year": 2022,
    "maxResults": 300
  }'

# Fetch results (replace DATASET_ID from the run response above)
curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_API_TOKEN&format=json"

How National Childcare Price Search works

Data source and API connection

The actor queries the DOL Women's Bureau National Database of Childcare Prices at https://apiprod.dol.gov/v4/get/WB/ndcp/json. All requests include the user-supplied API key in the X-API-KEY query parameter alongside limit, offset, sort=desc, and sort_by=study_year to return the most recent records first. Each page fetches up to 1,000 records; the actor continues paginating with a 500ms inter-page delay until it reaches maxResults or the API returns fewer records than the page size.

Filter construction

Filters are serialized as JSON and URL-encoded into the filter_object parameter. A single filter condition (e.g., state equals TX) maps to { field, operator, value }. Multiple conditions are wrapped in { and: [...] }. The actor supports eq (exact match for state and year), like (partial match for county name with % wildcards), gte and lte (for year range bounds). If no filters are provided, the actor fetches national data sorted by most recent year.

Rate-limit handling and retry logic

When the DOL API responds with HTTP 429, the actor waits 2^attempt × 2000ms before retrying — 4 seconds on the first retry, 8 seconds on the second, 16 seconds on the third, up to 4 attempts. On other non-OK responses, it uses a simpler 2^attempt × 1000ms backoff. HTTP 401 and 403 errors log a clear message directing the user to register a free API key and terminate immediately without retrying.

Record transformation and affordability calculation

Raw DOL field names (mc_infant, mfcc_toddler, mhi_2019, etc.) are mapped to structured camelCase output. The affordability percentage is calculated as (weeklyInfantPrice × 52) / medianHouseholdIncome × 100, rounded to two decimal places. The rating is assigned by comparing this figure to the HHS 7% benchmark: ≤7% = Affordable, 7–14% = Moderate, 14–21% = Expensive, >21% = Very Expensive. The summary is built by aggregating all records in memory: sorting for top-10 expensive and affordable counties, computing per-state averages, and calculating cross-record mean prices for each age group.

Tips for best results

1. Use the most recent year for benchmarking. 2022 is the latest study year available. Set year: 2022 to get the most current prices for location comparisons or benefits calculations.

2. Use year ranges for trend analysis, not individual queries. Requesting yearFrom: 2015, yearTo: 2022 for a single state in one run is more cost-efficient than eight separate annual queries and delivers a single summary with the full year range included.

3. Filter by county name when you need a specific jurisdiction. The countyName partial match works across states — querying countyName: "Orange" returns Orange County, CA; Orange County, FL; Orange County, NY and others simultaneously.

4. Review the summary object before exporting. The topExpensiveCounties and topAffordableCounties lists identify the outliers in your result set without post-processing. The byState breakdown is useful for multi-state comparison tables.

5. Pair with income data for deeper affordability research. The demographics.medianIncome field already in each record comes from the NDCP's embedded 2019 ACS data. For more recent income figures, cross-reference with other economic datasets.

6. Set maxResults to match your scope. A single state typically has 60–200 county records per year. Setting maxResults: 500 is safe for state-level work; set it to 3,000–5,000 only for national pulls.

7. Export as CSV for spreadsheet analysis. The Apify Dataset tab supports direct CSV export. Pivot on stateAbbr and year to build the time-series tables most common in policy research.

Combine with other Apify actors

Limitations

• Data ends at 2022. The NDCP is updated periodically by the DOL Women's Bureau; the actor reflects the most recent published dataset. Real-time or 2023+ data is not available through this source.
• Prices are weekly medians, not actual provider rates. The NDCP figures are county-level medians drawn from survey data, not prices scraped from individual providers. Actual rates at a specific daycare center will vary.
• Income data is from 2019 ACS. The medianIncome field uses 2019 American Community Survey data embedded in the NDCP, not current-year income estimates. Affordability percentages may be understated for counties with income growth since 2019.
• Not all counties have all age groups. Some counties have null values for certain age groups or provider types where survey data was insufficient. The averageCenterPrice and averageFamilyPrice fields exclude nulls from their calculations.
• Requires a free DOL API key. The actor cannot run against real data without registering at dataportal.dol.gov/registration. The dry run mode returns sample data only.
• No supply-side data. The NDCP measures prices but does not include the number of licensed slots, wait lists, or childcare desert indicators. Pair with state licensing databases for supply analysis.
• International data not available. Coverage is US counties only; no Canadian, UK, or other national data is included in the DOL NDCP.
• County-level granularity only. Data is not available at the city, ZIP code, or individual provider level through this dataset.

Integrations

• Zapier — trigger a childcare price search when a new employee record is added to your HR system and push results to a Slack channel
• Make — build an automated monthly benefits report that pulls the latest NDCP data for your office locations
• Google Sheets — export county childcare prices directly into a spreadsheet for policy briefings or board presentations
• Apify API — integrate childcare cost lookups into internal HR tools, relocation calculators, or benefits portals
• Webhooks — post results to a data warehouse or analytics platform when a scheduled run completes
• LangChain / LlamaIndex — feed structured childcare cost data into an AI assistant that answers employee questions about childcare affordability by location

Troubleshooting

Run returns sample data even though I provided an API key. Check that dryRun is explicitly set to false in your input. When dryRun is omitted, the actor defaults to true unless an apiKey is also provided in the same input object. Providing both apiKey and dryRun: false forces a live API call.

