# Peerless Cleaners Locations — partial U.S.: 1 state (TX) location dataset

All 12 locations in partial U.S.: 1 state (TX), as one CSV: 42 fields per record, 1 states, file built October 8, 2026. $9 one-time, with up to 10 real rows free before you buy.

Canonical URL: https://locationlists.com/data/peerless-cleaners-locations

12 Peerless Cleaners locations from the locations page on Peerless' own site: Corpus Christi 8, Aransas Pass 2, and Ingleside and Portland 1 each. 10 are dry cleaning stores and 2 are laundromats. Every row has a phone, hours by day and the store's map point; isMainStore marks the main store.

## The figures

- Records: 12 locations
- States: 1
- Coverage: partial U.S.: 1 state (TX)
- Fields: 42
- Price: $9 one-time, CSV download, commercial license (https://locationlists.com/license)
- Snapshot built on October 8, 2026. Not rebuilt on a schedule.
- File last modified: 2026-10-08

## Fields

- `brand`: The brand the location trades under (in the bundle: which of the 28 lists the row comes from; Independent for the independents)
- `parentCompany`: The company that owns or franchises the brand, as the chain's own site names it
- `name`: The location's own name as its source publishes it
- `address`: Street address
- `city`: City
- `state`: Two-letter state code (DC for Washington, PR for Puerto Rico)
- `zip`: Five-digit ZIP code
- `country`: Country code (US)
- `phone`: Location phone number
- `website`: The location's own page on the chain's site, or the shop's own website
- `latitude`: GPS latitude
- `longitude`: GPS longitude
- `locationType`: What the location is in its source's own words (Tide's Store, Locker or Concierge; store + 24/7 kiosk; a state register's plant or drop-off)
- `hours`: Opening hours for the week, one entry per day, as the source publishes them
- `hours_mon`: Opening hours on Monday (24-hour clock)
- `hours_tue`: Opening hours on Tuesday (24-hour clock)
- `hours_wed`: Opening hours on Wednesday (24-hour clock)
- `hours_thu`: Opening hours on Thursday (24-hour clock)
- `hours_fri`: Opening hours on Friday (24-hour clock)
- `hours_sat`: Opening hours on Saturday (24-hour clock)
- `hours_sun`: Opening hours on Sunday (24-hour clock)
- `crossStreet`: The cross street the chain gives
- `locationLabel`: The location's label on the chain's site
- `isMainStore`: true for the chain's main store
- `sourceId`: The chain's own id for the location
- `sourceUrl`: The page or feed the row was read from
- `sources`: Every source the row's facts come from, joined with |: the chain's store locator, Overture Maps, a state dry-cleaner register, EPA ECHO
- `siteType`: What the location is, in one vocabulary across every list: store, plant, drop-off, locker, concierge, laundromat, mobile or restoration
- `status`: Open on the build date (NOW OPEN where the chain's page carries that banner)
- `directionsUrl`: A Google Maps directions link to the location
- `naicsCode`: NAICS industry code: 812320, Drycleaning and Laundry Services (except Coin-Operated)
- `naicsTitle`: Title of the NAICS code
- `sicCode`: SIC industry code: 7216, Drycleaning Plants, Except Rug Cleaning
- `sicTitle`: Title of the SIC code
- `sicCode2`: Second SIC code: 7212, Garment Pressing, and Agents for Laundries and Drycleaners
- `sicTitle2`: Title of the second SIC code
- `updatedDate`: The date the row was built from its source
- `geo_precision`: How the coordinates were arrived at: source (the publisher's own map point), address (a geocode of the street address), zip_centroid or city_centroid
- `county`: County name, from the US Census Bureau county list
- `county_fips`: Five-digit county FIPS code
- `county_note`: Set when the ZIP code spans more than one county: which county the row was placed in
- `address_quality`: How complete the street address is: complete, no_house_number, po_box, missing_city_or_zip or missing

## What we did to this data

Added the county to 12 listings and measured 12 rows. Rebuilt October 8, 2026 from peerlesscleaners.com.

## How complete the key fields are

phone 100%, website 100%, street address 100%, city 100%, state 100%, ZIP code 100%, latitude 100%, longitude 100%. 40 of 42 columns are filled on at least half the rows.

## Ask this list a question with a link

No connector and no account; each link answers with the matching count, preview rows and the price for just that part.

- [Within 25 miles of Corpus Christi, TX, the busiest area](https://locationlists.com/find?dataset=peerless-cleaners-locations&near=Corpus+Christi+TX&radius=25)
- [Within a 30-minute drive of Corpus Christi, TX](https://locationlists.com/find?dataset=peerless-cleaners-locations&near=Corpus+Christi+TX&drive=30)
- [Only rows where isMainStore is true](https://locationlists.com/find?dataset=peerless-cleaners-locations&where=isMainStore%3Aeq%3Atrue)
- [Every Dry Cleaners & Laundry list combined, within 25 miles of Corpus Christi, TX](https://locationlists.com/find?category=dry-cleaners&near=Corpus+Christi+TX&radius=25)
- [Each one's nearest Dependable Cleaners Stores, with miles](https://locationlists.com/find?dataset=peerless-cleaners-locations&relate=nearest&k=1&b.dataset=dependable-cleaners-locations)
- [The whole list: add a city, state, ZIP code or distance](https://locationlists.com/find?dataset=peerless-cleaners-locations)

## The same dataset, for machines

- Record as JSON: https://locationlists.com/data/peerless-cleaners-locations/dataset.json
- Free sample, up to 10 real rows: https://locationlists.com/data/peerless-cleaners-locations/sample.csv or https://locationlists.com/data/peerless-cleaners-locations/sample.json
- Buy link (opens Stripe Checkout): https://locationlists.com/data/peerless-cleaners-locations/buy

## Questions

### Why are there so many columns?

Because the file keeps every field the chain's locator and store pages publish for each location, not a shortlist: hours, services, prices, kiosks and lockers, and the rest. A column the source fills for only a few locations is still kept, and its fill is shown beside it on this page.

### Is this list in the Dry Cleaning Industry Bundle?

Yes. The bundle puts this list together with the other 26 chain lists and 16,550 independent and regional dry cleaners in one CSV, tagged by brand, for less than buying the lists one by one.

### How current is it?

Snapshot built on October 8, 2026. It is a one-time snapshot and is not rebuilt on a schedule.

### How is this data cleaned?

Every rebuild runs the same steps and counts what each one changed. For the current file, rebuilt October 8, 2026 from peerlesscleaners.com: Merged 0 duplicate listings that had the same business name, street address and ZIP code, keeping every filled-in detail from both (October 8, 2026). Unified 0 city names written more than one way within the same ZIP code (for example with and without a space or an abbreviation) to the US Census Bureau spelling (October 8, 2026). Corrected 0 misspelled city names to the US Census Bureau place name for their ZIP code (October 8, 2026). Added map coordinates to 0 listings that had none, from the US Census Bureau address geocoder or, where the street address could not be matched, the centre of the ZIP code (October 8, 2026). Set the county and its federal county code on 12 listings, matched to the US Census Bureau county list from the county the source records, the listing's map point, or its ZIP code area (October 8, 2026). Checked every map point against the state in its address and re-placed 0 points that fell outside that state (October 8, 2026). Flagged 0 addresses that are incomplete, a PO box, or missing a house number, in an address quality column (October 8, 2026). Checked that the row count, state count and field completeness published for this file were measured from the file itself (October 8, 2026).

### Isn't this free on peerlesscleaners.com?

The underlying records are public on peerlesscleaners.com. What you pay for is the work between that public release and this file: added the county to 12 listings and measured 12 rows. The current file was rebuilt October 8, 2026 from peerlesscleaners.com. Doing it yourself means downloading the full release, repeating each of those steps, and repeating them again every time the source updates.

### How complete is each field?

Measured on every row of the current file, the share of rows that carry each key field: phone 100%, website 100%, street address 100%, city 100%, state 100%, ZIP code 100%, latitude 100%, longitude 100%. 40 of 42 columns are filled on at least half the rows.