HTTP 401 or 403 error in the run log. Your DOL API key is invalid, expired, or was entered with leading/trailing whitespace. Re-register or regenerate your key at dataportal.dol.gov/registration. The field is marked as a secret in the input schema, so paste the key carefully.

No records found for my county name filter. County names in the NDCP are stored in uppercase (e.g., HARRIS, SAN FRANCISCO). The actor applies its own toUpperCase() conversion, so Harris and harris both work. If you get zero results, try a shorter partial match (e.g., Harris instead of Harris County) and verify the spelling.

Run times out on a large national pull. Fetching 5,000 records requires 5+ paginated API calls with inter-page delays. If your run is hitting the default timeout, reduce maxResults to 2,000–3,000, or increase the actor's memory allocation to 512 MB in the run configuration to allow more headroom.

Affordability rating is Unknown for some records. The affordability calculation requires medianIncome (the mhi_2019 field from the DOL dataset). Some counties have null income data in the NDCP. This is a gap in the source dataset, not an actor error.

Responsible use

• This actor accesses only publicly available government data published by the U.S. Department of Labor Women's Bureau.
• The DOL Open Data Portal API is a public service; use it responsibly and avoid high-frequency polling that could affect service for other users.
• NDCP data is published for research and policy purposes. Cite the DOL Women's Bureau as the data source in any published work.
• For guidance on using government data APIs, see the DOL Open Data Portal terms of service.

FAQ

How many counties does the National Childcare Price Search cover? The NDCP covers 3,000+ US counties across all 50 states and DC. Coverage varies by year — earlier study years (2008–2010) have slightly fewer counties than more recent ones. Set maxResults: 5000 with no state filter to retrieve the full national dataset for a given year.

What years of childcare price data are available? The dataset covers study years 2008 through 2022. The actor sorts results by most recent year first. Set year: 2022 to get the latest available data, or use yearFrom/yearTo for multi-year trend analysis.

Are the childcare prices weekly or monthly figures? All price fields (centerBased.*, familyBased.*) are weekly rates in US dollars, as published in the NDCP. To convert to monthly, multiply by 4.33. To convert to annual, multiply by 52 (which is how the affordability percentage is calculated internally).

How is the affordability rating calculated? The actor multiplies the weekly infant center price by 52 to get an annual cost, then divides by the county's median household income (2019 ACS data embedded in the NDCP) and multiplies by 100. The result is compared to the HHS benchmark: ≤7% = Affordable, 7–14% = Moderate, 14–21% = Expensive, >21% = Very Expensive.

Does childcare price data require a paid subscription? No. The DOL Open Data Portal API key is completely free. Register at dataportal.dol.gov/registration to get immediate access. Apify platform costs for running the actor are also very low — typically under $0.10 for a national pull.

How is this different from looking up NDCP data on the DOL website manually? The DOL website provides a data explorer with limited filtering and no structured export. This actor returns fully structured JSON with computed fields (affordability percentage, ratings, aggregated averages, top-county rankings) that the DOL portal does not calculate. Results are immediately downloadable as CSV or JSON and can be piped into any downstream system via API.

Can I search childcare prices for a specific city? The NDCP only provides county-level data — city-level breakdowns are not available in this dataset. Use the countyName filter to find the county containing your city of interest (e.g., countyName: "Cook" for Chicago, IL).

How accurate is the childcare price data? The NDCP figures are county-level medians derived from state-level market rate surveys, subsidy eligibility studies, and provider cost surveys. They represent the middle of the market distribution, not guaranteed prices at any specific provider. Actual center rates in expensive urban markets may be higher than the county median.

Can I schedule this actor to run automatically? Yes. Use the Apify Scheduler to run the actor weekly, monthly, or on any cron schedule. This is useful for tracking year-over-year changes when new NDCP study years are published, or for monitoring a set of target counties on a regular basis.

Is it legal to use DOL NDCP data in commercial research or products? Yes. The NDCP is published as open government data by the U.S. Department of Labor and is freely available for commercial and non-commercial use. Cite the source as: "National Database of Childcare Prices, Women's Bureau, U.S. Department of Labor." For full terms, see the DOL Open Data Portal.

What happens if I run without providing an API key? The actor defaults to dry run mode and returns 3 sample records (New York County NY, San Francisco County CA, Douglas County NE) with 2022 data. No DOL API call is made. This is useful for testing your downstream pipeline before committing a real run.

Can I combine childcare price data with other datasets? Yes. The countyFips field is a standard 5-digit FIPS code that joins cleanly with Census data, BLS employment data, ACS income data, and any other county-level federal dataset. Use it as the join key when enriching NDCP records with additional economic indicators.

Help us improve

If you encounter issues, you can help us debug faster by enabling run sharing in your Apify account:

1. Go to Account Settings > Privacy
2. Enable Share runs with public Actor creators

This lets us see your run details when something goes wrong, so we can fix issues faster. Your data is only visible to the actor developer, not publicly.

Support

Found a bug or have a feature request? Open an issue in the Issues tab on this actor's page. For custom solutions or enterprise integrations, reach out through the Apify platform.